• TABLE OF CONTENTS
HIDE
 Front Cover
 Title Page
 Foreword
 Acknowledgement
 Table of Contents
 Introduction
 Demographic characteristics
 Land characteristics
 Land and labour relationships
 Summary
 Bibliography
 Appendix A - Calculation of the...
 Appendix B - Dan Mahawayi
 Appendix C - Doka
 Appendix D - Hanwa
 Appendix E - Glossary of Hausa...














Group Title: Samaru miscellaneous paper - Ahmadu Bello University Institute for Agricultural Research ; 19, 23, 37-38
Title: An economic study of three villages in Zaria Province
CITATION THUMBNAILS PAGE IMAGE ZOOMABLE
Full Citation
STANDARD VIEW MARC VIEW
Permanent Link: http://ufdc.ufl.edu/UF00023855/00001
 Material Information
Title: An economic study of three villages in Zaria Province
Series Title: Samaru miscellaneous paper
Alternate Title: Economic survey of three villages in Zaria Province
Physical Description: v : ill. ; 30 cm.
Language: English
Creator: Norman, D. W ( David W )
Publisher: Institute for Agricultural Research, Samaru, Ahmadu Bello University
Place of Publication: Zaria Nigeria
Publication Date: 1967 (1974 printing)-<1972 >
 Subjects
Subject: Agriculture -- Economic aspects -- Nigeria -- Zaria (Province)   ( lcsh )
Economic conditions -- Zaria Province (Nigeria)   ( lcsh )
Genre: federal government publication   ( marcgt )
bibliography   ( marcgt )
statistics   ( marcgt )
non-fiction   ( marcgt )
 Notes
Bibliography: Includes bibliographies.
Statement of Responsibility: D. W. Norman.
General Note: Pt. 2- has title: An economic survey of three villages in Zaria Province.
 Record Information
Bibliographic ID: UF00023855
Volume ID: VID00001
Source Institution: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: aleph - 000560320
oclc - 02491845
notis - ACY5855
lccn - 76-374517//r83

Table of Contents
    Front Cover
        Front Cover 1
        Front Cover 2
    Title Page
        Title Page 1
        Title Page 2
    Foreword
        Foreword
    Acknowledgement
        Acknowledgement
    Table of Contents
        Table of Contents 1
        Table of Contents 2
        Table of Contents 3
    Introduction
        Page 1
        Page 2
        Page 2a
        Page 3
        Page 4
    Demographic characteristics
        Page 5
        Page 6
        Page 7
        Page 8
        Page 9
        Page 10
        Page 11
    Land characteristics
        Page 12
        Page 13
        Page 14
        Page 15
        Page 16
        Page 17
        Page 18
        Page 19
        Page 20
        Page 21
        Page 22
        Page 23
        Page 24
        Page 25
        Page 26
        Page 27
        Page 28
        Page 29
    Land and labour relationships
        Page 30
        Page 31
        Page 32
        Page 33
        Page 34
        Page 35
        Page 36
        Page 37
        Page 38
    Summary
        Page 39
        Page 40
    Bibliography
        Page 41
        Page 42
    Appendix A - Calculation of the fragmentation index
        Page 43
        Page 44
        Page 45
        Page 46
        Page 47
        Page 48
    Appendix B - Dan Mahawayi
        Page 49
        Page 50
        Page 51
        Page 52
        Page 53
        Page 54
        Page 55
        Page 56
        Page 57
        Page 58
        Page 59
        Page 60
    Appendix C - Doka
        Page 61
        Page 62
        Page 63
        Page 64
        Page 65
        Page 66
        Page 67
        Page 68
        Page 69
        Page 70
        Page 71
        Page 72
        Page 73
        Page 74
        Page 75
        Page 76
    Appendix D - Hanwa
        Page 77
        Page 78
        Page 79
        Page 80
        Page 81
        Page 82
        Page 83
    Appendix E - Glossary of Hausa terms
        Page 84
Full Text


SAMARU MISCELLANEOUS PAPER No. 19


AN ECONOMIC STUDY OF THREE


IN ZARIA


PROVINCE:


1. LAND AND LABOUR RELATIONSHIPS








,. 7-11
OCT 8W)
'. ^ : i -.-:. .


INSTITUTE
AHMADU


FOR AGRICULTURAL
BELLO UNIVERSITY


RESEARCH


SAMARU, ZARIA
NIGERIA


PRICE: TWO SHILLINGS


VILLAGES


A 0
". X*


1967







SAMARU MISCELLANEOUS PAPER No. 19


AN ECONOMIC STUDY OF THREE


IN ZARIA


PROVINCE:


1. LAND AND LABOUR RELATIONSHIPS




by D. W Norman


INSTITUTE
AHMADU
SAMARU,
NIGERIA


FOR AGRICULTURAL RESEARCH
BELLO UNIVERSITY
ZARIA


VILLAGES




















p/So




./


4
'I-
..J. .~


SCIENCE
LIBRARY








FOREWORD


In the period October 1965 to March 1967 the Rural Economy
Research Unit carried out an agro-economic study of three villages
in Zaria Province. In the latter part of the same period geographical
and sociological studies were also started and the results will be
published in separate reports.
The results of the economic study will be published in four reports:
1. The first report (Part I) deals with the demographic and land
holding relationships of the three villages. In this report are
considered all the inhabitants and land farmed by each village.

2. The second report (Part II) considers the input-output study
undertaken for a sample of farmers in each village. The sample
was drawn from the frame delineated in the first report.
3. The third report (Part III) consists of the maps delineating the
fields farmed by each household.
4. The fourth report (Part IV) contains -nple exercise in farm
planning on typical farms in the three Zaria villages.
It is anticipated the Parts I and III will be of more general interest
(e.g. to geographers and economists), while Parts II and IV are
expected to be of more specific interest to economists.
Because of the lack of detailed basic data on the economy of Northern
Nigeria it was considered desirable to include as much basic data as
possible in the appendices to enable other researchers to test hypo-
theses of their own.









ACKNOWLEDGE MENTS

The guidance and encouragement of the Director of the Institute for
Agricultural Research and other members of the Rural Economy
Research Unit Policy Committee have been a continual aid to the
research work.
I also wish to express my gratitude to all others who contributed to
this study. Without the help of junior staff, both field and office,
this report would not have been possible. Special thanks are due to
other RERU staff members (i.e. F. J. Buntjer, C. J. N. Gibbs,
J. C. Fine and M. Zaidu el Aliyu), Mrs W. Gibbs and F. Williams
for their help in constructing the maps. The helpful criticism and
aid of my colleagues are gratefully acknowledged. Finally special
acknowledgement is due to the villagers who co-operated in every
possible way.










CONTENTS


Page


CHAPTER I.


CHAPTER II.






CHAPTER III.


CHAPTER IV.


CHAPTER


BIBLIOGRAPHY
APPENDIX A.

APPENDIX E.

APPENDIX C.
APPENDIX D.

APPENDIX E.


INTRODUCTION


The aims of the study
Selection of the study area
Representativeness of the villages
Methodology
Plan of the report

DEMOGRAPHIC CHARACTERISTICS
Historical and ethnic origins of the
survey villages
Demographic characteristics
Occupations of gandu heads

LAND CHARACTERISTICS
Average size of holding
Size distribution of holdings
Field and distance relationships
Land tenure and land ownership

LAND AND LAFOUR RELATIONSHIPS
Land-labour ratios
Determinants of size of holding

SUMMARY


Calculation of the fragmentation index


Dan Mahawayi
Doka

Hanwa
Glossary of Hausa terms


FIGURES


Figure Al.


Location of fields farmed by gandu 25(1)
in Doka village 1966.


TABLES


Table 1.



Table 2.


Population and population densities of Zaria
Province and districts in which selected villages
were located

Percentage of gandu heads in the survey villages
according to tribal origin, 1966









Table 3A. Age distribution. Hanwa, June 1966
Table 3E. Age distribution. Doka, June 1966

Table 3C. Age distri'-ution. Dan Mahawayi, June 1966

Table 4. Average number of residents and labour units (LU. 1)
per gandu in the survey villages, June 1966
Table 5. Percentage of gandu heads with one, two and three
occupations in the survey villages, 1966
Table 6. Major and minor occupations of gandu heads in the
survey villages, 1966

Table 7. Average size and range in size of holding in the
survey villages, 1966

Table 8. Acres of fallow land and percentage of total land held
by a sample of gandaye in the survey villages, 1966
Table 9. Average number of acres of gona and fadama farmed
by a sample of gandaye in the survey villages, 1966


Table 10.



Table 11A.



Table 113.



Table 11C.



Table 12A.


Table 12P.


Table 12C.


Table 13.


Table 14A.


Table 141P.


Table 14C.


Table 15.


Average number and size of fields farmed by a
sample of gandu heads and other members of the gandu
in the survey villages, 1966
Number of farmers, fields and acres and average
value of fragmentation factor by size of holding.
Hanwa, 1966

Number of farmers, fields and acres and average
value of fragmentation index by size of holding.
Doka, 1966 (i) Central vil .ge (ii) Unguwa

Number of farmers, fields and acres and average
value of fragmentation index by size of holding. Dan
Mahawayi, 1966 (i) Central village (ii) Unguwa

Size and number of individual fields according to
distance factor. Hanwa, 1966

Size and number of individual fields according to
distance factor. Doka, 1966

Size and number of individual fields according to
distance factor. Dan Mahawayi, 1966

Per cent of total acreage and fields within 750 yards
of the place of residence in the survey villages, 1966.

Land tenure pattern of fields farmed by gandaye.
Hanwa, 1966
Land tenure pattern of fields farmed by a sample of
gandaye. Doka, 1966

Land tenure pattern of fields farmed by a sample of
gandaye. Dan Mahawayi, 1966

Acres and cultivated acres per resident, per labour
unit available for work outside the compound (LU. 2)
and per labour unit available for farm work (LU. 3) for
a sample of gandaye in the survey villages, 1966









Table 16. Hypothesised signs on the determinants of size of
holding equations

Table 17A. Determinants of the size of holding equations
Hanwa, 1966
Table 17E. Determinants of the size of holding equations
Doka, 1966

Table 17C. Determinants of the size of holding equations
Dan Mahawayi, 1966

Table Al. Computation of fragmentation index for gandu 25 (1) in
Doka, 1966
Table A2. Constants used in calculating fragmentation indices
in the survey villages, 1966

Table Bl. Number of residents and labour units according to
gandu. Dan Mahawayi, June, 1966

Table B2. Distribution and description of fields according to
gandu farming them. Dan Mahawayi, 19r6

Table Cl. Number of residents and labour units according to
gandu. Doka, June 1966

Table C2. Distribution and description of fields according to
gandu farming them. Doka, 1966

Table Dl. Number of residents and labour units according to
gandu. Hanwa, June 1966
MAPS

Map 1A* Dan Mahawayi village, Giwa District, Zaria Province:
field boundaries with serial numbers

Map 1B* Dan Mahawayi village, area within village wall, Giwa
District, Zaria Province: field boundaries with serial
numbers

Map 2A* Doka village, Makarfi District, Zaria Province: field
boundaries with serial numbers

Map 2B* Doka village, areas within village wall, Makarfi
District, Zaria Province: field boundaries with serial
numbers

Map 3* Hanwa village, Sabon Gari District, Zaria Province:
field boundaries with serial numbers

Map 4 Location of villages in Zaria Province


* Published separately as Samaru Miscellaneous Paper No. 23.









AN ECONOMIC STUDY OF THREE VILLAGES IN ZARIA PROVINCE

I. LAND AND LABOUR RELATIONSHIPS

I. INTRODUCTION

In any developing economy labour, and sometimes land, are the two
factors of production likely to be most abundant in agriculture.
Northern Nigeria unlike some developing regions of the world experi-
ences abundant land, but not labour. For example, in Zaria Province
in 1952 the population density was 49 persons per square mile
(9, p. 15). Nevertheless agriculture contributed significantly to the
economy of the Province with-about 75 per cent of the working popu-
lation being engaged in agriculture in 1952 (9, p. 21). In 1957-8 a
total of 830,000 acres (7 per cent of the total land area) was under
farm crops (5, Table 1). In terms of income agriculture accounted
for 64.2 per cent of Northern Nigeria's contribution to the gross
domestic product of the Federation in 1957 (10. p. 46).

THE AIMS OF THE STUDY

The aims of the part of the economic study presented in this report
were:
1. to describe the population and farmland characteristics of
each of the three selected villages. This was necessary before
undertaking the input-output investigation described in the
second part of this study

2. to investigate the land and labour relationships which exist in
each village.

SELECTION OF THE STUDY AREA

To permit an intensive study only three villages were selected. The
selection of the three villages was based on the concept that marked
differences between villages may arise as a result of differences in
ease of communication with, and in distance from, urban areas. In
more formal terms this can be stated in terms of Von Thunen's con-
centric ring theory (12, p. 320-1) or in terms of a more sophisticated
statement of the same concept, i.e., Schultz's locational matrix hypo-
thesis (21, p. 146). In this hypothesis it is reasoned that farmers'
incomes will tend to be higher nearer urban areas than those situated
farther away owing to greater efficiency of the factor and product
markets. The hypothesis has been stated as follows:

'1. Economic development occurs in a specific locational matrix;
there may be one or more such matrices in a particular
economy. The process of economic development does not
necessarily occur in the same way, at the same time, or at the
same rate in different locations.

2. These locational matrices are primarily industrial-urban in
composition; as centres in which economic development occurs,
they are not mainly out in rural or farming areas although some
farming areas are situated more favourably than are others in
relation to such centres.
3. The existing economic organisation works best at or near the
centre of a particular matrix; and it works less satisfactorily










in those parts of agriculture which are situated at the
periphery of such a matrix" (20, p. 205).

The hypothesis has been found to have some degree of validity in
explaining geographical differences in both developing, e.g., Brazil
(13), and developed, e.g., U.S.A. (1, p. 202; 15, p. 145), countries.
Therefore the main criterion used in the selection of the villages was
that the three villages should differ in ease of communication with
and distance from Zaria City and should be representative of other
villages in the same general location.

To ensure the successful completion of the study several sub-criteria
of a more practical nature were taken into account in the final
selection of the three villages:
1. Some assurance was necessary that the villages would remain
co-operative throughout the period of the study, i.e., about 1.5
years. Experience has indicated that the village head is most
influential in determining the attitude of the village as a whole.
Great care was therefore taken to find village heads who would
be sympathetic towards the aims of the project.
2. Village areas devoid of steep slopes were selected thus enabling
aerial photographs to be used without needing to correct field
measurements for distortion due to slopes.
3. The limited time available for constructing farm maps neces-
sitated the selection of village areas or sections of villages
that did not amount to more than 1,000 inhabitants for each area.
4. To ensure adequate supervision of the enumerators throughout
the farming year it was considered necessary that even the
most isolated village should be accessible, at least by bicycle,
during the rainy season.

Three villages were finally selected as follows:

1. Hanwa situated in Sabon Gari District and bordering on Zaria
Township.

2. Doka, I cated in Makarfi District and situated about 25 miles
from Zaria on the main Kano-Zaria road. This enables pro-
ducts to be transported to the Zaria market throughout the year.

3. Dan 1Mahawayi in Giwa District, was selected as the isolated
village. The village is situated about 20 miles from Zaria, the
last seven miles of which are motorable only during the dry
season.

The location of the villages is illustrated in Map 4, while Table 1
illustrates the population gradient away from Zaria. In addition the
rate of population increase for the period 1952 to 1963 as expected
has been greater in areas close to Zaria City.

REPRESENTATIVENESS OF THE VILLAGES
Limits imposed by both time and staff restricted the study to three
villages. In addition the proposed mapping of the villages would not
have been practicable with a larger number.

As a result the study could perhaps be legitimately criticised on the
basis that the selected villages were not representative of the study







Map 4.


Location of villages in Zaria Province


MILLs 4


SCALE:-1:250,000 OR 1'70 3-9SMILES
4 MILES


R E F E REN C E
Tarred Roads--- -----__-__
Bush tracks- ------- _______--
Streams- --- --- -- __ __ _-.- s
Villages used in Survey- -_--_ HANWA
Other Centres --- Zara


---~ 'i- --- -- "-- ~-- --:;---


. I I


-









Table 1. Population and population densities of Zaria Province
and districts in which selected villages were located



Administrative Population Population density Rate of population
unit 1963 (Persons/square increase (per cent
mile) per annum) 1952-63
1952 1963

Province:
Zaria 1,553,300 49 80 6.82

Districts:
Sabon Gari 62,476 411 842 9.54
Makarfi 114,104 179 345 8.45
Giwa 54,074 56 75 3.18

Villages:
Hanwa 2,718 8.80
Doka 1,983 5.54
Dan Mahawayi 1,269 0.27

Sources: (18, Bulletin 4; 14. p. 102, 232-49; 9. p. 15; 17).
aExceptionally high figures in this column may be a reflection
of an inaccurate 1963 census. The relative increases between
different villages and districts are consistent with expectation.

area. Two observations may answer this criticism:
1. Throughout the study there was no indication that the villages
were in any way unique compared with other villages in the
same relative location. Of course marked differences did
arise between the selected villages, but this was to be expected
as a result of the main criterion adopted in their selection.
2. The use of capital in developed countries increases both the
range and variability of combinations of resources and enter-
prises. Such a situation complicates even further the problem
of selecting representative farmers. However, in some
developing economies, e.g., Northern Nigeria, capital is still
largely an insignificant input in peasant farming. In the area
under consideration in this study, i.e., the northern part of
Zaria Province, mixed farmers, or farmers using oxen in
their farming operations, are virtually absent. The possibili-
ties of variations in resource and enterprise combinations in
a hand labour system of agriculture are very limited thereby
simplifying the selection of representative villages. Clayton
(2, p. 81) has used the same argument to justify the selection
of representative farmers for investigation and making
generalisations from the results.
METHODOLOGY
To facilitate field work an identification number was painted on each
compound. This was followed by a detailed enumeration of the popu-
lation in each of the three villages. The aim of the enumeration was
to provide frames or lists of the farmers in each village from which









samples could be drawn. Another more detailed enumeration car-
ried out by the rural sociologist near the time of completion of the
economics field work provided a check on the initial data collected.
In March 1966 aerial photographs were taken of Dan Mahawayi and
Doka village areas. Two areas of 36 square miles centred on each
village were flown at a scale of 1:10,000. Aerial photographs of
Hanwa at this scale were already available. Two-diameter enlarge-
ments of a limited number of photographs were made for use in the
field. The boundaries of the fields farmed by each individual in the
frame were delineated on the enlarged aerial photographs as a result
of visiting each field personally. In addition a check survey was
carried out later in the year on all fields farmed by individuals in the
master sample. From this information it was possible to construct
farm maps. The sizes of the individual fields were measured by
means of a planimeter. Additional information on field type, soil
type and type of tenure was collected for each field from all the
farmers in the master sample. A simple random sample of about
40 farmers was drawn in each of the three villages.
PLAN OF THE REPORT
The report is confined to the two most significant factors of produc-
tion in a developing country, i.e., labour and land.
Consequently Chapter II is devoted to the demographic characteristics
of the three selected villages, while Chapter III deals with the land
relationships. Chapter IV considers the labour-land relationships
existing in the three villages.
Data concerning each of the numbered fields on Maps 1A, 1B, 2A,
2B and 3 are contained in Appendices B, C and D of this report
together with some demographic data.









II. DEMOGRAPHIC CHARACTERISTICS


In the study area villages often consist of a number of residential
clusters which although separated from each other come under the
jurisdiction of a village head. The village head usually lives in the
main residential cluster sometimes known as the central village or
central cluster. The other residential clusters are known as ungwoyi
(s. unguwa) or hamlets. In actual fact the central village may also
be divided into wards which are also sometimes called ungwoyi.
However in this report the term unguwa will be used only in reference
to a hamlet which is physically separated from the central village.
In each residential cluster there are a number of compounds each of
which is usually surrounded by a wall or fence and often has only one
entrance.
Smith (22, pp. 18-20) in his discussion on the social organisation of
the compound has differentiated three social units. The compound
which is a physical unit is sometimes partitioned off by fences into
sassal. Such a situation, for example, arises when the head of the
compound has an adult son or dependent adult male relative living
with him. A social unit which is often synonymous with the sassa is
the iyli or individual family which usually includes a man, his wives
and his dependent children. Finally there is the gandu or work unit
which is "a separate unit of domestic economy with common produc'-
tion and consumption of food, a single head, a common pot, a com-
mon granary and a common farm" (22, p. 19). No attempt is made
to investigate these phenomena more thoroughly since this will be
discussed in greater detail in a later report by the rural sociologist.
For the purposes of this study a family was defined as "those people
eating from one pot. "2 It was assumed that such a group constituted
an economic unit. In the villages studied in Zaria Province the data
collected about gandu and "those persons eating from one pot" gave
identical results. Consequently, in the villages selected in Zaria
Province and as far as this study was concerned, a gandu was con-
sidered as synonymous with "those persons eating from one pot. "3
In this study the term gandu will be considered synonymous with
family, work unit and economic unit.






1. Unless otherwise stated, all underlined words embodied in the
text itself are Hausa words.
2. In Hausa those eating from one pot is expressed as: "suna ci
daga tukunya daya. This is the definition for a family adopted
y the Federal Office of Statistics in their Agricultural Sample
Surveys.
3. It should be noted that the term gandu does not necessarily have
the same connotation throughout Hausaland. In fact, preliminary
results in the current survey in Sokoto Province indicate that
gandu has an entirely different meaning. However preliminary
results indicate that the term "persons eating from one pot" is
satisfactory in all three provinces studied to date, i.e.,Sokoto,
Bauchi and Zaria.









HISTORICAL AND ETHNIC ORIGINS OF THE SURVEY VILLAGES1

Hanwa
Hanwa appears to have been permanently settled about 150 years ago.
The central cluster, some of the inhabitants of which consider them-
selves descended from two brothers who came from Katsina Province,
is surrounded by four hamlets or ungwoyi and a few scattered com-
pounds. Investigations were confined to a complete enumeration of
the central cluster and one of the ungyi.
Doka
The central village area was first settled about 100 years ago as a
result of the resettlement of some of the inhabitants from Dan Sambo
village in Kano Province. The reason for the move was said to be
an exhorbitant tax burden. The one main unguwa included in the enu-
meration has a more recent history of settlement (i.e., about 75
years).
Dan Mahawayi
Dan Mahawayi is reputed to have been founded about 150 years ago
by a pagan although like the other two villages it is now completely
Moslem in faith. During the laying of the Gusau-Zaria railway the
Emir of Zaria compelled many villagers to help in its construction.
As a result many fled into Katsina Province and never returned.
The central village and one unguwa were included in the enumeration.
Once again the unguwa was settled at a later date as a result of
individuals moving from the central village.
Ethnic origins
A simple comparison of the tribal origins of the gand heads in the
three villages is given in Table 2. In Dan Mahawayi and Hanwa
there is a high proportion of gandu heads who are Fhlani. In contrast
Doka is almost completely Habe in composition. 2
An interesting difference between the Fulani in Hanwa and Dan
Mahawayi is that in the former village about 79 per cent of the Fulani
gandu heads own cattle, while in the latter village there are no cattle
owners. No instances were found of persons of other tribal origins
owning cattle.
DEMOGRAPHIC CHARACTERISTICS
The population enumeration was carried out in both January 1966 and
January 1967. From this data it was possible to compile the popula-
tion fi;- res which existed in June 1966.
An interesting age and sex distribution emerges from the data pre-
sented in Tables 3A, 3B and 3C. The general trends are consistent
1. The material in this section will also be discussed in greater
detail by the rural sociologist in a future report. The inclusion
of the section is justified on the basis that it helps explain some
of the relationships discussed later in this report.
2. No attempt was made to classify the gandu heads into groupings
more satisfactory from an anthropological point of view. The
simple classification used here was considered sufficient for
the purposes of the economic study.









Table 2. Percentage of gandu heads in the survey villages according
to tribal origin, 1966


Village Percent of gandu heads in each tribal group Total
Habe Fulani Kanuri Others number
of gandu
heads

Hanwa 50.00 47.72 1.14 1.14 88
Doka 97.39 1.96 0.65 0.00 153
DanMahawayi 47.71 43.12 8.26 0.91 109

Average 70.00 26.29 3.14 0.57 350

with those found by Mortimore and Wilson (11, pp. 29-33) in the Kano
area. There is a high percentage of the total population in the lower
age groups with a concomitant smaller proportion in the older age
groups. In fact in all three villages about 50 per cent of the popula-
tion are less than 20 years old. This could imply a rapid increase
in population, although at the present time this is still being tem-
pered by a low average expectation of life. Mortimore and Wilson
(11, p. 33) note that in a hand labour economy where the area culti-
vated is dependent on the number of workers available such a skewed
population is desirable. However, it is likely that in the fairly near
future, as a result of better medical services, there will be a greater
proportion in the less productive higher age groups that will require
supporting.
An additional characteristic is the trend in the male/female ratios as
age increases. In general Table 3 indicates that the ratio of men to
women shows at the lower ages a slightly negative correlation with
age and then from 10 years old and more a positive correlation with
an increase in age. Two features arise from this observation:

1. The small male/female ratios in the 10 to 29 age range indicates
a preponderance of females. As Mortimore and Wilson (11, p.
29) note this is related to the polygamous nature of marriages.
2. Assuming the population pyramid changes little over time, a
feature is the implication that women in the 20-29 age range
have on average only about half the chance of men to live to be
more than 60 years of age. Once again Mortimore and Wilson
(11, p. 29) report similar findings in Kano Province.
There is an imbalance in the male/female ratio for the three villages,
i.e., 0.91, which compares with the figure of 0.95 for Zaria Province
in 1952 (18, Fulletin 4).

Table 4 illustrates the average size of family and number of labour
units per gandu in the survey villages.

From the economic point of view it is necessary to differentiate be-
tween the number of residents in the garru and the number of persons
in the gandu who are in a position to contribute to its income. As a
result the term labour unit is often used to assess the magnitude of
the potential productive capacity of a family. It is appreciated that
such a measure is arbitrary in nature, but often it is more realistic
to discuss economic phenomena in such a way rather than in terms of









Table 3A. Age distribution. Hanwa, June 1966


Age Numbers Male /female
(years) Male Female Total Percent Cumulative ratio
of total percentage
Less than 10 131 121 252 34.85 34.85 )
10-19 75 63 138 19.09 53.94 )
20-29 51 86 137 18.95 72.89 )
0.76
30-39 44 39 83 11.48 84.37 )
40-49 31 19 50 6.91 91.28 )
50-59 17 18 35 4.84 96.12 )
60 or more 13 15 28 3.88 100.00 0.87
All ages 362 361 723 100.00 1.00


Table 3B. Age distribution. Doka, June 1966

Age Numbers Male /female
(years) Male Female Total Percent Cumulative ratio
of total percentage
Less than 10 146 176 322 31.41 31.41 )
10-19 95 128 223 21.76 53.17 )
20-29 87 134 221 21.56 74.73 0.83
30-39 66 50 116 11.32 86.05 )
40-49 40 30 70 6.83 92.88 )
50-59 23 10 33 3.22 96.10 )
60 or more 21 19 40 3.90 100.00 1.11
All ages 478 547 1,025 100.00 0.87


Table 3C. Age distribution. Dan Mahawayi, June 1966

Age Numbers Male /female
(years) Male Female Total Percent Cumulative ratio
of total percentage
Less than 10 89 104 193 28.99 28.99 )
10-19 65 70 135 20.27 49.26 )
20-29 53 75 128 1: 2 68.78 )
0.82
30-39 43 43 86 13.06 81.84 )
40-49 25 34 59 8.86 90.70 0.84
50-59 18 17 35 5.25 95.95 )
60 or more 16 11 27 4.05 100.00 1.45

All ages 309 354 663 100.00 0.88

family size. In this study a labour unit was considered to be an
adult male between the ages of 15 and 64. Two assumptions were
employed in assigning labour unit equivalents to different sex and
age groups:

1. Physical labour productivity shows initially a positive correlation
and then a negative correlation with increases in age.
2. The physical labour productivity of women is lower than that of
men.









Table 4. Average number of residents and labour units (LU. 1) per
gandu in the survey villages, June 1966

Village No. of No. of Residents per gandu Labour units per gandu Resident
Cpds gandu Av. Min. Max. Av. Min. Max. / labour
unit ratio

Hanwa 77 88 8.21 2 30 4.70 1.75 16.75 1.75
... 90 153 6.70 2 31 3.84 1.50 15.75 1.74
Dan Mahawayi 88 109 6.08 1 21 3.60 0.75 12.25 1.69


Total


255 350 6.89 3.98 1.73

On the basis of these assumptions the following labour unit (LU. 1)1
equivalents were assigned:

Age Sex Labour unit
(years) equivalent
Less than 6 Male and female 0.00
7-14 Male and female 0.50
15-64 Male 1.00
15-64 Female 0.75
65 or more Male and female 0.50

The average number of residents per family or gandu was found to
be about seven persons; Hanwa was a little higher, while Doka and
Dan Mahawayi were a little lower. The same relationships were
found to exist when potential income earners were expressed in terms
of labour units (LU. 1). The average number of labour units per
gandu was found to be about four.

Of particular interest was the fact that the ratio of residents to
labour units (LU. 1) was almost exactly the same in each of the three
villages, i.e., about 1.7.
OCCUPATIONS OF GANDU HEADS
The long, dry season and limited amount of fadama2 land in Zaria
Province has caused villagers to find some other sources of income
to supplement that obtained from agriculture. Apart from Hanwa,
time devoted to these additional occupations shows an inverse cor-
relation to that devoted to farming.

A breakdown of the major and minor occupations of gandu heads is
shown in Table 6. Tables 5 and 6 serve to emphasise the fact that
the proximity of Hanwa to Zaria and the ensuing off-farm employ-
ment opportunities together with the ownership of cattle by the Fulani
residents, means that a greater proportion of gandu heads supple-
ment their incomes from off-farm sources than in Doka and Dan
Mahawayi.
1. The reason for the symbol LU. 1 is that the labour unit equivalents
will be modified later in the report to reflect labour available
for work outside the compound (LU. 2) and labour available for
work on the farm (LU. 3).
2. Fadama or lowland fields are found where the water-table is
near the surface, e.g., near streams, and as a result they are
often irrigated during the dry season.










Many of the labouring jobs in Zaria held by Hanwa village provide a
regular source of employment throughout the year, in contrast to
Dan MIahawayi and Doka where off-farm employment opportunities
are considerably more circumscribed. Lack of proximity to off-
farm employment opportunities means that most off-farm activities
are of minor importance and tend to be confined mostly to the dry
season. It is interesting to note from Table 6 the importance of
weavers in Doka and the increase in the proportion of gandu heads
who do some trading as communications with Zaria become more
difficult. It should be noted that other members of the gandu also
often have other occupations. The dominance of the ku~e type of
marriage means that many women work at occupations that can be
carried out inside the compound, e.g., spinning, weaving, making
cooked food which is hawked by young daughters and sons, etc.

Table 5. Percentage of gandu heads with one, two and three occupa-
tions in the survey villages, 1966


Village Percentage of gandu heads

One Two Three
occupation occupations occupations

Hanwa 17.04 75.00 7.96
Doka 43.14 50.98 5.88
Dan Mahawayi 35.78 58.71 5.51









Table 6. Major and minor occupations of gandu heads in the survey villages, 1966


Occupation of gandu heads
Degree of Primary Manufacturing _Service _Others Total
age emphasis Farming Herds- Black- Builder Weaver Butcher herb Public Koranic Broker c d Lab-Beg- number
Other oc. teacherrader Other
man smith and/ or &/ or officialteacher our- going
e
thatcher tailor ing
out-
side
vill-
ige

Hanwa
HanwaMajor 53 3 1 1 1 1 1 1 27 88

Minor 28 29 2 1 1 1 8 10 80
Doka Major 148 1 1 1 1 1 153

Minor 5 1 19 7 5 1 17 6 16 9 6 4 96
Danahawayi Major 97 1 1 2 1 5 2 109
Minor 6 4 5 4 2 3 1 5 33 12 1 76

a Major occupations are classified as those to which over 50 per cent of the gandu head's time is devoted, while minor occupations are those
on which a smaller proportion of the gandu head's time is spent.
b Includes a leather worker, a potter and sugar makers.
c Articles traded include sugar-cane, mangoes, peppers, salt, kola nuts, guinea-corn, millet, palm oil, fish, cassava, groundnuts and
cotton, sweets, eggs, hens, sheep, cigarettes, soap, hides, clothes, grass and mats.
d Includes farm and other paid labourers who work in the village, barbers, a washerman, a firewood cutter, bicycle mechanics, a native
doctor, musicians and a magician.
e Include stewards, servants, road workers, commission agents, porters, lorry park attendants, gardeners, and labourers employed by
the Native Authority, J. Allen and Co. Nigerian Tobacco Company, the Electricity Corporation of Nigeria and the Nigerian Railway
Corporation.









III. LAND CHARACTERISTICS


It was noted in Chapter I that two-diameter enlargements of aerial
photographs flown at a scale of 1:10,000 were used in the field identi-
fication. Mapping was accomplished by visiting each field and draw-
ing the boundaries on the aerial photographs. The initial mapping
was carried out during the period March to June 1966. Later in the
year in October and November, every field farmed by the gandaye in
the master sample was visited to check the boundaries.
For the sake of uniformity a field was defined as contiguous pieces
of land farmed by one gandu. This was necessary since the farmers
tend to differentiate fields according to general location, the way
they were initially acquired, soil type, etc.
The identification number of the family or gandu farming each piece
of land was determined. The size of the fields was measured by
means of a planimeter. Finally it was possible to calculate the size
of holding or farm1 farmed by each gandu by adding the acreages of
all fields farmed by the family or gandu in question.
It is important to note that size of holdings or farms were calculated
on the basis of those on which members of the gandu held the rights
of production in 1966. Therefore it included fields rented from
other gandaye, but not those belonging to the gandu which were rented
or leased to individuals outside the gandu in question.
A master sample of about 40 farming families in each village was
chosen at random. For each of these gandaye additional information
on each field was obtained. Such information included the name of
the person farming each field, the type of field, the soil type and
the mode of tenure under which each field in the farming gandu was
held.
AVERAGE SIZE OF HOLDING
According to the Federal Office of Statistics (5, p. 12; 6, p. 14) the
average size of holding in Zaria Province in 1957-8 was 4.5 acres,
while in 1963-4 for the North as a whole it was 4.59 acres.
Compared with these statistics it was found that somewhat higher
figures were obtained in the survey villages. Table 7 indicates that.
the average number of acres farmed by each gandu in 1966 was 5.94
acres in Hanwa, 8.79 acres in Doka and 10.09 acres in Dan Mahawayi.
Such a situation is consistent with the notion that farmers in more
densely populated areas (e.g., Hanwa) will tend to have smaller sized
holdings than those in areas where the population density is less
(e.g., Dan Mahawayi). The lower population densities have resulted
in a larger range in the size of holding in Doka and Dan Mahawayi
compared with Hanwa. In Doka the average size of holding in the
unguwa is almost the same as in the central village (i.e., about 8.7
acres), but in Dan Mahawayi the small number of residents in the
unguwa has resulted in a very large average size of holding (i.e.,
14.4 acres) compared with 9.62 acres in the central village.
Another reason, in addition to differing population densities, which
helps explain the diversity in the range of average size of holding in

1. In this report holding and farm were considered synonomous.
All the fields farmed by a gandu constitute the farm or holding.









the survey villages is the amount of fallow land. It can be hyptith-sised
that the amount of fallow land will exhibit a negative correlation with
the population density. Table 8 in fact indicates that the village in
the area with the highest population density (i.e., Hanwa) has only
about two per cent of the land in the sample under fallow compared
with about 19 per cent under fallow in the village situated in the least
densely populated area (i.e., Dan Mahawayi).
An inconsistency may at first glance appear to exist between Doka
and Dan Mahawayi in that the former village, situated in area of
higher population density and a lower average size of holding, has,
in fact, a greater percentage of land under fallow. However, Table
9 serves to indicate that Doka has a lower gona/fadara ratio implying
that a higher proportion of the acreage of an average holding in Doka
consists of the higher quality fadama. Gona or upland fields can only
be cultivated during the rainy season, while fadama or lowland fields
are found where the water-table is nearer the surface, e.g., near
streams. Fadama fields, which are often irrigated during the dry
season, can support crops throughout the year. The higher quality
fadama supports intensive crops, e.g., sugar-cane, rice, yams, etc.,
while on the gona are grown more extensive crops, e.g., guinea-corn,
millet, cotton, etc. These labour-intensive and high-value-per-acre
fadama crops may be substituted to some extent for the less labour-
intensive and lower value-per-acre gona crops. This may partially
account for the slightly higher percentage of fallow land in Doka
compared with Dan Mahawayi.
Table 7. Average size and range in size of holding in the survey
villages, 1966

Name of village Section Number Size of holding (acres)
of of Average Smallest Largest
village holdings
Hanwa Wholea 64 5.94 0.06 15.90
Doka Central 77 8.79 0.17 54.43
Unguwa 76 8.58 C 60 22.45
Whole 153 8.69 -
Dan Mahawayi Central 93 9.62 0.18 53.57
Unguwa 10 14.43 2.73 38.63
Whole 103 10.09 -
Total Whole 320 8.59

a In Hanwa the unguwa is situated very close to the village. There-
fore it was considered unnecessary to separate it from the central
village. In addition only those compounds in which the gandaye
were fully differentiated have been included. (See note in
Appendix D. )
Although there appears to be valid reasons for the differences in the
average size of holdings in the survey villages, there still remains
the problem of explaining the lower figures obtained by the Federal
Office of Statistics. One practical problem that was met in the field
work was the tendency of farmers not to disclose all their fields.
This problem was eliminated by the complete mapping of the village
areas.
1. Before the mapping was carried out gandu heads were asked
(continued on next page)










However, in the case of the Federal Office of Statistics this solution
would not be practical. In addition to the natural reluctance of
farmers to disclose possession of all their fields, the following factors
may cause the farmers completely unintentionally not to disclose all
their fields:
1. Fallow fields are often not disclosed simply because they are
not being cultivated! A possible indication of the significance of
this omission can be gleaned from Table 8.
2. Often fields farmed by members of the gand other than the head
are not disclosed. These gayauna fields are farmed completely
independently of the gandu head, the person farming it having
the right to the crops produced from it. However, such
members of the family still have obligations to work on the fields
under the direct control of the gandu head. Table 10 indicates
that gayauna fields tend to be smaller than the fields farmed by
the gandu head, while the amount of land held under such an
arrangement may differ markedly from village to village (e.g.,
15 per cent in Hanwa and 5 per cent in Dan Mahawayi).

Table 8. Acres of fallow land and percentage of total land held by a
sample of gandayea in the survey villages, 1966b


Village Number of gandaye Av. number of Percent of total
in sample fallow acres land that is fallow
per gandu

Hanwa 38 0.14 1.99
Doka 44 2.31 23.51
Dan Mahawayi 42 2.26 18.96

a Unless otherwise stated all Tables based on a sample of gandaye
include all those in the master sample.
b Bush land which is not held by any gandu is excluded.

Table 9. Average number of acres of gona and fadama farmed by a
sample of gandaye in the survey villages, 1966a

Village Av. number of acres per Gona/fadama
holding ratio
Gona Fadama
Hanwab 5.30 0.35 15.14
Doka 7.84 1.04 7.54
Dan Mahawayi 9.73 0.96 10.13

a Fields that are part gona and part fadama were excluded from the
Table.
b The figures. for Hanwa are calculated on the basis of all the
differentiated gandaye in the village.
how many fields did the gandu possess the rights of production
over in 1966. The number given was checked with that found as
a result of the mapping. In Hanwa farmers initially disclosed
about 90 per cent of their fields while in Dan Mahawayi they
disclosed only about 70 per cent of the fields.










Table 10.


Average number and size of fields farmed by a sample of
gandu heads and other members of the gandu in the survey
villages, 1966a


Village Fields farmed Fields farmed Av. number of
by by other acres per gandu
Sgandu head gandu residents not farmed by
gandu head
Number Average Number Average
size size
Hanwa 205 1.06 52 0.82 1.12
Doka 254 1.61 21 0.89 0.43
Dan Mahawayi 254 1.83 30 0.76 0.55

a Fields farmed partly by the gandu head and partly by other gandu
residents are omitted.

SIZE DISTRIBUTION OF HOLDINGS

Table 11 indicates the size distribution of holdings in each of the
villages. One notable feature which is a common feature of so many
developing countries is the inequitable distribution of the land among
the residents of the villages. In quantitative terms 50 per cent of
the farmers hold only about 18 per cent of the total farm land in
Hanwa, and about 25 per cent of the total farm land in Doka and Dan
Mahawayi. Contrariwise 50 per cent of the farmers hold 82 per cent
of total farm land in Hanwa, and 75 per cent in Doka and Dan Maha-
wayi.

It is interesting to note that a larger size of holding entails having
more fields. Preliminary investigations in Hanwa (16, p. 103) indi-
cated that a correlation coefficient of 0.6490, which is significant at
the 1 per cent level, existed between the number of fields per holding
and the size of holding expressed in acres.. In addition Tables 11A,
11B and 11C indicate that the average size of fields also show a
positive relationship with the size of holding.


Number of farmers, fields and acres and average value


of fragmentation fadeor by size of
1966a


holding. Hanwa,


- C -


Farmers


Fields


Acres


Farmers_ I Field-


No.


P~2 cent
of total


No.


Av. No
per
hnolrlin


Average
size
(acres)


. No.


Per
cent of
total


Av. value of
fragmentation
index


than 0.25 1 1.56 1 1.00 0.06 0.06 0.02 19.19
to 0.49 2 3.12 3 1.50 0.27 0.80 0.21 22.99
to 0.99 0 -
to 2.49 18 23.12 37 2.05 0.80 29.63 7.80 39.92
to 4.99 12 18.75 60 5.00 0.69 41.67 10.96 49.18
to 9.99 16 25.00 83 5.19 1.44 119.34 31.40 62.05
to 24.99 15 23.45 100 6.67 1.89 188.58 49.61 65.73
to 49.99 0 -
or more 0- -
64 100.00 284 4.44 1.34 380.08 100.00 50.24


The gandaye which are not differentiated in
excluded from this analysis.


the tables given in Appendix D were


Table 11A.


Size of
holding
(acres)


0.25
0.50
1.00
2.50
5.00


-












Table 11E. Number of farmers, fields and acres and average value
of fragmentation indtlr' by size of holding. Doka, 1966
(i) Central village

Size of Farmers Fields Acres Av. value of
holding No. Per cent No. Av. No. Average No. Per fragme:
(acres) of total per size cent of index
holding (acres) total
Less than 0.25 1 1.30 1 1.00 0.17 0.17 0.03 6.25
0.25 to 0.49 0 -
0.50 to 0.99 1 1.30 1 1.00 0.54 0.54 0.08 6.25
1.00 to 2.49 9 11.69 29 3.22 0.64 18.47 2.73 55.87
2.50 to 4.99 15 19.48 62 4.13 0.92 57.29 8.46 69.87
5.00 to 9.99 26 33.76 148 5.69 1.27 181.52 26.80 69.92
10.00 to 24.99 23 29.87 226 9.83 1.46 331.40 48.93 72.62
25.00 to 49.99 1 1.30 22 22.00 1.52 33.42 4.93 86.52
50.00 or more 1 1.30 20 20.00 2.72 54.43 8.04 100.23

Total 77 100.00 509 6.61 1.33 677.24 100.00 68.03












(ii) Unguwa

Size of Farmers Fields Acres Av. value of
holding No Per ceni No Av. No. Average No. Per fragme
(acres) of total per size cent of index
holding (acres) total
Less than 0.25 0 -
0.25 to 0.49 0 -
0.50 to 0.99 3 3.95 7 2.33 0.31 2.16 0.33 19.75
1.00 to 2.49 4 5.26 9 2.25 0.73 6.55 1.00 28.39
2.50 to 4.99 18 23.68 79 4.39 0.86 68.37 10.48 50.13
5.00 to 9.99 26 34.21 185 7.11 1.00 185.08 28.38 62.00
10.00 to 24.99 24 31.58 204 8.50 1.73 353.04 54.15 54.42
25.00 to 49.99 1 1.32 8 8.00 4.61 36.88 5.66 79.38
50.00 or more 0 -

Total 76 100.00 492 6.47 1.32 652.08 100.00 53.59









Table 11C. Number of farmers, fields and acres and average value
of fragmentation fadto:- by size of holding. Dan
Mahawayi, 1966
(i) Central village


Size of
holding
(acres)


I.. than 0.25
0.25 to 0.49
0.50 to 0.99
1.00 to 2.49
2.50 to 4.99
5.00 to 9.99
to 24.99
to 49.99
or more


Farmers


No.


Per cent
of total

1.07

5.38
9.68
20.43
34.41
21.50
6.46
1.07


Fields


I. 4 4


No.


1

8
28
90
214
171
82
23


Av. No.
per
holding
1.00

1.36
3.11
4.74
6.69
8.55
13.67
23.00


Average
size
(acres)
0.18

0.41
0.54
0.84
1.22
1.66
2.45
2.33


Acres


No.


0.18

3.29
15.19
75.64
262.12
283.96
201.29
53.57


Per
cent of
total
0.02
-
0.37
1.70
8.45
29.28
31.72
22.48
5.98


Av. value of
fragment
index


6.25

15.63
51.48
53.26
76.25
72.91
88.25
93.48


93 100.00 617 6.63 1.45 895.24 100.00 65.46


(ii) Unguwa


Size of
holding
(acres)


S than 0.25
0.25 to 0-49
0.50 to 0.99
1.00 to 2.49
2.50 to 4.99
5.00 to 9.99
to 24.99
to 49.99
or more


Farmers
). Per cent
of total


20.00
30.00
30.00
20.00


No.


Fields


Av. No.
per
holding


1.50
2.67
4.00
7.00


Average
size
(acres)


1.91
2.57
4.47
4.60


Acres


No.


5.74
20.53
53.59
64.41


SPer
cent of
total


3.98
14.23
37.15
44.64


10 100.00 37 3.70 3.90 144.27 100.00 39.93


Fragmentation index

To express the distance of the fields
the place of residence and from each
anr rlpvlnncpdrl xrhih hn hbon ftrmodrl


Av. value of
fragmentation
index


13.28
34.44
48.81
61.48


farmed by the gandu from both
other a measure was designed
the frn mcmntntinn indrlp Tt is


a measure in which the limits of the values are near 0 and 200. A
value near 0 would imply that all the fields farmed by the gandu are
close together and also near the compound.


1. The method of calculating the fragmentation index is described in
detail in Appendix A. However, the notion that it is a relative
measure can be obtained from the following formula:


Actual fragmentation factor


Jrr~ L1 I ,d,11Ie1LdA1UI lli~, s.


I Potential fragmentation factor.
The potential fragmentation factor varies according to the
number of fields.


-


,


,









Conversely a very high value would imply that the fields farmed by
the gandu are widely scattered both from each other and from the
place of residence.
One fact arising from Table 11 is that the fragmentation index is
very much lower than it could be,the theoretical maximum being 200.
This in turn implies that gandaye tend to have their fields in the
same general location. Two factors could be responsible for this
situation:
1. Farmers may recognize the desirability of having their fields
close together. The potential saving in time in walking to the
fields and transporting manure, crops, etc., may stimulate the
farmers to make a conscious effort to acquire fields in the same
general location. There is some evidence that this may be
partly true in Hanwa. As will be discussed later in this chapter,
over half of the farm land in Hanwa is rented. 1 Consequently
farmers have the opportunity of acquiring fields which are in the
same general location. The average value of the fragmentation
index in Hanwa, i.e., 50.24, is significantly lower than those for
the central village areas of Doka and Dan Mahawayi, i.e., 68.03
and 65.46 respectively. 2
2. A more common situation is where farmers may recognize the
desirability of having fields close together, but are powerless
to ensure that such a situation arises. This is possibly true in
cases where the more "traditional" types of land tenure are
most common, e.g., particularly inherited land. However,
although it may be difficult to acquire more land in such villages,
there may be a counteracting influence ensuring a reasonable
concentration of fields farmed by one gandu. It appears that the
original settlers in such a village acquired large tracts of land,
usually in one or two locations. This land, through inheritance
decisions will to some extent be divided up, but the fields farmed
by these gandaye still appear to be in one or two general loca-
tions. 3 Such a situation may exist in Doka and Dan Mahawayi
where 78 per cent and 57 per cent of the total farm land is
inherited. 4 Although, all other things being equal, it is obviously
desirable to have a holding with a low fragmentation index,
there is according to Tables 11A, 11E and 11C a tendency for a
larger size of holding to carry with it an attendant increase in
the fragmentation index.
1. See Table 14A.
2. In fact the difference in average value between Hanwa and the
other two villages is greater than the figures imply. This is
due to the method used in calculating the fragmentation index.
(See Appendix A.)
3. It is hoped that some evidence in support of this statement will
arise from the work currently under way by the geographer
and rural sociologist into the mode of acquiring the rights of
production on specific areas of land.
4. See Tables 14B and 14C.









This in turn implies that a greater portion of time is devoted to
walking from one field to another and from the field to the com-
pound. However, it is interesting to note that the fragmentation
indices are lower in the ungwoyi than in the central villages.
For example, in Doka the average fragmentation index in the
central village is 68.03 compared with 53.59 in the unguwa, while
in the central village of Dan Mahawayi it is 65.46 compared with
only 39.93 in the unguwa. Two factors that may partially account
for the differences are:
1. The lower population concentrations and far less clustered
position of the compounds in the unguwa enable the gandaye to
have their fields closer to the compound.

2. The more dispersed nature the compounds in the unguwa may
result in a larger average size of field. This appears to be true
in the case of Dan Mahawayi, but not Doka. In the former village
the average size of field in the unguwa was about two and a half
times as large as in the central village (i.e., 3.90 acres com-
pared with 1.45 acres). Because of this and in spite of the larger
average size of holding in the unguwa (i.e., 14.43 acres compared
with 9.62 acres) the average number of fields per holding was
lower (i. e., 3.70 fields compared with 6.63 fields).
These characteristics help explain the lower average of the fragmen-
tation index to be found in the ungwoyi. This phenomenon implies
the desirability of farmers living in the ungwoyi nearer their fields
rather than in the central village with the concomittant increase in
remoteness of the fields.
FIELD BND DISTANCE RELATIONSHIPS
The distribution of fields according to the distance from the place of
residence is depicted in Tables 12A, 12B and 12C. The distance of
each field is calculated as the shortest distance of the furthermost
border from the place of residence.
The average size of gona and fadama fields in Hanwa and Doka and
the central village of Dan Mahawayi are very similar. The average
size of gona (i.e., about 1.7 acres) is almost three times as large as
fadama fields (i.e., about 0.6 acres).
With the exception of the ungwoyi in Dan Mahawayi and Doka, there
is a marked tendency in all three villages for the upland or gona
fields to increase in size with an increase in distance from the place
of residence. There are probably many reasons for this. The pre-
sence of the village has presumably had an influence on the demand
for land immediately surrounding the village over a considerable
length of time. This has resulted in fragmentation of the fields. As
population has increased land more remote from the village has been
brought into cultivation, but owing to its more remote location and
its being cultivated for a shorter period of time, it has not yet been
divided up as a result of inheritance decisions or intense competition
for farm land.
In the ungwoyi of Doka and Dan Mahawayi the relationship mentioned
above was not found. In the Doka unguwa there is no pronounced
relationship between the size of gona field and the distance from the
place of residence. This is consistent with what would be expected










in an area of physically dispersed compounds. In the Dan Mahawayi
unguwa the average field size actually decreases with an increase in
distance from the unguwa. This unguwa is situated near the Dan
Mahawayi village area boundary. Therefore the only fields that are
any distance from the unguwa are in the direction of the central
village. This means that the further the field is from the unguwa
the nearer it is to the central village and the resulting more intense
competition for land. An additional point to note is that the Doka and
Dan Mahawayi ungwoyi were settled after the central villages. The
short passage of time since settlement and lack of population concen-
trations have prevented the relationship between size of gona and
distance from the place of residence, as seen in the central villages,
from being evident in the ungwoyi.

In both the central villages and ungwoyi there appears to be in the
case of fadama no such relationship as that found for gona fields.
This is not surprising in that there is intense competition for the
limited quantity of fadama in each village.

Table 12A. Size and number of individual fields according to
distance factor. Hanwa, 1966

Distance Gona Fadama Total
factor Acres Av. field Acres Av. field A b Av. field No. of fields
Acres
size size size
2 30.39 0.84 1.76 0.35 32.40 0.77 42
3 23.80 0.66 7.92 0.53 35.00 0.65 54
4 19.56 0.93 7.61 0.54 29.11 0.79 37
5 29.83 1.03 7.80 1.56 39.86 1.14 35
6 26.73 1.07 1.06 0.53 27.79 1.03 27
7 36.04 1.44 0.75 0.13 3G.13 1.19 32
8 39.11 2.17 1.26 1.26 48.32 2.30 21
9 13.45 1.49 1.83 0.61 17.80 1.37 13
10 13.77 2.30 0.30 0.30 14.07 2.01 7
11 29.12 2.43 29.12 2.43 12
12 20.33 3.39 20.33 3.39 6
13 58.98 3.68 58.98 3.68 16
14 15.89 1.77 15.89 1.77 9
15 13.62 4.54 13.62 4.54 3
16-17 37.02 3.37 37.02 3.37 11

Total 407.64 1.56 30.29 0.58 457.44 1.41 325
a
Each unit of the distance factor is equal to 150 yards. For example
a total of 39.86 acres are situated between 600 and 750 yards from
the centre of the village.
SThe sum of gona and fadama acres does not always equal the total
acreage. This is due to the omission of fields that are partly gona
and partly fadama.

The furthermost field farmed by residents of the three villages was
1.4 miles for Hanwa, 2.0 miles for Doka and 2.1 miles for Dan
Alahawayi. One characteristic arising from Table 13 is that, as
population density decreases, the higher is the total percentage of
land near the place of residence. This relationship is true as one
moves from Hanwa to Dan l-ahawayi and from the central villages to
the ungwoyi.








Table 12F. Size and number of individual fields according to distance factor. Doka, 1966


(2Pntral villhuDP


Master sample


Fadamrna )Total
Acres Av. field Acresb
.size


Total


L i


Acres


Av. field
size


No. of
fields


Acres


Av. field
size


Uneuwa


Master sample


Acres


Av. field
size


Total
Acres


Total


Acres Av. field
size


No. of fields


I Is I Is I [ __ I J Iz J. -


2.29
1.30
2.11
5.01
10.39
1.82
0.32




0.10


0.57
0.65
1.05
0.76
0.61
0.36
0.32




0.10


14.68
7.49
28.44
20.64
40.66
22.68
32.63
18.04
10.47
2.34
3.03
3.48
7.01


43.69
44.23
79.84
76.47
114.89
112.80
89.34
46.41
42.51
7.05
3.03
3.48
7.01
3.56
2993.


0.55
1.23
1.29
1.47
1.79
1.61
0.99
1.55
3.27
1.76
1.51
3.48
2.34
3.56
2.93


10.82
61.5E
14.9,
20.8E
11.9E
40.9E
2.41
10.04
1.3E
1.47





1.7E


1.08
2.37
1.36
1.61
1.49
10.24
0.80
3.35
1.35
1.47





1.75


1.08
4.90
9.01
3.77
1.62


2
3
4
5
6
7
8
9
10
11
12
13
14
15
1 6- 24


0.27
0.70
0.56
0.54
0.32


14.68
7.49
18.85
19.34
38.55
15.60
11.30
16.22
10.15
0.99
3.03
3.48
6.91


10.83
65.64
33.69
33.77
15.73
42.5
12.41
10.04
1.35
1.4,7
0.6C

1.22

2.15


47.43
129.15
124.79
111.36
78.39
81.61
20.86
27.77
10.40
8.12
4.02
4.56
1.23

2.39


1.16
1.61
1.26
1.17
1.21
1.94
0.91
1.46
0.80
2.03
1.34
1.14
1.23

0.80


Acres


Av. field
siz 7


Distance
factora


0.51
2.50
1.45
1.62
2.27
1.42
2.26
5.41
3.38
0.99
1.52
3.48
3.46


0.60

1.23

0.40


0.60

1.23

0.40


Total 166.59 1.63 23.34 0.60 211.59 677.24 1.33 509 178.18 2.20 22.61 0.54 221.41 652.08 1.32 492
aSee footnote on Table 12A.
bSee footnote on Table 12A.
See footnote on Table 12A.


~"----~-----------~I-~---~I--


- -- I ~- --


Ceta---- v ---ill e .


--~-~--~


I r


I


r


I


-










Table 12C. Size and number of individual fields according to distance factor. Dlan Jahawayi, 1966


Distance Central village Thnguwa___
factor Master sample Total Master sample Tota
Gona Fadama Total C;_on.a Fadama Total
Acres Av. field Acres Av. field Acres Acres Av. field No. of Acres Av. field Acres Av. field Acres Acres Av. field No. of
size size size fields size size size fields
2 12.71 0.25 12.71 29.05 0.27 107 6.46 3.23 6.46 27,43 3.92 7
3 21.09 1.10 21.09 48.99 0.94 52 8.39 4.19 8.39 54.77 7.82 7
4 36.88 1.32 5.64 0.47 42.52 77.18 1.10 70 18.75 18.75 18.75 37.00 4.11 9
5 46.70 2.12 12.53 0.70 62.77 99.80 1.22 82 5.16 1.72 3
6 31.91 1.68 2.83 0.47 44.92 111.93 1.23 91 16.86 2.81 6
7 31.87 1.77 5.82 0.83 45.38 120.89 1.86 65 0.75 0.75 0.75 0.75 0.75 1
8 32.95 2.35 8.26 0.75 45.59 96.14 1.81 53 0.43 0.43 1
9 63.03 5.25 2.44 2.44 74.82 102.07 3.78 27 1.09 0.54 2
10 13.40 2.23 0.34 0.34 24.90 57.17 2.86 20 0.78 0.78 1
11 38.27 4.78 43.49 70.12 3.34 21 -
12 14.45 2.41 14.45 20.72 2.30 9 -
13 7.83 3.91 7.83 27.25 4.54 6 -
14 5.20 5.20 5.20 11.15 3.72 3 -
15 7.05 3.52 1.29 1.29 8.34 8.34 2.78 3 -
16-25 11.64 1.94 0.36 0.36 12.00 14.44 1.81 8 -
Total 374.98 1.78 39.51 0.68 466.01 895.24 1.45 617 33.60 6.72 0.75 0.75 34.35 144.27 3.90 37


foot note on
footnote on


Table 12A.
Table 12A.


a See
b See
See









LAND TENURE AND LAND OWNERSHIP

A detailed discussion on the intricacies of land tenure relationships
is beyond the scope of this report. This will be dealt with in greater
detail in a future report by the geographer and the rural sociologist.
Consideration in this report is confined to the effect of the tenurial
pattern on security of tenure and a comparison of the frequency of
different types of tenure in the three villages.
Traditionally land belongs to the Eniir, whose representative at the
village level is the village head. The latter distributes the land and
authorises and witnesses certain land transactions. It should be
emphasised that because the land is owned by the Emir an individual
can have only a usufructuary control over land. Theoretically, at
least, this may inhibit individuals from investing capital in improving
the farm land. However, in practice, there usually appears to be
little to fear of losing land on which rights of usufruct have been
inherited.

In addition to the local law and custom mentioned in the preceding
paragraph, Moslem law is also applied in controlling land tenure.
Moslem law is concerned with the way in which the land is divided
amongst heirs. Luning (7, p. 78) notes that under the basic law of
inheritance the properties of the deceased are valued on death. The
value includes goods, chattels and land over which there is right of
usufruct. The estate is then divided amongst all those entitled to a
share and none of the close relatives of the deceased can be over-
looked. According to Luning (7, p. 78) and Rowling (19, para. 34)
this division of the land at death is the main cause of fragmentation
of holdings. Certain transactions such as pledge, sale and loan are
recognized by Moslem law as long as they do not contravene the
customary laws.

Table 13. Per cent of total acreage and fields within 750 yards of
the place of residence in the survey villages, 1966.


Village Section of Percentage
village Acreage Fields

Hanwa Whole 29.81 51.69
Doka Central 36.06 45.19
Unguwa 63.29 64.02
Dan Mahawayi Central 54.72 50.40
Unguwa 86.20 70.27

Land transactions defined.

Six types of acquisition"and transaction involved in obtaining the right
to farm land were found in the survey villages. The following defini-
tions are based on those given by Luning (8, pp. 177-8 and 7, pp.
78-83). These are brief descriptions ard no attempt is made to
differentiate between the peculiarities that arise in different villages.

1. Inheritance (gado). Upon the death of the head of a family and
sometimes even before death the land is divided amongst the sons
and sometimes daughters.
2. Allocation and gift (kyauta). There are two variants of this type
of transaction:









a. The village head may allocate an abandoned farm or piece of
bush to a newcomer or to a local inhabitant who requires
some more farmland.
b. The land holder may give a piece of land to relatives or close
friends. Gift land can be inherited by the descendents of the
original recipient of the land.
3. Sale (sayarwa). This is an outright transfer of land for cash.
However it is only the usufructuary rights to the land that are
being sold and not the land itself. Although there are variations
in the procedure from area to area, there must usually be two
witnesses present and the village head has to be informed.
4. Fledge (jingina). The right to use the land is passed to another
individual in return for a money loan In such cases the amount
paid is usually less than the land's value, no term is stated and
the creditor will farm it until the loan is repaid.
5. Loan (aro). The land is usually farmed on a year to year basis
by another individual, although sometimes the agreement may
be for a period of two or three years. Usually a small rental is
paid at the time of harvest in either cash or kind.

6. Government. This type of transaction was found only in Hanwa
and can be considered as a variant of the loan type of tenure
except that no rental is paid. The Government land situated in
the southeastern corner of the village area was sold by Emir
Aliyu (1903-20) to the Government. Farmers are allowed to use
the land as long as the Government does not require it for build-
ing or for other purposes. The Government reserves the right
to take possession of the land at any time. If this happens
during the growing season, money equal to the value of the crops
is given as compensation.
Luning (7, p. 82) states that in the case of loan and pledging the tem-
porary cultivator will not be inclined to manure the field. If he did,
Luning notes it would imply that he is establishing a claim on the
land and the owner will refuse to continue the contract for another
year. This fact together with the lack of security of tenure in the
case of loan and pledging means that capital investment in land imp-
rovements in such cases will be virtually nothing. From the point
of view of security of tenure the most secure is probably inherited
land followed by gift, sale, pledge, loan and government land.

Tenure patterns in the survey villages
Before turning to a consideration of the tenure patterns in the survey
villages, the following reservations about the type of tenure as shown
in Tables 14A, 14B. and 14C should be noted:

1. In practice the only gift land that was disclosed as such was that
allocated by the village head. It is thought that land given by
previous holders to close relatives was disclosed as inherited
land.
2. Some confusion appeared to exist between purchased and pledged
land. Several instances were reported in Hanwa in which land
had supposedly been purchased, but where the original owner
1. This information was obtained by the geographer and the rural
sociologist in a discussion with the village head.









had returned and asked for more money. Such situations are
more likely to arise where there are no written agreements.
Therefore most farmers preferred to consider the land being
pledged to them rather than having been purchased by them.

Fearing these reservations in mind one obvious fact arising from
Tables 14A, 14E and 14C is the importance of inherited land in Doka
and Dan Mahawayi compared with Hanwa. Luning (7, p. 80) also
found in Katsina Province the same relationship that in the more rural
locations, which are areas of lower population densities, there was
a concomittant rise in the percentage of land inherited. Location
and the past history of the three survey villages seem to have had a
profound effect on the types of tenure found at the present time. The
following comments on each of the villages help to illustrate this
point.
1. Hanwa

Although the percentage of the fields in Hanwa that are inherited
is low (i.e., 32 per cent), it is also interesting to note from Table
14A that about 65 per cent of all the fields within about a quarter
of a mile from the village are farmed by families who inheiited
them. In actual fact about 60 per cent of all the fields which
are inherited are located in this area. The implication of this
relationship that there appears to be a recognition on the part of
farmers of the desirability of farming land situated close to the
village thereby obviating the necessity for much walking supports
observations made earlier in the report.
At greater distances from the central village and unguwa of
Hanwa other types of tenure are more common implying that
farmers are willing to give other families or gandaye the right
to farm their land. By far the most common type of tenure in
Hanwa was in fact found to be loaned land, which accounted for
about 67 per cent of the fields located half a mile or more from
the village. The high proportion of loaned land in Hanwa com-
pared with Doka and Dan Mahawayi can be attributed to its
location. Firstly, the high population density has no doubt con-
tributed to the high frequency of land transfers. Secondly, the
nearness of Hanwa to Zaria has resulted in city residents owning
usufructuary rights over sizable tracts of land in the village area.
This situation arose during the time when slaves belonging to
wealthy individuals in the city were sent to cultivate their land
outside the city. With the end of slavery these landowners have
adopted the practice of renting their land to farmers resident in
the village.
Purchased, pledged and Government land were four to be un-
important in Hanwa where no examples of gift land were found.
This is understandable in view of the high population density in
the area.
One small point to note from Table 14A is that, while only 27
per cent of the gona land is inherited, over 53 per cent of the
fadama land is inherited. One possible implication of this is
that farmers value fadama land, which is very limited in area,


1. See page 18.









Table 14A. Land tenure pattern of fields farmed by gandaye.
Hanwa, 1966


Inherited Gift Sale Pledge Loan Gov. Others Total

Acres:

Totala 127.58 15.58 53.78 214.60 41.53 4.37 457.44
Gona 108.68 15.58 49.17 195.59 34.25 4.37 407.64
Fadama 16.25 2.38 9.87 1.79 30.29
Average field size 1.23 1.95 185 1.51 1.01 4.37

Percentage of:

Total No. of fields 32.00 2.46 8.92 43.70 12.61 0.31 100.00
Total acres 28.26 3.40 11.76 47.28 9.08 0.22 100.00
Gona acres 27.08 3.82 12.06 48.40 8.40 0.24 100.00
Fadama acres 53.65 7.86 32.58 5.91 100.00

Number of fields in
each distance fact-
or according to
type of tenure:
2 34 2 6 42
3 28 5 18 3 54
4 10 1 3 19 4 37
5 5 1 5 14 10 35
6 8 1 11 7 27
7 4 3 15 10 32
8 5 5 7 3 1 21
9 2 1 1 7 2 13
10 2 2 3 7
11 2 1 1 7 1 12
12 2 -- 4 6
13 1 2 3 9 1 16
14 9 9
15 3 3
16-17 1 10 11

Total 104 8 29 142 41 1 325

aThe sum of gona and fadama acreages do not necessarily equal the total
acreage because of the omission of fields that are partly gona and partly
fadama









Table 14B. Land tenure pattern of fields farmed by a sample of
gandaye. Doka, 1966


Acres:

Totala
Gona
Fadama

Average field size
Percentage of:

Total 'yo. of fields
Total acres
Gona acres
Fadama acres

Number of fields in
each distance factor
according to type of
tenure:
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16-24


Inherited Gift Sale Pledge Loan Gov. Other Total


338.94
260.84
39.44

1.47


83.39
78.26
75.66
85.83





34
29
38
35
28
24
23
11
2
1
1
1
3

1


58.56
54.96
3.60

3.08


6.86
13.52
15.94
7.83





1
2
2
3
2
3
2

1

2

1
-


3.12
2.40


0.78


1.44
0.72
0.70


0.60
0.60


0.60


0.36
0.15
0.17













1


16.04
14.76
1.28

1.00


5.78
3.70
4.28
2.79





1
2
2
4
3
1


1
2


15.82
11.21
1.63

2.65


2.17
3.65
3.25
3.55





1
1

1
1

1

1


433.08
344.77
45.95



100.00
100.00
100.00
100.00





39
34
42
44
34
28
27
11
5
3
3
1
4

2.


Total 231 19 4 1 16 6 277

a See footnote at the bottom of Table 14A.









Table 14C.


Land tenure pattern of fields farmed by a sample of
gandaye. Dan Mahawayi, 1966


Inherited Gift Sale Pledge Loan Gov. Others Total


Acres:

Totala
Gona
Fadama
Average field size

Percentage of:
Total No. of fields
Total acres
Gona acres
Fadama acres

Number of fields in
each distance factor
according to type of
tenure:
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16-25


286.54
223.79
21.97
1.88


52.96
57.27
54.77
54.57





37
12
19
22
12
8
15
10
2
2
2
2

2
7


98.52
83.04
10.26
1.82


18.81
19.69
20.32
25.48





7
2
10
7
3
8
8

2
3
3


1


30.94
24.45
6.49
0.97


11.15
6.18
5.98
16.12





4
2
6
7
5
3
1
2
2
-


22.87
21.73

1.20


6.62
4.57
5.32






4
1
3
3
5
1


2


37.34
35.80
1.54
1.62


8.01
7.46
8.76
3.83


24.15
19.77

3.45


2.45
4.83
4.85


500.36
408.58
40.26




100.00
100.00
100.00
100.00





52
21
41
41
28
27
27
14
8
9
6
2
1
3
7


Total 152 54 32 19 23 7 287

aSee footnote at the bottom of Table 14A.









somewhat higher than gona land and therefore are more keen
to retain their inherited usufructuary rights.
2. Doka
Compared with Hanwa, by far the most common type of tenure
in Doka is inherited land. Apart from gift land other types of
tenure were found to be insignificant. About 87 per cent of the
gift land was in fact found in the unguwa which was settled more
recently than the central village.

3. Dan Mahawayi
Once again in Dan Mahawayi inherited and gift land are the most
important types of tenure. The significance of the gift land can
be accounted for by looking at the historical development of the
village. As was noted earlier in the report1, there was at one
time in the development of the village an emigration of residents.
The farms which were abandoned as a result were reallocated.
In all three villages the remuneration for loaned land showed no par-
ticular correlation with size, type or location of the field. The
same was observed for purchased and pledged land. The rental for
land held on loan is sometimes paid in cash and sometimes in kind,
e.g., one bundle of guineacorn and one bundle of millet. Sometimes
no rental is paid.
The predominance of land being farmed by the gandu that inherited it
has implications concerning ease of acquiring usufructuary rights or
land mobility and the feasibility of a land reform programme. In
such cases it seems likely that land is not readily transferred from
one gandu to another. Under such circumstances there has been no
preconditioning for the adoption of a voluntary land reform pro-
gramme. However, in the case of Hanwa, and probably of other
villages situated close to urban areas, there is a considerable
amount of land that changes hands from year to year, e.g., land held
on loan and pledge. The resulting concept of land mobility may well
be an impirant factor in bringing about a favourable attitude on the
part of farmers to a land reform and perhaps a land consolidation
programme.




















1. See page 6.









IV. LAND AND LABOUR RELATIONSHIPS


Consideration in this chapter is devoted to an investigation of the
relationship of labour and land. The two main subjects to be con-
sidered are the land-labour ratios and the principal factors import-
ant in determining the size of holding farmed by a gandu.
LAND-LAB OUR RATIOS
As was indicated earlier in the report it is important in an economic
sense to differentiate between the residents of the family and those
who potentially, at least, can contribute to the earning capacity of
the family. Labour units (LU. 1) were calculated in an attempt to
measure the total potential. However, because adult women are
generally confined to the compound, it is necessary to modify this
measure into a form that reflects labour units available for work
outside the compound (LU. 2). Consequently the labour unit equivalents
used in constructing this measure were exactly the same as those
used in calculating the total labour units (LU. 1) except that the women
between the ages of 15 and 64 were valued at zero. Thus the weights
assigned were as follows:

Age Sex Labour unit
(years) equivalent
Less than 6 Male and female 0.00
7 14 Male and female 0.50
15 64 Male 1.00
15 64 Female 0.00
65 or more Male and female 0.50
It is appreciated that these are arbitrary weights and there may be
exceptions. For example, some women between the ages of 15 and
64 do work outside the compound and occasionally help in the fields
at peak labour periods, e.g., planting, and in harvesting and cotton
picking. However, preliminary results from the input-output study
indicate that this is an exception rather than the rule.
In Hanwa, unlike the other two villages, there is an additional com-
plication in that there are off-farm employment opportunities in
Zaria and also the ownership of cattle, the supervision of which
decreases even further the amount of labour actually available for
work on the farm. Therefore a second modification was introduced
in constructing a measure designed to signify labour units available
for work on the farm (LU. 3). This measure was calculated by sub-
tracting from the labour units available for work outside the com-
pound (LU. 2) the sum of the labour units working ;f:.'the farm which
were calculated using the following labour unit equivalents:
Age Sex Type of job and labour unit equivalents
Regular non-farm Looking after
employment cattle
7-14 Male and female 0.25
15-64 Male 1.00 0.50
It is recognized that many residents in the three villages have sub-
sidiary occupations (Table 6). However, these are such that they
are usually pursued during periods when farming operations are less
time consuming.
1. See page 7.









Thus they are pursued at slack periods in the farming year whereas
regular off-farm employment and tending cattle compete directly with
time that could otherwise be spent on farming activities and have to
be carried on no matter how busy the farming season is. In addition
this problem of part time farmers may be further accentuated in a
hand labour economy where a class of hired, land-less, farm labourers
has not yet evolved.
Since there are no cattle owners or regular off-farm employment
opportunities in Doka and Dan Mahawayi, the number of labour units
available for work outside the compound (LU. 2) and on the farm
(LU. 3) are identical.
The results in Table 15 once again reflect the differences in popula-
tion densities in the three areas. The differences in the ratio of total
land per resident and the labour unit measures between the three
villages are accentuated because of the presence of significant amounts
of fallow land in Doka and Dan Mahawayi. When the ratios are
expressed in terms of the land cultivated in 1966, the range between
the three villages is substantially reduced.
The various ratios in Table 15 imply that the system of agriculture in
Dan Mahawayi may be somewhat more extensive than in Hanwa and
probably Doka.
Table 15. Acresa and cultivated acres per resident, per labour unit
available for work outside the compound (LU. 2) and per
labour unit available for farm work (LU. 3) for a sample
of gandaye in the survey villages, 1966

Hanwa Doka Dan Mahawayi
Total acres per:
Resident 0.66 1.24 1.75
LU. 2 1.85 3.64 5.53
LU. 3 3.07 3.64 5.53
Cultivated acres per:
Resident 0.65 0.90 1.43
LU. 2 1.82 2.64 4.48
LU. 3 3.00 2.64 4.48
aThis excludes bush land over which no gandaye hold the rights of
production.

DETERMINANTS OF SIZE OF HOLDING

Multiple regression analysis was used in an attempt to identify quanti-
tatively what factors are.important in determining the size of holding
farmed by a gandu in 1966.
Model specification

The dependent variable (Y) was the size of holding expressed in
acreage terms.

The independent variables used and the measures designed to reflect
them were as follows:
1. Size of family (X1). Luning (7, p. 51) and others have considered
the size of family important in determining the size of holding. A
positive relationship can be expected to exist between X1 and Y.










2. Number of family labour units available for farming (X2). In a
hand labour economy in which a class of farm labourers has not
yet evolved, the size of holding that can be adequately cultivated
will be limited by the number of labour units in the family that
are available for farm work. The details on calculating this
measure (LU. 3) are described on an earlier page. A positive
relationship can be expected to exist between X2 and Y.

3. Fragmentation index (X3). It is hypothesised that a large size
of holding can only be achieved as a result of having a large
number of fields that are widely dispersed. Such a characteristic
may place an effective limit on the size of holding that can be
handled by one family.- Details on the calculation of the frag-
mentation index are given in Appendix A. A positive relationship
can be expected to exist between X3 and Y.
4. Soil fertility index (X ). It is believed that the fertility of the
land as viewed by the farmers may be important in determining
the size of holding. Farmers differentiated three types of soil
in the survey villages. These were:

a. Eakar kasa, i.e., black and rich soil.
b. Farar kasa, i.e., whitish but less fertile soil.
c. Jar kasa, i.e., red and least fertile soil.
X is the index designed to reflect the average fertility level of the
holding. This soil classification may not correspond with a scientific
classification of soil fertility. However, this does not negate the
value of the classification used here since it was the farmer's notion
concerning the fertility level that is being tested as a possible deter-
minant of the size of holding. X. was calculated as follows:

3
A.. C.
=1 1J 1
X4j -= 3 i
2 A..
i=l
where:
X4j = soil fertility index of holding j.

C. = soil fertility class i where i = 1,2,3, (i.e., where
bakar kasa = 1, farar kasa = 2 and jar kasa = 3).

A.. = number of acres of soil fertility class i in holding j.

A high value for the index would indicate a low general fertility level
for the holding. A positive relationship is expected to exist between
X and Y, the hypothesis being that a low average fertility level will
be compensated by a large holding.

Another measure of land quality, i.e., the percentage of the acreage
farmed by the household that is gona, was also tested in the initial
stages, but was rejected because of problems of multicollinearity.
Fadama land consists mainly of black soil, while gona land is mostly
made up of both red and white soils. Consequently the soil fertility
index was considered a more sensitive measure of land quality.

5. Land immobility index (X5). The ease or difficulty of acquiring
more land may contribute to determining the size of holding. An









attempt to measure the degree of mobility was made by means of
a proxy variable. As mentioned earlier in the report different
types of tenure have varying degrees of security as far as
usufructuary rights are concerned. 1 In the construction of this
index it was assumed that the ease of acquiring more land bears
an inverse relationship with the security of tenure. For example,
land that is inherited is the most secure type of tenure as far as
the farmer is concerned, but such land does not change hands
readily. At the other extreme land that is held on loan is the
least secure from the point of the cultivator, but is very mobile
in the sense that it can be transferred readily to another culti-
vator. The index was calculated as follows:
3
2 B.. D.
i=l 1]J 1
5j 3

i=l
where:
X5j = land immobility index of holding j.
D. = land mobility class i where i = 1,2,3, (i.e., govern-
1 ment and loaned land = 1, purchased and pledged
land = 2, and inherited and gift land = 3).
B.. = number of acres of land mobility class i land in
S holding j.

A significant positive relationship between X5 and Y would imply that
it is difficult to acquire more land. In effect the only possible way
to have a large size of holding is to have been fortunate enough to
have had a large proportion which was received as a gift or was in-
herited. Non significance of the variable would imply that additional
land is easy to acquire, and therefore land immobility is not a res-
trictive influence on the size of holding.
In some preliminary work on Hanwa (16, p. 110) another variable,
percentage of land that was inherited, was used to reflect land immo-
bility.
6. Acres of fallow land (X ). The inclusion of this variable is
necessary since not all the land of holding is necessarily culti-
vated every year. Ceteris paribus the amount of fallow land
will show a positive correlation with the size of holding.

Since family size (X1) and number of labour units available for farm
work (X ) are likely to show a high degree of inter correlation, two
equations were estimated as follows:
Equation 1:
Y. =b +b X + b X +b X + bX +b X. +U.
S o 1 i 3 i3 4 i4 5 i5 6 16
Equation 2:
Y. = b + b X + b X + b X +b X +b X. +U
1 o 2 i2 3 i3 4 i4 5 i5 6 16
Because of the negligible amount of fallow land in Hanwa3, X6 was
omitted from the estimating equations.
1. See page 26.
2. Latin expression.
3. See Table 8.









A summary of the hypothesised signs on the variables included in the
empirical analysis is given in Table 16.
Table 16. Hypothesised signs on the determinants of size of holding
equations

Variable Equation 1. Equation 2.

X1 +
X1
X2 +
X3 + +
X4 + +
4
X5 + +
x6 + +
X6

Results of empirical analysis
The results of the multiple regression estimating equations for the
three villages are presented in Table 17.
The results in all three villages for Equation 1 give quantitative
support to observations by many writers, e.g., Luning (7, p. 51)
that the number of family members (X ) is important in determining
the size of the holding. Apart from Doka the results of Equation 2
also show that the number of labour units in the family available for
farm work (X ) is very significant in determining the size of holding. 1
As noted earlier in this study the significance of family size and
labour units available for farming is to be expected in a hand labour
economy where a class of hired, land-less farm labourers has not
yet evolved.
The size of a family therefore imposes definite limitations on the
area of land that can be cultivated in any one year. Assuming
ceteris paribus conditions the proportion of fallow land will increase
with an increase in the size of holding. Admittedly large farmers
use a certain amount of hired labour, but not an amount sufficient to
upset this relationship. Hired labourers are usually farmers in
their own right. Unfortunately the periods when they are most in
demand coincide with the labour peaks in the farming operations on
their own farms. Thus the amount of land that can be satisfactorily
managed by family members during the peak labour periods effectively
limits the size of cultivated area. 2 This observation is supported
by the fact that in both Dan Mahawayi and Doka the number of acres
of fallow land (X6) increased significantly with an increase in the
size of holding. This variable, as mentioned earlier, was excluded
from the Hanwa equations, since population pressure has decreased
the amount of fallow land to almost nothing.
1. The unsatisfactory result for Doka may be due to problems of
multicollinearity. However, since all the computations were
carried out on a desk calculator, time precluded a more detailed
investigation.
2. This assumes that farmers with large holdings would cultivate
more land if they could, i.e., they would be prepared to earn in-
comes greater than the amount necessary for subsistence.


(continued on page 38)








Table 17A. Determinants of the size of holding equations. Hanwa, 1966


Equation 1. Equation 2.

Variable Partial regression Standard t-value Beta Variable Partial regression Standard t-value Beta
coefficient error coefficient coefficient error coefficient

Constant -4.0592 Constant -1.3333
X1 0.4298 0.0872 4.9289* 0.4642 X2 1.4110 0.3900 3.6179* 0.4579
X3 0.1117 0.0268 4.1679* 0.4668 X3 0.1172 0.0306 3.8300* 0.4898
X4 0.2159 1.4750 0.1464 0.0165 X4 -0.4758 1.7890 -0.2660 -0.0364
X5 0.1837 0.7930 0.2316 0.0252 X5 -0.1120 0.9155 -0.1223 -0.0154

R = 0.7887* R = 0.7118*
R2 0.6220 R2 = 0.5066
Syx = 0.4728 Syx = 0.5402


Significantly different from zero at the 5 per cent level. Sample size = 38.










'I'able 17P. Determinants of the size of holding equations. Doka, 1CGG


Equation 1. Equation 2.

Variable Partial regression Standard t-value Peta Variable Partial regression Standard t-value Peta
coefficient error coefficient coefficient error coefficient

Constant 4.2511 Constant 0.5879
X1 0.5690 0.1728 3.2928* 0.4311 X2 0.1236 0.1302 0.9493 0.0792
X3 0.0198 0.0271 0.7296 0.0729 X3 0.0573 0.0298 1.9192* 0.2110
X4 -0.8230 1.4920 -0.5516 -0.0524 X4 0.5390 1.6840 0.3201 0.0343
X5 -0.1200 2.5760 -0.4658 -0.0043 X5 0.3420 3.0080 0.1137 0.0122
X6 0.9521 0.2400 3.9671* 0.5497 X6 1.3190 0.1824 7.2313* 0.7616
6 6

R = 0.8412* R = 0.7752*
2 2
R = 0.7077 R = 0.6009
S = 0.5583 S = 0.6524
yx yx

Significantly different from zero at the 5 per cent level. Sample size = 44.








Table 17C. Determinants of the size of holding equations. Dan Mahawayi, 1966


;_Equation 1 Equation 2
Variable Partial regression Standard t-value Beta Variable Partial regression Standard t-value Beta
coefficient error coefficients coefficient error coefficients
Constant -10.3064 Constant -12.3271

X1 1.4667 0.3664 4.0030* 0.5576 X2 4.2920 1.2080 3.5553* 0.5155
X3 0.0150 0.0680 0.2206 0.0369 X3 0.0261 0.0694 0.3760 0.0643
X4 2.6470 3.5700 0.7414 0.0916 X4 0.9960 3.6590 0.2722 0.0345
X5 1.5240 3.4720 0.4389 0.0646 X5 3.4600 3.4540 1.0017 0.1467
X6 1.3001 0.4178 3.1118* 0.3731 X6 1.1210 0.4357 2.7771* 0.3234

R = 0.7584" R = 0.7358*
R2 0.5751 R2 = 0.5414

S = 1.2460 S = 1.2950
SSignificantlyyx d f z a t 5 p yx=
* Significantly different from zero at the 5 per cent level. Sample size = 42.









The results for Hanwa and Equation 2 for Dokal indicate that a
larger size of holding can be achieved only by an increase in the frag-
mentation index (X ). This is not surprising in view of the evidence
in Tables 12A and I2E that larger fields are to be found only at some
distance from the village. Of necessity the time devoted to super-
vision increases with an increase in the size of business or farm.
However, in such cases where fields are widely dispersed the super-
vision necessary is further increased. This ultimately could place a
limit on the feasible size of holding.
In both equations in all three villages the land fertility index (X ) and
the land immobility index (X5) were found to be not significant. In
Equation 2 of Hanwa and Equation 1 of Doka the signs on the partial
regression coefficients were contrary to those hypothesised. How-
ever, owing to the non-significance of these variables this was not
considered to be a serious limitation.

The non-significance of the fertility index implies that the average
fertility of the land is not important in determining the size of holding.
The non-significance of the land immobility index indicates that it is
not difficult to acquire more land in order to enlarge the size of hold-
ing. In other words a family can still have a large size of holding
even if a significant proportion has not been inherited nor been received
as a gift. However, a note of caution should be given concerning the
results for this variable. One of the problems of a proxy variable
such as this is that one can never be certain that it is reflecting the
characteristic that one is attempting to measure. From information
given earlier in the study (Table 14) one would expect it would be
easier to acquire more land in Hanwa than in Dan Mahawayi. This
is supported by the fact that in both equations the beta coefficient
values for this variable are greater in Dan Mahawayi than in Hanwa.






















One indirect result of this limit of labour availability is the pro-
bability of the level of fertility being maintained on large holdings
through fallowing rather than through the addition of fertilizer.
1. For reasons noted in the footnote on page 34 this result should
be treated with caution.









V. SUMMARY

The section of the economic study discussed in this report was con-
cerned with a quantitative description of the demographic, natural
resource and land-labour relationships in the three survey villages
situated in the northern part of Zaria Province. The villages which
were selected differed in ease of communication with Zaria, with its
large market for factors of production and agricultural products.
Hanwa was selected as a village in close proximity to Zaria, while
Dan Mahawayi is inaccessible to motor transport during the rainy
season. Doka falls between these two extremes. Complete enume-
ration of sections of the survey villages was carried out to obtain
details on demographic characteristics and to construct farm maps
from aerial photographs.
Many of the differences found between the survey villages can be
explained on the basis of their location. Location is an important
factor in determining the population density. Table 1 indicates that
the districts in which the villages are located show a marked decrease
in population density as physical communication with Zaria becomes
more difficult. 1
The main results arising from the demographic analysis were the
skewed age distribution with over 50 per cent of the population less
than 20 years old and the tendency for the male-female ratio to be
lowest in the 20 to 39 age range. The latter is related to the poly-
gamous nature of marriages, while the preponderance of persons in
the younger age groups means that a larger area of land can be culti-
vated than if the age distribution was more equitable.
There was an average of about seven residents per family or gandu
while the ratio of total residents to productive labour (LU. 1) was very
similar for the three villages.
The location of the villages was found to be important in contributing
to differences in the following relationships:
1. The differences which result in the average size of holding both
between and within sections of the villages. The amount of
fallow land shows an inverse relationship with the population
density, while another factor accounting for the difference is
the differing regular off-farm employment opportunities.
Both population density and availability of off-farm employment
opportunities are influenced by the location of the villages.
2. The tenure patterns are influenced by the location and historical
development of the villages. Under ceteris paribus conditions
more "traditional" types of tenure, e.g., inherited land, tend to
be dominant the more remote the village is from an urban area.
3. The values of the various ratios designed to measure the relation-
ship of land to labour i.e., land-resident and land-labour unit
ratios showed a tendency to rise with an increase in the remote-
ness of the village from Zaria.
1. Data on the number of persons per square mile are not available
at the village level. However, the number of persons per square
mile of land farmed or fallow in 1966 show the same trend, i.e.,
1,011.54 in Hanwa, 493.48 in Doka and 408.19 in Dan Mahawayi.








Other conculsions arising from the.location of farms and fields with-
in a village area rather than from the location of the village itself
-are : . ,;.. .
1. There -is'a colsiderable ihiqulity :i' thI i st i i but io 6ibf'the liand
between the garidaye or families ithin-the 'v-ilagel, ie.; 50 per cent
of the gandaye hold" 18 'to6I5 per ch.f &fth ot'al farm land '
2. The:fragmentation, index.increaes with; a, increase i n.the size
of holding although in the case of the.ungwoyi the. average frag-
mentation index value is lower, than;that, lorthe central, villages.
This characteristic, implies that, by, living in an unguw.a time can
be saved in walking to, between and froqn, .fields, farmed by the
fam ily. .. .. ... .. .
3. The average size of gona fields tend to ihcnreae""with'increa'e
in their distance from.the place..of residence. Unlike the central
villages this relationships not so apparent i, the .ungwoyi.
4. MIore "traditional" types of t nriire' eg.'i inherited-land; are
dominant naart-he places! of residence, 'Ahil efiebds 'held 'inder
types of tenure in' vhich :suf rut i y 'right's are frequently trans-
ferable, e.g., loaned and pledged land, are found further away
from-the village. .. -,
The equations estimated~ in ah atteimp t I asertaint te more important
determinants of the size of'holding-;, 'gav 'eiipi*rical' support to the
notion that family size and the: :number: of lab'ur 'nit i'the gandu
are most important'in deciding tfli -aea that' xi'fl'be cultivated. This
is to be expected in. a'predomiriaritly- 1IaId' labi6Uir'ec 6oomiy wihere'a
class of landless -farii :lab'oure rs'has: 'not' y;dtevolved&` Alsb related
to this limitation on the size. of holding, ;and in,ayrea ,,sof a low popula-
-tion density the number of, acres ,of fallow-land.wasfopund to increase
significantly with an increase in the size of; holding,
The purpose; of this report .in providing background; material, for the
section of the study devoted to.the, input-out put investigationhas
resulted in its being positively rather than normatively orientated.
Finally, there does appearto be' 'fi kted' dffrePnces between
villages when considered ini terfs' df'theiri6ldcatibn with respect to
an urban area, th'erefore ijustifyiing-"te mai'nicri ion:adOted in
their selection.









BIBLIOGRAPHY


1.. Bryant, W. K. An Analysis of Inter-community Income
Differentials in Agriculture in the United States.
Ph.D. thesis. Lansing, Michigan State University,
1962. 321 numb. leaves. (Microfilm).
2. Clayton, E. S. Agrarian Development in Peasant Economies.
London, Pergamon Press, 1964. 154 pp.
3. Ezekiel, M. and Fox, K. A. Methods of Correlation and
Regression Analysis. New York, Wiley, 1959. 548 pp.
4. Federal Office of Statistics. Agricultural sample survey,
1955-1960. Bulletin 2 (Revised), Zone P, 1956/57.
Lagos, Nigeria. 7 pp. (Mimeographed).
5. Federal Office of Statistics. Agricultural sample survey,
Northern Region. Bulletin 3, 1957-1958. Lagos, Nigeria.
15 pp. (Mimeographed).
6. Federal Office of Statistics. Nigerian rural economic survey.
Farm survey 1963/1964. Lagos, Nigeria. 20 pp.
(Mimeographed).
7. Luning, H. A. An Agro-economic Survey of Katsina Province.
Kaduna, Government Printer, 1963. 154 pp.
8. Luning, H. A. The impact of socio-economic factors on the
land tenure pattern in Northern Nigeria. Journal of
Local Administration Overseas, 41 (1965), pp. 173-182.
9. Ministry of Economic Planning, Northern Nigeria. Statistical
Yearbook, 1964. Kaduna, Government Printer, 1965.
188 pp.
10. Ministry of Economic Planning, Northern Nigeria. Statistical
Yearbook, 1965. Kaduna, Government Printer, 1965.
247 pp.
11. Mortimore, M. J. and Wilson, J. Land and people in the
Kano close-settled zone. Report to the Greater Kano
Planning Authority. Zaria, Ahmadu Bello University,
March, 1965. 119 pp. (Department of Geography
Occasional Paper No. 1).
12. Newman, P.C., Gayer, A.D., and Spencer, M.H. Source
Readings in Economic Thought. New York, V.W. Norton,
1954. 762 pp.

13. Nicholls, W. H. Industrialization, factor market and agricul-
tural development. Journal of Political Economy, 49
(1957 ?), pp. 319-40.
14. Nigeria Federal Census Board. Administrative Population of
Northern Nigeria, 1963. Lagos Federal Census Office,
1965. 258 pp.

15. Norman, D. W. Natural Resource Characteristics as Related
to the Pattern of Agricultural Income in Certain Specified
Areas of the United States. Ph.D. thesis. Corvallis,
Oregon State University, 1966. 174 numb. leaves.









16. Norman, D. W. Preliminary observations on demographic,
size of holding and mode of tenure relationships in Hanwa
village, Zaria Province. Bulletin of Rural Economics and
Sociology, 2 (1967), pp. 99-113.
17. Northern Nigeria Survey. District Map of Zaria Province,
scale 1:1,000,000. Kaduna, Northern Nigeria Survey.
1965.
18. Regional Census Office, Kaduna. Population Census of the
Northern Region of Nigeria, 1952. Bulletin Nos. 1-13.
Lagos, Census Superintendent. March 1964.
19. Rowling. Report on Land Tenure, Kano Province. Kaduna,
Government Printer. 1949.
20. Schultz, T. W. A framework for land economics the long
view. Journal of Farm Economics, 33 (1951), pp. 204-15.
21. Schultz, T. W. The Economic Organization of Agriculture.
New York, Mc-Graw Hill, 1953. 374 pp.
22. Smith, M. G. The economy of Hausa communities of Zaria.
A Report to the Colonial Social Science Research Council.
H.M.S.O., 1955. 264 pp.







FgureAL
Location of fields farmed by gondu 25(1
in Doko vl//oge /966.


Scee / inch = (SO0 feet I
/.2, -- 6 = Segment numbers
--- = Diosne numbers -- re omit ed due
to lock o room.
Area o = orea b =........= oreo h = sections each 20ocres in size.
= field number S30










Table Al. Computation of fragmentation index for gandu 25 (1) in
Doka, 1966

Field or Section Segment number
serial number Location of Distance
number field between fields
259 1.5 15.5 1.0
246 1.5 16/1 0.0
270 1.0 16/1 1.0
273 1.0 1.5 4.5
530 3.0 6.0 9.5

Number of fields = 5
S, 25(), DOKA= 8.0 5 = 1.60
A, 25(1), DOKA
DA, 25(1), DOKA 6.5 5 1.30
For Doka (100 S) 6.25 omTable
For five fields (100 -- D ) = 41.67 ) A2

F25(1), DOKA = (1.80)(6.25) + (1.30)(41.67)
= 65.42

In the case of the example in Table Al the actual corrected disper-
sion factor is 1.30.
d. Potential corrected dispersion factor (D ). The factor is
calculated on the basis of the maximum possible dispersion of the
fields. For example the maximum possible dispersion of a holding
of five fields is to have them located in segments 3, 6, 9, 13 and 16.
The potential corrected dispersion factor in this case is thus 2.6 units.
The size of the potential corrected dispersion factor varies according
to the number of fields in the holding and is independent of the village.
The factors delineated above are combined in the following for-
mula to give the fragmentation index.
100S .. 100D
Aij c Aij
F.. = + i
ij S
Pj D P

where:
F.. = Fragmentation index of holding i in village j.

SA = Actual corrected spatial factor of holding i in village j.
Aij
S = Potential corrected spatial factor of village j.
D j= Actual corrected dispersion factor of holding i in village
Aij
D, = Potential corrected dispersion factor.


1. The numbers of the segments are actually immaterial, since the
same value would be obtained if the fields were located in
segments 1, 4, 7, 10 and 14.










To facilitate the calculation of large numbers of fragmentation
indices the constants in Table A2 were used in the survey villages.

Table A2. Constants used in calculating fragmentation indices in
the survey villages, 1966

Number of 100 S
Pj
fields in 100 D
ld in Hanwa Doka and F
holding i
Dan Mahawayi
_n = 13 n = 16


a The corrected dispersion factor, both actual and potential,
is irrelevant when there is only one field in the holding.

The limits of the fragmentation index are (100 S .) and 200.
A value near a value of (100 -+ S P) would imply that al the fields
farmed by the gandu are close together and also near the residence
cluster. Conversely a very high value would imply that the fields
farmed by the gandu are widely scattered both from each other and
from the place of residence.

The fragmentation index as described above can perhaps be
criticised on several counts. For example the size of section of 20
acres was arbitrarily chosen and could be reduced although this
would greatly increase the computational burden. Another criticism
that can be advanced is that no account has been taken of the size of
field. The emphasis in this study was to derive a measure that was
relatively simple and could be carried out without the aid of a com-
putor. It is hoped that from future studies will evolve a more
refined method for measuring the degree of fragmentation of a
holding.


7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69
7.69


25.00
30.00
33.33
41.67
46.15
53.85
57.14
64.29
71.43
78.57
85.71
92.86
100.00
107.15
106.67
113.34
120.00
126.66
133.33
140.00
146.67
153.33
160.00


6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25
6.25









NOTES ON APPENDICES B,. C AND D.
In Appendices B, C and D are presented basic data on the demo-
graphic characteristics of each gandu and details on each field to be
found on Maps 1A and 1B, 2A and 2B, and 3.

More explicitly the details in Table B2 refer to fields listed on
Maps 1A and 1B, those in Table C2 refer to Maps 2A and 2B, and
those in Table D2 refer to Map 3.
The following key delineates the data included in the columns
presented in Tables B1, B2, C1, C2, D2 and D1:
Column (1). Compound number with gandu number in cases where
there is more than one gandu in the compound.
Column (2). Master sample number.
Column (3). Family or gandu size.
Column (4). Total number of labour units in the family (LU. 1).
Column (5). Number of labour units available for work outside the
compound (LU. 2).
Column (6). Number of labour units available for farm work (LU. 3).
Column (7). Field or serial number.
Column (8). Name of the person farming the field expressed in terms
of his/her relationship to the head of the gandu or family. A number
following the letter indicates that more than one person of that
relationship in the gandu has a field. The numbers are assigned in
order of age, e.g., the elder son is denoted by S1 and the younger
son by S2.

H = gandu head.
B = brother.

C = cousin.
S = son.
D = daughter.
SL = son in law.
DL = daughter in law.
N = nephew.
F = friend or servant.
Column (9). Size of the field in acres.

Column (10). Location of the field where:

a = distance of the field from the central village. Each
unit equals 150 yards.
b = Octrant number. Numbering is carried out clock-
wise starting at the segment to the upper right of a
vertical line on each map.
It should be noted that these numbers refer to the location of fields
relative to the central village and not the place of residence which
was the case in the analytical sections of the report.









Column (11). The characteristics of every field in Hanwa and each
field in the master samples of Doka and Dan Mahawayi. The first
letter (A to C) refers to the field type, the second (D to J) to the soil
type and the third (K to W) to the type of tenure where:

A = Gona.
B = Fadama.
C = Combination of gona and fadama.
D = Bakar kasa.
E = Farar kasa.
F = Jar kasa.
G = Combination of bakar and farar kasa.
H = Combination of bakar and jar kasa.
I = Mixture of bakar, farar and jar kasa.
J = Combination of farar and jar kasa.
K = Inherited.
L = Gift.
M = Sale.
N = Pledged.
0 = Loaned.
P = Government.
Q = Partly inherit'd and partly gift.
R = Partly inherited and partly loaned.
S = Partly acquired by sale and partly gift.
T = Partly acquired by pledge and partly gift.
U = Partly held on loan and partly as gift.
V = Partly inherited and partly on pledge.
W = Partly acquired by sale and partly inherited.








APPENDIX E


DAN MAHAWAYI
In the following tables gandu numbers 1(1) to 81 inclusive are located
in the central village and 82 to 89 are situated in the unguwa.
Table Fl. Number of residents and labour units according to gandu.
Dan Mahawayi, June, 1966

(1) (2) (3) (4) (5) (6) (1) (2) (3) (4) (5) (6)
1(1) 1 21 12.25 7.0 7.0 38(1) 9 4.25 2.0 2.0
1(2) 8 13 6.75 4.5 4.5 38(2) 2 1.50 1.5 1.5
1(3) 2 1.75 1.0 1.0 38(3) 26 4 2.25 1.5 1.5
2 25 14 7.50 4.5 4.5 39 4 2.75 2.0 2.0
3 3 3 1.75 1.0 1.0 40(1) 20 7 3.50 2.0 2.0
4 11 4 3.50 2.0 2.0 40(2) 13 4.00 2.5 2.5
5 7 3.50 2.0 2.0 41 17 2 1.75 1.0 1.0
6 5 2.25 1.5 1.5 43 8 5.25 4.5 4.5
7 1 1.00 1.0 1.0 44(1) 10 6.00 3.0 3.0
8 7 5.75 2.0 2.0 44(2) 8 5.25 3.0 3.0
9 5 2.75 2.0 2.0 44(3) 18 3 1.75 1.0 1.0
10 15 3 2.75 2.0 2.0 44(4) 3 1.75 1.0 1.0
11 3 2.75 2.0 2.0 45 33 4 3.25 1.0 1.0
12 28 5 3.50 2.0 2.0 46 35 1.75 1.0 1.0
13(1) 12 7.00 4.0 4.0 47 4 2.50 1.0 1.0
13(2) 24 5 3.50 2.0 2.0 48 31 15 6.50 3.5 3.5
14(1) 4 3.50 1.0 1.0 49 5 1.75 1.0 1.0
14(2) 8 3.50 2.0 2.0 50 9 4.50 3.0 3.0
15 43 3 2.50 1.0 1.0 51 9 6.00 1.5 1.5
16(1) 5 3.75 3.0 3.0 52 8 4.75 4.0 4.0
16(2) 42 13 4.50 3.0 3.0 53 10 7.25 0.5 0.5
17 6 4.00 1.0 1.0 54 6 9 4.00 4.0 4.0
18 8 4.75 2.5 2.5 55 5 2.25 1.5 1.5
19 40 5 3.50 2.0 2.0 56 36 9 4.75 2.5 2.5
20 5 2.75 2.0 2.0 57(1) 30 6 2.50 1.0 1.0
21 1 0.75 0.0 0.0 57(2) 5 2.25 1.5 1.5
22(1) 29 4 3.00 1.5 1.5 57(3) 21 3 1.75 1.0 1.0
22(2) 6 3.25 2.5 2.5 58 5 3.50 2.0 2.0
23 1 0.75 0.0 0.0 59(1) 9 5.75 3.5 3.5
24 2 1.75 1.0 1.0 59(2) 15 7.00 4.0 4.0
25 1 1.00 1.0 1.0 60 3 2.25 1.5 1.5
26 21 11.00 6.5 6.5 61 7 2.75 2.0 2.0
27 9 4.75 2.5 2.5 62 6 2.75 2.0 2.0
28(1) 27 6 3.00 1.5 1.5 63 4 3.00 1.5 1.5
28(2) 41 5 2.25 1.5 1.5 64 34 16 9.25 4.0 4.0
29(1) 3 2.25 1.5 1.5 65 37 10 5.75 5.0 5.0
29(2) 4 1.75 1.0 1.0 66(1) 22 6 2.75 2.0 2.0
30(1) 32 6 4.00 2.5 2,5 66(2) 4 2.25 1.5 1.5
30(2) 3 2.25 1.5 1.5 67 14 6 3.75 0.5 0.5
31 10 5.75 3.5 3.5 68 3 1.50 1.5 1.5
32 10 3 2.00 2.0 2.0 69 2 1.75 1.0 1.0
33 38 5 3.25 1.0 1.0 70 4 3.00 1.5 1.5
34 2 10 3.75 1.5 1.5 71 3 2.25 1.5 1.5
35 23 6 4.00 3.5 3.5 72 16 2 1.75 1.0 1.0
36 1 1.50 1.5 1.5 73 5 3.50 2.0 2.0
37 7 10 5.75 2.0 2.0 74 2 1.75 1.0 1.0









Table Fl. (Contd.)


(1) (2) (3) (4) (5) (6) (1) (2) (3) (4) (5) (6)
76 19 3 1.75 1.0 1.0 83 4 2.75 2.0 2.0
77 3 2.50 1.0 1.0 84 6 5,50 4.0 4.0
78(1) 7 4.75 2.5 2.5 85(1) 9 6.25 4,0 4.0
78(2) 12 12 6.75 3.5 3.5 85(2) 2 1.75 1.0 1.0
79 5 9 4.00 2.5 2.5 85(3) 13 4 2.50 1.0 1.0
80 7 4.50 3.0 3.0 86 1 0.50 0.5 0.5
81 9 7 4.00 2.5 2.5 87 3 1.75 1.0 1.0
82 39 3 2.25 1.5 1,5 88 7 5.75 3.5 3.5
89 4 3.50 3.5 3.5









Table B2. Distribution and description of fields according to gandu


farming them.


Dan Mahawayi, 1966


(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b I a b
1(1) 15 N1 0.03 2.0 6.0 ADK 345 H 0.80 7.5 5.0 BDK
30 N1 0.10 2.0 6.0 ADK 368 H 10.69 8.5 4.0 ADK
90 N1 0.23 2.0 3.0 ADI. 377 H 8.68 8.5 3.5 ADK
94 H 0.30 2.0 4.0 ADK 471 N1 2.81 7.5 2.0 ADK
102 H 1.03 2.0 4.5 ADK 549 H 3.03 2.5 8/1 AEK
138 N1 0.18 3.0 4.0 ADO 573 N1 0.25 5.0 8.0 BDK
259 N1 0.97 5.5 5.0 ADK 579 H 1.82 4.0 8.0 AFK
322 Ni 1.07 7.5 4.0 BGK 582 H 1.51 3.5 8.0 AFK
324 N2 0.80 7.5 4.5 BDK 645 H 0.23 7.5 5.0 BDK
331 N1 0.73 6.5 5.0 BDK
__ TOTAL 35.26
1(2) 61 H 0.30 2.0 5.5 ADK 540 H 0.82 3.5 1.0 AFM
119 H 3.46 4.5 5.0 ADIV 289 H 0.34 5.0 5.0 BDM
121 H 1.33 3.5 4.5 ADK 633 H 1.69 14.5 4.0 ADL
126 H 0.07 4.0 5.0 ADK 300 B 0.91 5.5 4.0 AEO
132 H 0.62 2.5 4.0 ADT 302 H 0.50 4.5 4.0 ADL
253 H 2.49 5.5 5.5 AEN 320 H 4.38 7.5 4.5 CGR
334 H 0.93 7.5 5.0 BDL 325 H 1.53 7.0 4.5 BDL
351 H 0.39 7.0 5.0 BDO 366 H 6.05 9.0 4.0 AEK
410 H 2.12 6.5 4.0 AEO 370 H 9.51 8.5 3.5 AJS
423 H 0.67 4.5 4.0 BDL 467 H 5.73 10.5 3.0 ADL
434 H 0.52 4.0 3.0 BEN 191 H 1.60 6.5 7.0 AEM
465 H 7.61 8.5 2.5 AEK
TOTAL 53.57
1(3) 78 0.09 2.0 2.0 620 2.02 10.5 4.0
543 0.96 11.0 2.0 188 3.13 7.5 7.0
612 1.22 10.5 4.0 647 1.98 11.5 2.5

TOTAL 9.40
2 7 H 0.24 2.0 7.0 ADM 522 H 1.38 5.0 1.0 BDK
60 H 0.06 2.0 6.5 ADM 538 H 0.52 3.5 1.0 AEK
96 H 0.28 2.0 4.0 ADK 581 H 0.96 4.5 8.0 AFK
106 H 1.64 2.5 4.0 ADK 586 H 1.54 3.5 8.0 AFK
113 H 1.09 3.0 5.0 ADK 588 H 3.83 6.5 8.0 CGK
141 H 0.60 3.5 4.0 EDM 649 H 3.54 5.0 8.0 CGK
250 H 1.67 3.5 5.5 AFK 650 H 0.68 5.5 7.0 AEN
314 H 9.35 8.5 4.0 CEK 651 H 11.16 10.0 4.0 CGK
428 H 0.89 3.5 4.0 EDK 193 H 1.00 5.5 7.0 AEN
TOTAL 40.43
3 130 H 0.22 4.0 4.0 ADK 408 H 0.23 7.5 4.0 AEK
398 H 0.71 5.0 5.0 ADL 646 H 1.87 7.5 4.0 BEL

TOTAL 3.03
4 59 H 0.14 2.0 7.5 AFK 402 H 1.12 7.5 4.0 AFL
248 H 0.34 4.0 6.0 AFL 429 H 0.64 4.0 3.5 BDL
256 H 0.64 4.5 5.0 AFM 432 S 0.23 4.0 3.0 BEL
335 H 1.44 7.5 5.0 BDL 454 S 0.98 5.0 3.0 ADM

TOTAL 5.53
-..-..=.= = = n










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b a b
5 110 1.16 3.0 5.0 321 0.87 8.0 4.0
173 2.99 7.5 7.0 382 2.37 8.5 3.0
209 0.39 4.0 7.0

TOTAL_ 7.78
6 57 0.04 2.0 8/1 330 0.77 6.5 5.0
189 1.71 8.5 7.0 349 0.34 7.5 5.0
194 0.78 7.5 7.0 560 0.18 5.0 8/
200 0.46 5.5 7.0

TOTAL 4.28
7 55 0.07 2.0 8/1 406 1.25 7.5 4.0

TOTAL 1.32
8 54 0.18 2.01 8/
TOTAL 0.18
9 568 4.31 6.5 1.0
TOTAL 4.31
10 144 H 0.15 2.0 7.0 AFL 420 H 0.87 11.5 2.0 ADL
245 H 1.51 11.0 6.5 AEO
TOTAL 2.53
11 233 0.34 3.5 6.0 344 2.55 13.5 3.0
246 3.51 10.5 6.0 488 1.15 8.0 2.0
TOTAL 7.55
12 469 H 2.67 10.5 2.0 ADL 472 H 1.89 7.5 2.0 ADL

TOTAL, 4.52
13(1) 9 0.24 2.0 6.5 383 4.39 8.5 3.0
19 0.07 2.0 8.0 384 10.27 9.5 3.0
123 0.64 3.0 4.5 462 4.82 5.5 2.5
137 1.25 5.5 8.0 561 0.64 5.0 8/1
199 0.59 5.5 7.0 564 0.30 5.0 1.0
213 0.52 5.0 7.0 590 0.18 5.5 8.0
235 1.23 3.5 6.0 596 0.32 7.0 8.0
311 1.12 6.5 4.0 136 1.64 6.5 7.0

TOTAL 28.22
13(2) 214 B 0.82 5.0 7.0 BDK 607 H 1.35 10.5 7.5 AFO
378 H 9.99 10.5 3.0 ADKT
TOTAL 12.16
14(1) 16 0.67 2.0 7.5 470 4.85 8.5 2.0
152 1.16 2,5 7.5 490 1.46 6.0 2.0
175 2.90 8.5 7.0 516 1.22 6.0 1.0
176 3.76 7.5 7.5 569 1.23 6.0 8/1
206 0.25 4.0 7.0 591 0.61 6.0 8.0
347 0.52 7.0 5.0 1
TOTAL 18.63
14(2) 155 2.14 4.5 8.0 562 0.39 5.0 1.0
337 0.30 7.0 5.0 556 1.67 4.0 8/1
481 5.07 6.5 2.0
TOTAL 9.57
15 100 H 0.20 2.0 4.5 AEK 652 H 0.36 7.0 4.0 AEK

TOTAL 0.56










(i) (7 [8) (9) (10) (1 ) (7)- 8) (9) (10) (1)
a b __a b_
16(1) 1 0.47 2.0 7.0 5.Z4 2.42 2.5 1.0
92 0.39 2.0 4.5 566 0.57 6.0 1.0
521 0.50 5.0 1.0 593 0.24 7.0 8.0
TOTAL 4.59
16(2) 21 H 0.17 2.0 7.0 ADK 494 H 2.71 4.5 2.0 ADK
186 H 1.85 7.5 7.0 AEO 572 H 0.20 5.0 8/1 BDK
473 H 1.39 6.5 2.5 AEO
TOTAL 6.32
17 22 0.02 2.0 7.0 195 1.16 6.5 7.0
TOTAL 1.18
18 6 0.10 2.0 7.0 534 0.53 4.5 1.0
129 1.01 4.5 4.5 598 0.24 7.5 8.0
281 0.34 6.0 5.0 542 0.25 3.0 1.0
387 1.09 7.5 3.0 291 0.36 6.0 5.0
405 2.23 7.5 4.0 303 0.25 5.0 4.0
489 2.07 6.5 2.0
TOTAL 8.47
19 11 H 0.08 2.0 6.5 ADN 305 H 0.25 4.0 4.0 BDL
131 H 0.46 4.0 4.0 EDO 653 H 0.93 11.5 2.0 ADO
227 H 2.26 3.5 6.5 BDL
TOTAL 9.70
20 142 1.23 3.0 4.0 391 1.67 5.5 3.0
165 6.21 10.5 7.5 654 1.05 5.5 3.0
271 0.20 6.0 5.0 547 1.96 2.0 1.5
TOTAL 12.32
22(1 5 H 0.18 2.0 7.0 AHK 448 H 1.79 3.5 2.5 AEK
10 H 0.23 2.0 6.0 ADK 565 H 0.38 5.0 1.0 BDK
220 H 3.42 4.5 7.0 ADK 594 H 2.76 6.5 8.0 AFK
TOTAL 8.76
22(2) 204 3.01 3.5 7.5 215 0.34 4.5 7.0
346 0.32 8.0 5.0 238 0.30 6.0 6.0
348 0.36 7.0 5.0
TOTAL 4.33
26 14 0.11 2.0 6.0 517 1.61 5.5 1.0
185 0.52 8.5 7.0 519 0.46 5.5 1.0
224 0.23 2.0 7.0 528 3.22 4.5 1.5
237 3.28 5.5 6.0 529 0.32 8.5 2.0
241 1.85 6.5 7.0 535 1.03 4.0 1.0
292 0.98 6.0 5.0 550 0.61 2.5 1.0
327 1.25 6.0 4.5 552 1.40 3.0 1.0
515 0.46 6.5 1.0 555 1.21 3.5 1.0
TOTAL 18.54
27 23 0.05 2.0 7.0 354 0.29 7.0 5.0
29 0.19 2.0 6.5 379 2.83 9.5 3.0
228 0.32 3.0 6.0 557 0.96 4.5 1.0
239 1.25 6.5 6.0 559 0.33 5.0 8/1
312 1.80 7.0 4.0 583 1.32 2.0 8/1
TOTAL 9.34
-










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
1 a b I a b
28(1) 174 H 1.41 9.5 7.0 AGN 355 H 0.62 7.5 5.0 ADK
216 H 1.71 5.5 7.0 AEK 409 H 2.10 6.5 4.0 ADK
222 H 4.31 3.5 7.0 AEK 4 H 0.16 2.0 7.0 ADK
272 H 0.48 6.0 5.0 ADM
27 TOTAL 10.79
28(2) 145 H 0.15 2.0 7.0 AEK 415 H 0.34 5.0 4.0 AEK
218 H 0.91 4.5 7.0 AEK 558 H 0.59 4.0 1.0 BDK
TOTAL 1.99
29(1) 127 0.28 4.5 5.0 269 0.18 6.0 5.0
217 1.30 4.5 7.0 287 0.24 5.0 5.0
260 2.24 5.5 5.0 169 0.36 3.5 6.0
I TOTAL 4.61
29(2) 293 0.24 6.0 5.0 32 0.26 2.0 6.0
484 0.30 7.0 2.0 608 0.23 4.5 8/1
T__OTAL 1.03
S30(1) 13 H 0.23 2.0 6.0 AEK 288 H 0.20 5.0 5.0 BDK
146 0.53 2.5 5.5 ADK 301 H 0.18 4.0 4.0 BDK
198 H,N 8.01 5.5 7.0 AEK 99 H 0.16 2.0 6.5 ADK
283 H 0.26 6.0 5.0 BDK 599 H 0.26 7.5 8.0 B '
TOTAL 9.83
30(2) 107 0.20 2.0 6.5 208 0.75 4.0 7.0
147 0.36 2.5 5.5 262 0.13 6.0 5.0
205 0.78 4.0 7.0
TOTAL 2.22
31 42 2.93 2.5 5.5 509 0.39 7.0 2.0
184 6.84 9.5 7.0 512 0.42 6.0 1.0
196 0.98 6.0 7.0 600 0.14 8.0 8.0
201 0.80 5.0 7.0 501 10.11 7.5 2.0
203 1.78 4.5 7.5
TOTAL 24.39
32 109 H 0.34 2.5 5.0 ADM 264 H 0.88 5.5 5.0 AJN
124 H 0.80 5.5 7.0 AFN 286 H 0.48 5.0 5.0 BDM
202 H 1.12 4.5 7.5 AFM 401 H 2.08 8.0 3.0 AGL
211 H 0.75 3.5 7.0 AFN 424 H 0.62 4.0 4.0 EEM
219 H 0.68 4.0 7.0 ADN 637 H 3.01 6.5 7.0 AFO
257 H 1.00 5.0 5.0 AFN
TOTAL 11.76
33 116 H 1.32 2.5 4.5 ADU 234 H 0.64 4.0 6.0 ADL
140 H 0.18 3.0 4.0 ADL 273 H 0.29 6.0 5.0 EDL
197 H 1.37 6.0 7.0 AFO
TOTAL 3.80
34 105 H 0.39 2.0 5.0 ADK 276 H 0.82 6.0 5.0 BDK
149 H 0.32 3.5 5.0 AFK 447 H 1.89 3.0 2.0 ADK
252 H 2.84 5.5 5.5 AFK 624 H 3.15 11.5 4.0 AEK
TOTAL 9.41









(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)

35 122 H 0.16 3.0 4.5 ADK 298 H 0.87 5.0 4.5 BDM
128 H 0.81 3.5 4.5 ADM 326 H 2.34 6.5 4.0 BD
240 H 0.91 7.0 6.0 ADN 380 H 2.78 9.5 3.0 ADL
244 S1 1.35 11.0 7.0 AFO 411 S2 0.78 6.5 4.0 ADO
258 H 3.01 5.5 5.5 AFM
S TOTAL 13.01
36 304 0.79 4.0 4.0
TOTAL 0.79
37 108i H 0.28 2.0 5.0 ADK 172 H 0.41 16.0 7.0 ADK
167 H 2.35 16.5 7.0 ADK 255 H 0.95 4.5 5.0 ADK
170 H 4.20 17.5 7.0 ADK 318 H 0.32 8.5 4.0 ADK
171 H 2.92 18.5 7.0 ADK
TOTAL 11.43
38(1 41 0.09 2.0 5.0 182 1.09 5.5 7.5
73 0.39 2.5 4.5 290 0.41 5.5 5.0
101 0.42 2.0 5.0 333 0.36 7.0 5.0
114 0.25 3.0 5.0 475 2.43 11.0 2.5
163 0.49 80 8.0OTAL 5.93
tOTAL 5.93
38(2 103 0.19 2.0 5.0 231 1.12 3.5 6.0
112 1.28 2.5 8.0 553 0.33 2.5 1.0
150 0.64 4.0 5.0
TOTAL 3.56
38(3) 148 H 0.14 3.0 5.5 ADK 585 H 1.37 3.0 8.0 ADK
230 H 0.66 3.0 6.0 ADK 635 H 0.41 4.5 4.0 BDL
242 H 1.60 7.0 7.0 ADK
TOTAL 4.18
39 2 0.26 2.0 7.0 43 0.11 2.0 5.0
38 0.01 2.0 6.0 192 0.59 7.0 7.0
39 0.01 2.0 6.0 328 0.77 9.5 4.0
40 0.05 2.0 5.0 369 1.48 9.5 4.0
S___ OTAL 3.28
40(1) 33 H 0.02 2.0 6.0 ADL 412 H 1.19 6.0 4.0 AEN
37 H 0.10 2.0 5.5 ADL 536 H 0.19 4.0 1.0 ADK
120 H 0.16 3.5 5.0 ADL 575 H 0.25 5.0 8.0 BDK
265 H 2.32 6.5 5.0 ADL 577 H 0.25 4.5 8.0 BDK
266 H 0.17 7.0 5.0 BDM
_OTAL 4.65
40(2) 12 0.19 2.0 6.0 267 1.23 6.5 5.0
125 0.29 4.0 5.0 294 0.25 6.0 5.0
212 1.67 5.5 7.0 323 0.20 7.0 4.0
221 2.17 3.5 7.0 574 0.25 5.0 8.0
226 1.82 2.5 6.0 576 0.25 5.0 8.0
232 2.28 3.5 5.5
tOTAL 10.60
41 35 H 0.14 2.0 5.0 AEK 268 H 0.36 6.0 5.0 AEK
36 H 0.22 2.0 5.5 ADK 606 H 7.48 10.5 3.0 AEK
45 H 0.20 2.0 4.5 AEK
TOTAL 8.40
43 243 11.38 12.5 7.0 278 0.50 6.0 5.0
I 1 FAOTAL 11.88









(1) (7) (8) (9) (10) (11)1 (7) (8) (9) (10) (11)
a b _- a b
44(1) 31 0.30 2.0 6.5 168 3.28 12.5 7.0
104 0.24 2.0 4.5 178 7.41 6.5 7.5
156 0.23 3.5 6.0 343 2.11 7.0 5.0
159 1.00 6.5 8.0 603 0.71 8.5 8.5
162 0.46 8.0 8.0
TOTAL 15.74
44(2) 181 0.98 5.0 8.0 158 0.89 6.0 8.0
28 0.16 2.0 7.0 602 0.20 8.0 8.0
TOTAL 2.23
44(3) 179 H 1:23 6.5 8.0 AFK 595 H 0.82 7.5 8.0 AGK

__ __ TOTAL 2.05
44(4) 3 0.19 2.0 7.0 597 0.18 7.0 8.0
180 0.93 5.5 8.0
_TOTAL 1.30
45 24 S 0.20 2.0 7.0 ADK 161 H 0.34 3.5 6.0 ADK
27 H 0.05 2.0 7.0 ADK 207 H 1.07 4.5 7.0 AFK
160 H 3.67 7.5 7.5 AFK 570 H 4.24 6.5 8/1 ADL

TOTAL 9.57
46 466 H 1.71 9.5 2.5 ADL 508 H 2,94 7.5 2.0 ADL
483 H 0.18 5.0 2.0 ADL
TOTAL 4.83
47 26 0.06 2.0 7.5 457 2.78 6.0 3.0
151 0.73 2.0 7.5 499 2.95 6.5 2.0
270 0.22 6.0 5.0
TOTAL 6.74
48 25 H 0.06 2.0 7.0 AFK 229 H 1.78 3.0 6.0 ADK
44 B 0.21 2.0 5.0 ADK 510 H 3.86 6.5 1.5 CHK
58 H 0.13 2.0 7.5 ADK 531 H 0.75 5.0 1.0 EDK

TOTAL 6.79
49 70 0.54 2.0 4.0 307 0.25 4.5 4.0
56 0.09 2.0 8.0 336 2.40 10.5 3.0
299 1.00 9.5 3.0 339 0.36 8.0 5.0

TOTAL 4.64
50 46 0.36 2.0 1.0 279 0.24 6.0 5.0
117 0.20 3.0 4.0 417 5.70 6.5 4.0
433 0.30 2.5 4.0 438 0.89 3.0 3.0
137 0.63 3.0 4.0 464 0.65 6.5 3.0
164 0.66 8.5 8.0 506 2.08 10.5 2.0
275 0.48 5.5 5.0 610 2.08 11.5 4.0
277 0.39 6.0 5.0 628 2.29 12.5 4.0

TOTAL 16.95
51 8 0.18 2.0 6.5 541 0.98 3.5 1.0
249 1.80 4.0 5.5 545 0.75 2.5 1.5-
282 0.41 5.5 5.0 546 0.39 2.0 8/1
374 2.61 9.5 3.5 578 1.23 4,0 8/1
458 1.07 6.5 3.0 263 0.52 6.0 5.0

TOTAL 9.94










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
Sa bb I ___a b
52 459 0.80 7.0 3.0 445 0.77 2.5 2.0
493 0.75 5.0 2.0 450 0.65 3.5 2.5
505 1.61 10.5 2.0 62 0.02 2.0 1.0
362 2.44 17.5 4.0
__ TOTAL 7.04
53 375 0.64 10.0 3.0 414 1.23 5.5 4.0
TOTAL 1.87
54 18 H 0.05 2.0 7.5 ADK 225 H 0.36 2.5 6.5 AFV
20 H 0.47 2.0 8/1ADK 251 H 4.49 4.5 5.5 AFV
64 H 0.10 2.0 2.0 ADK 476 N 1.95 5.5 2.5 ADK
TOTAL 7.42
55 51 0.06 2.0 1.5 254 1.66 4.5 5.0
153 2.19 2.5 7,5 376 2.80 9.5 3.0
247 0.27 4.5 5.0 455 1.76 5.5 3.0
TOTAL 8.74
56 52 H 0.09 2.0 1.5 AEL 504 H 0.31 8.5 2.0 ADO
183 H 8.19 10.5 7.0ADO 539 H 0.73 4.0 1.0 AFN
310 H 1.14 6.0 4.0 CGN 551 H 1.98 11.5 3.0 ADL
TOTAL 12.44
57(1) 358 H 5.22 10.5 2.5 CGL 523 H 3.83 4.5 1.5 BDK
449 H 2.49 4.5 2.0ADL
TOTAL 11.54
57(2) 49 1.13 2.0 2.0 477 2.05 5.0 2.0
50 0.31 2.0 1.5 511 2.21 11.5 2.0
274 0.34 6.0 5.0 525 0.20 5.0 1.0
468 1.28 9.0 2.0 537 0.31 4.0 1.0
TOTAL 7.83
57(3) 48 H 0.76 2.0 1.5 AHK 527 H 3.47 3.5 1.5 AJV
518 H 0.80 5.5 1.5 EEK 604 H 4.24 11.5 2.0 AEL
_TOTAL 9.27
58 53 0.05 2.0 2.0 461 2.83 6.5 3.0
284 0.14 6.0 5.0 513 0.27 6.0 1.5
364 0.96 9.5 4.0 524 2.32 4.5 1.5
427 2.14 5.0 4.0
T TOTAL 8.71
59(1) 338 2.46 12.5 3.0 530 0.38 5.0 1.0
352 0.21 7.0 5.0 533 0.83 4.5 1.0
395 19.01 6.5 3.5 584 3.31 3.5 8/1
514 0.32 6.0 1.5
_TOTAL 26.52
59(2) 63 0.22 2.0 1.5
520 0.46 5.5 1.0 396 3.67 6.5 3.5
66 0.15 2.0 2.0 419 0.71 5.5 4.0
532 0.57 4.5 1.0 613 2.33 10.5 4.0
143 0.11 3.0 4.0 421 0.30 5.5 3.0
544 1.50 3.0 2.0 486 0.98 7.0 2.0
497 2.69 5.5 2.0
T_ OTAL 13.69










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b ___ a b
60 118 0.56 3.0 5.0 416 1.12 5.5 4.0
309 0.50 9.5 2.0 261 0.90 5.5 5.0

T__OTAL 3.08
61 135 0251 3.0 4.0 210 0.75 4.0 7.0
177 2.76 7.5 7.0 329 0.32 6.0 5.0
187 3.58 8.5 7.0 422 1.35 4.5 4.0
TOTAL 9.27
62 65 0.12 2.0 1.5 407 0.32 8.0 4.0
74 0.07 2.0 2.0 425 0.97 4.0 4.0
297 3.65 7.5 4.0 567 1.09 5.5 1.0
367 0.72 9.0 4.0
___ OTAL 6.94
63 67 0.18 2.0 2.0 443 1.19 2.5 3.0
526 0.62 4.0 2.0 446 0.40 2.5 2.0
385 3.24 8.5 3.0 495 1.92 3.5 2.0
400 2.01 7.5 3.0 498 1.76 5.5 2.0
430 1.23 4.5 3.5
t___OTAL 12.55
64 72 N 0.05 2.0 2.0 ADK 601 H 0.30 8.0 8.0 PDK
487 H 6.82 8.5 2.0 ADK 353 S 0.18 7.0 5.0 EEK
82 S 0.50 2.0 2.5 AEK 356 S 0.35 7.5 5.0 EEK
95 S 2.64 8.5 4.0 ADM 631 H 1.35 13.0 4.0 ADK
587 H 5.73 5.5 8.0 CHK 371 S 2.89 9.5 4.0 AEN
154 H 1.70 3.5 7.5 AFK 392 H 7.34 4.5 3.0 ADK
340 H 2.44 8.5 5.0 BDK 397 N 2.58 7.5 3.5 ADK
474 H 6.41 8.5 1.5 ADK
TOTAL 41.28
65 75 H 0.02 2.0 2.0 ADN 313 H 0.30 7.0 4.0 AGO
79 H 0.58 2.0 2.5 ADN 404 H 0.68 7.0 4.0 ADL
190 H 1.19 5.5 7.0 AEO 413 H 0.82 6.0 4.0 AEL
236 H 1.96 4.5 6.5 ADN 563 H 0.43 5.0 1.0 BDO
__OTAL 5.98
66 34 H 1.52 21.5 6.0 ADK 83 H 0.24 24.5 6.0 ADK
502 H 1.28 8.5 2.0 AFK 86 H 0.36 25.0 6.0 AEK
68 B 0.12 2.0 2.0 ADK 111 H 0.76 2.5 5.0 ADM
69 B 0.13 2.0 2.0 ADK 315 H 3.15 9.5 4.0 ADK
__ OTAL 7.56
67 71 H 0.31 2.0 2.0 ADL 496 H 2.81 5.0 2.0AEM
76 H 0.07 2.0 2.0 ADL OTAL
TOTAL 3.19
69 463 0.50 5.5 3.0
TOTAL 0.50
70 166 0.93 11.0 7.5 478 3.28 5.5 2.0
365 1.57 9.5 4.0 485 0.34 7.0 2.0
460 0.96 7.5 3.0 615 0.93 10.0 4.0
TOTAL 8.01
71 17 0.05 2.0 3.0 479 0.68 5.5 2.0
47 0.07 2.0 3.0 632 3.40 13.5 4.0

TOTAL_ 4.20









(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b____ a b
72 80 H 0.17 2.0 3.0 ADN 444 H 1.73 2.5 2.5 AEN
386 H 3.89 7.5 3.0 AGL 456 H 1.55 6.5 3.0 AEL

TOTAL 7.34
73 81 0.24 2.0 2.5 426 5.25 4.5 4.0
85 0.43 2.0 3.0 452 1.28 4.5 3.0
589 0.43 5.0 8.0 492 0.80 5.0 2.0
91 0.44 2.0 3.0 554 2.91 3.5 1.0
115 0.23 3.0 5.0 TTA 12.01

74 84 0.50 2.0 3.0 440 0.45 3.0 3.0
388 2.33 7.5 3.0 453 0.75 4.5 3.0

TOTAL 4.03
76 87 H 0.13 2.0 3.0 ADM 435 H 1.14 3.5 3.0 ADL
507 H 0.34 9.5 2.0 FDM 439 H 0.68 3.5 3.0 ADM
285 H 0.18 6.0 5.0 EDL 491 H 1.25 5.5 2.0 ADM
381 H 2.71 8.5 3.0 ADM 503 H 1.46 9.5 2.0 AEM
390 H 1.41 6.5 3.0 AEL30
TOTAL 9.30
77 89 0.10 2.0 3.0 442 0.45 2.5 2.5

TOTAL 0.55
78(1) 139 0.67 3.5 4.0 437 0.22 3.0 3.0

TOTAL 0.89
78(2) 134 H 3.31 2.5 3.5 AEK 605 H 0.64 7.5 5.0 ADK
436 H 1.57 3.5 3.5 ADK 625 H 3.28 11.5 4.0 AFK
451 H 6.45 4.5 2.5 ADK 629 H 6.48 12.5 4.0 AEK
500 H 7.85 7.5 2.0 ADK T
TOTAL 29.58
79 98 I-S: 0.64 2.0 3.5 ADL 389 H 3.51 6.5 3.0 ADL
332 S1 0.48 7.0 5.0 EDL 433 S1 0.32 4.0 3.0 BDL
350 S1 0.21 7.5 5.0 BDM 441 H,S2 4.52 3.5 3.0 ADL

TOTAL 9.68
80 97 0.97 2.0 3.5 372 2.81 8.0 4.0
223 1.41 5.5 4.5 394 4.62 5.5 3.0
280 0.42 6.0 5.0 399 0.93 7.5 3.5
342 4.87 7.5 5.0 431 0.93 4.5 3.0

TOTAL 16.96
81 77 H 1.32 3.5 4.0 ADK 571 H 0.48 5.5 8/1 BDK
88 H 2.06 2.0 3.5 ADK 580 H 1.87 4.5 8.0 AHK
93 H 0.04 2.0 5.0 ADK 636 H 1.29 14.5 4.0 EDK
308 H 3.31 5.5 4.0 CDK 648 H 0.84 5.0 4.0 ADK
480 H 5.36 14.5 4.0 ADK
TOTAL 16.57
82 357 H 18.75 16.5 3.5 AEL 641 H 4.47 14.5 3.0 AEL

TOTAL 23.22
83 640 4.52 13.5 3.5 644 2.21 15.0 3.0

__ TOTAL 6.73
84 643 23.11 14.5 3.5 360 2.67 17.5 3.0

T______OTAL 25.78_










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b __ a b '
85(1) 306 0.27 4.5 4.0 616 3.88 10.5 4.0
341 0.78 8.0 5.0 630 2.17 12.5 4.0
592 4.63 16.5 3.0 639 7.51 12.5 4.0

TOTAL 19.24
85(2) 623 5.66 11.5 4.0

TOTAL 5.66
85(3) 317 H 0.75 9.5 4.0 BDK 418 H 1.51 12.5 4.0 AEK
403 H 4.95 12.5 4.0 AEK 638 H 3.92 14.5 4.0 AEK
TOTAL 11.13
86 393 0.72 4.5 3.0 618 2.01 10.5 4.0

TOTAL 2.73
87 621 3.01 12.0 3.5

TOTAL 3.01
88 622 17.98 12.5 3.5 363 2.08 10.0 4.0
296 1.39 10.5 3.0 373 3.97 9.5 3.5
316 0.43 11.0 4.0 483 0.27 12.0 4.0
319 0.82 8.5 4.5 611 0.25 12.0 4.0
359 6.43 16.5 3.0 617 1.92 10.5 4.0
361 1.98 15.5 4.0 619 1.11 10.5 4.0

TOTAL 38.63
89 609 0.80 11.5 4.0 627 2.14 11.5 4.0
614 0.42 10.5 4.0 642 2.60 14.5 3.0
626 2.18 11.5 4.0
TOTAL 8.14


Grand Total = 1032.88 acres.









APPENDIX C


DOKA

In the following tables gandu numbers 1(1) to 49 inclusive, 92, 93(1)
and 93(2) are located in the central village and 51(1) to 91 in the
unguwa.


Table C1.


Number of residents
Doka, June 1966


and labour units according to gandu.


1(1)
1(2)
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17(1)
17(2)
17(3)
18
19
20
21
22
23
24
25(1)
25(2)
26
27
28(1)
28(2)
28(3)
29(1)
29(2)
30(1)
30(2)
30(3)
31
32
33
34
35
36(1)


6.25
1.75
3.75
4.25
4.75
1.75
5.25
1.75
7.50
4.25
1.75
4.75
1.25.
7.00
1.75
4.00
7.50
4.25
5.00
2.25
5.25
3.00
5.00
5.75
6.50
2.75
8.50
1.75
7.75
3.25
3.25
4.75
2.75
4.00
4.50
2.75
10.75
2.25
2.50
5.75
3.00
6.50
3.50
1.75
6.00


4.0 4.0
1.0 1.0
1.5 1.5
2.0 2.0
2.5 2.5
1.0 1.0
3.0 3.0
1.0 1.0
6.0 6.0
2.0 2.0
1.0 1.0
2.5 2.5
0.5 0.5
4.0 4.0
1.0 1.0
2.5 2.5
6.0 6.0
2.0 2.0
3.5 3.5
1.5 1.5
4.5 4.5
1.5 1.5
3.5 3.5
3.0 3.0
2.0 2.0
2.0 2.0
5.5 5.5
1.0 1.0
5.5 5.5
1.0 1.0
2.5 2.5
2.5 2.5
2.0 2.0
2.5 2.5
3.0 3.0
2.0 2.0
5.5 5.5
1.5 1.5
1.0 1.0
3.5 3.5
1.5 1.5
3.5 3.5
2.0 2.0
1.0 1.0
3.0 3.0


(1) (2) (3) (4) (5) (6) (1) (2) (3) (4) (5) (6)


36(2)
36(3)
36(4)
36(5)
36(6)
36(7)
36(8)
37(1)
37(2)
37(3)
38
39(1)
39(2)
39(3)
39(4)
40
41
42
43(1)
43(2)
44(1)
44(2)
45
46
47(1)
47(2)
47(3)
48
49
51(1)
51(2)
51(3)
52(1)
52(2)
52(3)
53
54
55
56
57
58
59(1)
59(2)
60(1)
60(2)


5.75
6.50
1.75
3.50
4.50
1.75
2.25
7.25
4.50
1.75
2.25
7.50
2.25
1.50
1.75
3.25
7.50
3.50
5.75
3.00
5.25
1.75
1.75
3.25
3.50
2.75
2.25
3.00
3.25
2.75
1.75
2.50
3.50
1.75
1.75
1.75
4.25
2.25
3.50
4.25
6.00
4.25
1.00
2.50
2.25


2.0
3.5
1.0
2.0
3.0
1.0
1.5
5.0
3.0
1.0
1.5
4.5
1.5
1.5
1.0
2.5
4.5
2.0
3.5
1.5
3.0
1.0
1.0
2.5
2.0
2.0
1.5
1.5
1.0
0.5
1.0
1.0
2.0
1.0
1.0
1.0
2.0
1.5
2.0
\?.0
4.5
3.5
1.0
1.0
1.5


2.0
3.5
1.0
2.0
3.0
1.0
1.5
5.0
3.0
1.0
1.5
4.5
1.5
1.5
1.0
2.5
4.5
2.0
3.5
1.5
3.0
1.0
1.0
2.5
2.0
2.0
1.5
1.5
1.0
0.5
1.0
1.0
2.0
1.0
1.0
1.0
2.0
1.5
2.0
2.0
4.5
3.5
1.0
1.0
1.5









Table C1. (Contd.)


(1) I (2) (3) (4) 1 (5) (6) (1) (2) I(3) (4) (5) (6)


60(3)
60(4)
61(1)
61(2)
61(3)
61(4)
61(5)
62(1)
62(2)
64(1)
64(2)
65(1)
65(2)
65(3)
66(1)
66(2)
66(3)
67
68
69(1)
69(2)
70
71(1)
71(2)
71(3)
71(4)
71(5)
72
73(1)
73(2)
73(3)


14





24

20





39


22
37





16



30


1
2
6
4
13
5
2
7
2
31
3
2
6
7
5
7
4
8
5
3
3
10
7
5
8
3
4
8
4
8
6


1.75
1.75
3.75
2.25
7.50
2.50
2.25
4.75
1.50
15.75
1.75
1.75
3.25
4.25
3.25
3.75
2.50
5.25
2.25
1.75
1.75
6.75
5.25
2.75
4.00
2.25
3.50
5.25
2.50
5.00
3.25


Ir





32


1.0
1.0
3.0
1.5
4.5
1.0
1.5
2.5
1.5
10.5
1.0
1.0
2.5
3.5
1.0
3.0
1.0
3.0
1.5
1.0
1.0
3.0
3.0
2.0
2.5
1.5
2.0
3.0
1.0
3.5
1.0


i 1 .. .


_______ -4 .J4 ,- -


I


I


I


1.0
1.0
3.0
1.5
4.5
1.0
1.5
2.5
1.5
10.5
1.0
1.0
2.5
3.5
1.0
3.0
1.0
3.0
1.5
1.0
1.0
3.0
3.0
2.0
2.5
1.5
2.0
3.0
1.0
3.5
1.0


74
75(1)
75(2)
75(3)
75(4)
75(5)
75(6)
75(7)
75(8)
77
78
79
80(1)
80(2)
81(1)
81(2)
82
83
84(1)
84(2)
85
86
87
88(1)
88(2)
89
90(1)
90(2)
91
92
93(1)
93(2)


4
5
8
3
5
3
2
5
7
5
5
14
5
4
8
2
18
5
13
4
4
11
5
13
10
5
6
3
9
13
6
3


2.75
2.50
5.50
2.50
3.00
2.25
1.75
2.00
4.00
2.25
4.00
8.50
2.75
1.75
4.00
1.50
10.75
2.25
8.25
2.25
3.25
7.00
2.25
7.25
7.00
2.25
3.75
1.75
5.75
7.50
3.25
1.75


0.5
1.0
4.0
1.0
1.5
1.5
1.0
2.0
2.5
1.5
2.5
5.5
2.0
1.0
2.5
1.5
7.0
1.5
4.5
1.5
2.5
4.0
1.5
3.5
4.0
1.5
3.0
1.0
3.5
4.5
2.5
1.0


0.5
1.0
4.0
1.0
1.5
1.5
1.0
2.0
2.5
1.5
2.5
5.5
2.0
1.0
2.5
1.5
7.0
1.5
4.5
1.5
2.5
4.0
1.5
3.5
4.0
1.5
3.0
1.0
3.5
4.5
2.5
1.0









Table C2.


Distribution and description of fields
farming them. Doka, 1966


according to gandu


(1) (7) (8) (9) (1W ) (11) (7) (8) (9) (10) (11)
a b ___ a b
1(1) 81 H 2.85 2.5 5.5 AF 436 H 2.43 7.5 4.0 BAK
106 H 3.92 8.5 5.0 ADK 460 S 0.46 3.5 4.0 ADK
203 H 0.90 3.5 7.0 AFE 1
TOTAL 10.56
1(2) 102 4.20 6.5 5.0 524 0.34 7.5 3.0
167 1.39 4.5 7.0 TOTA 593
TOTAL 5.93
2 88 2.19 4.5 5.0 330 1.49 7.5 5.0
92 1.93 4.5 5.0 480 0.16 7.0 4.0
TOTAL_ 5.77
3 220 H 1.25 4.5 4.0 AFK 356 H 1.19 6.5 4.5 AEL
350 H 0.97 8.0 5.0 EDK 595 H 1.35 10.5 4.0 CEK

TOTAL 4.76
4 122 0.44 5.0 6.0 461 1.33 3.5 4.0
132 1.25 7.0 6.0 469 0.95 6.5 3.0
343 1.75 10.0 4.0 39 0.49 1.0 3.0
351 1.47 7.5 5.0 TOTA66
TOTAL 7.66
5 116 3.56 14.5 6.0 326 0.54 7.0 3.0

TOTAL 4.10
6 94 H 1.13 3.5 5.5 AFL 408 H 0.16 9.0 4.0 BDK
130 H 1.31 7.0 6.0 AFK 455 H 2.21 4.5 4.0 AFK
135 H 2.93 6.5 6.0 AFK 504 H 0.22 8.0 4.0 BDK
174 H 0.52 2.0 6.5 AFK 43 H 0.35 1.0 4.0 AFM
TOTAL 8.83
7 114 H 0.56 12.0 6.0 AFL 376 H 0.32 5.5 4.0 ADK
115 H 0.40 14.0 6.0 AFK TOA
TOTAL 1.28
8 38 H 2.08 1.5 2.5 AFK 235 H 0.70 5.0 1.0 BDK
97 H 0.28 4.0 6.0 AFK 510 H 0.42 8.0 4.0 BDK
162 H 5.06 3.5 6.5 AFK 622 H 0.99 10.5 3.0 AFO
TOTAL 9.53
9 121 0.50 5.5 6.0 311 1.05 3.5 3.0
123 1.07 4.5 6.0 447 3.02 6.5 3.0
219 1.85 8.5 8.0 477 0.40 7.0 3.0
234 0.46 5.5 1.0 479 0.14 7.0 3.5
303 1.19 2.5 2.5 41 0.61 1.0 3.0
TOTAL 10.29
10 268 0.70 3.0 8.0 236 0.78 5.5 1.0
294 0.34 4.0 2.0 492 0.22 8.0 4.0
304 1.39 3.0 3.0 552 0.54 9.0 3.0
434 2.45 5.5 6.0
TOTAL_ 6.42
11 373 H 1.35 3.5 4.0 AFK 14 H 1.19 3.5 4.5 ADK
808 H 0.10 14.0 2.0 BDK 42 H 0.66 1.0 3.0 AFK
TOTAL 3.30
12 372 0.54 3.5 4.0
TOTAL 0.54










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) 1(11)
_a b __ a b
13 82 2.51 3.0 5.0 371 0.42 4.0 4.5
87 1.29 5.5 5.0 384 0.28 8.0 4.0
296 0.24 4.0 2.0 540 0.22 8.0 3.0
301 0.84 3.5 2.0 34 0.26 2.0 3.5

TOTAL 6.06
14 I00 i.8b 55b b.b I / U.2 b.U U .
103 2.87 7.0 5.5 227 0.28 8.0 3.5

TOTAL 5.28
15 225 H 1.51 7.5 8.0 AFK 32 H 0.93 2.0 4.0AFK
310 H 0.52 3.5 3.0 AFK 62 H 0.11 1.0 8/ AFK

TOTAL 3.07
16 223 2.65 3.5 2.5 306 3.40 3.5 3.0
414 0.42 6.0 1.0 518 0.46 7.5 3.5
280 3.10 2.5 1.5 31 0.63 1.5 4.0

TOTAL 10.66
17(1) 279 H 2.55 2.5 8/1 ADK 318 H 1.29 6.0 3.0 FDK
85 H 1.97 4.5 5.0 AFK 335 H 4.32 9.5 5.0 AFR
298 H 0.40 4.0 2.0 FDK 360 H 4.18 7.5 5.0AFR
313 H 0.82 6.0 3.0 EDK 366 H 0.60 5.0 5.0AFO

TOTAL 16.13
17(2) 104 3.82 6.5 5.0 361 0.48 6.0 5.0
285 2.15 2.5 1.5 368 0.08 4.5 4.5
320 1.29 6.5 3.0 370 0.32 4.0 4.5
323 0.22 6.0 3.0 383 0.48 7.5 4.0
357 4.00 6.5 5.0 391 0.38 8.0 4.0
358 1.31 7.0 5.0
TOTAL 114.53
17(3) 377 0.40 5.5 4.0 362 1.41 6.5 5.0
107 4.94 7.5 5.0 369 0.30 4.0 5.0
332 4.14 8.5 5.0 395 0.24 8.0 4.0
337 2.49 10.5 5.0
TOTAL 13.92
18 99 H 2.23 5.5 5.5 AFK 302 H 1.43 3.5 2.5 CGK
286 H 2.09 2.5 2.0 AFK 44 H 1.28 1.0 2.5ADK
TOTAL 7.03
19 242 0.89 4.0 8.0 338 0.66 4.0 2.0
291 0.38 3.5 2.0 193
TOTAL 1.93
20 374 1.87 4.5 4.0 491 0.14 8.0 4.0
396 0.42 8.0 4.0
TOTAL 2.43
21 312 7.16 5.5 2.5 378 2.03 6.0 4.0
TOTAL 9.19
22 230 H 1.51 7.0 8/1 AFK 314 S 1.67 5.5 3.0AFK
233 H 1.85 5.5 1.0 AFK 528 S 1.39 8.0 3.0 CHK
237 S 0.60 5.0 1.0 EDK 25 H 0.38 1.0 4.0 AFK
241 S 0.36 4.0 1.0 CDK 46 H 0.11 1.0 2.5 AFK
254 H 9.55 7.5 8.0 CFK 1
TOTAL 17.42










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b __ a b
23 256 H 1.65 6.0 8.0 AFK 47 H 0.46 1.0 2.5 AEK
526 H 0.40 7.5 3.0 EDK
TOTAL 2.51
24 243 1.15 4.5 8.0 265 1.61 4.0 8.0
251 2.17 5.5 8.0 278 0.76 2.5 8/1
262 0.89 4.5 8.0 283 0.62 3.5 1.5
267 0.44 4.0 8.0 315 5.07 5.5 3.0
244 0.74 4.5 8.0 490 0.32 8.0 4.0
261 0.64 5.0 8.0 499 0.84 9.0 4.0
156 1.55 3.5 6.0 508 0.32 8.0 4.0
179 1.95 2.0 7.5 527 0.34 7.5 3.0
210 0.52 3.5 8.0 537 1.61 7.5 3.5
228 3.38 6.5 8.0 56 1.57 1.0 1.5
238 6.63 4.5 8/1 59 0.30 1.0 8/1
TOTAL 33.42
25(1) 246 H 1.63 5.5 8/1 AFK 273 H 0.64 4.0 1.0 BDK
259 H 0.87 5.0 8.0 AFK 530 H 2.49 7.5 3.0 ADK
270 H 1.47 3.5 8/1 AFK TOTAL 10
TOTAL 7.10
25(2) 260 0.74 5.0 8.0 438 0.48 6.0 4.0
263 0.68 4.5 8.0 446 0.40 7.0 3.0
139 0.70 6.5 6.0 449 1.65 5.5 3.0
140 3.36 8.5 6.5 467 0.28 5.0 3.0
142 1.97 7.5 6.5 474 0.89 7.5 3.0
417 0.20 8.0 4.0 513 0.30 7.5 4.0
TOTAL 11.65
26 252 H 0.89 6.0 8.0 AFK 48 H 1.46 1.0 2.0 AFK
297 H 1.03 3.5 2.0 BEK
TOTAL 3.38
27 86 H 3.90 5.5 5.0 AFK 515 H 0.14 7.0 4.0 AFK
271 H 5.51 3.5 8/1 CDK 53 H 0.19 1.5 1.0 ADK
476 H 0.26 7.0 3.0 BFK
TOTAL 10.00
28(1) 264 3.34 3.5 8.0 531 1.57 7.5 3.0
274 1.97 3.5 1.0 544 0.30 8.0 3.0
319 0.30 6.5 3.0 548 0.66 8.0 3.0
328 0.87 7.5 3.0 33 0.32 2.0 4.0
352 3.70 5.5 7.0 49 0.59 1.0 1.5
420 0.62 9.0 4.0 58 0.30 1.0 1.0
471 2.53 7.0 3.0 TOTAL 17.07
TOTAL 17.07
28(2) 150 1.05 5.0 6.5 215 0.42 5.0 8.0
209 0.62 3.0 8.0 545 0.26 8.0 3.0
TOTAL 2.35
28(3) 149 2.65 5.5 6.5 305 0.72 2.5 3.0
158 0.82 3.0 6.0 529 0.16 8.5 3.0
208 0,52 3.0 8.0 546 0.18 8.0 3.0
TOTAL 5.05
29(1) 195 H 4.08 5.5 7.0 AFK 346 H 0.22 4.0 2.0 BDK
224 H 0.76 5.5 8.0 AFK 489 H 0.24 8.0 4.0 BFK
257 H 1.11 5.5 8.0 AFK 52 H 0.62 1.0 1.0 ADK
TOTAL 7.03










(1) (7) (8) () (1 ) ( ) () (8) (9) (10) (11)
a b ____a b
29(2) 216 4.12 5.5 7.5 51 0.33 1.0 1.5
481 0.20 7.0 4.0
TOTAL 4.65
30(1) 16 0.85 1.4 4.5 177 0.64 2.0 7.5
37 2.71 1.5 3.5 272 0.48 4.0 1.0
20 0.29 2.0 4.0 275 3.10 2.5 8.0
83 1.89 3.5 5.0 284 0.78 3.0 1.5
90 1.47 4.5 5.0 300 0.82 2.5 2.0
96 4.12 3.5 5.5 390 1.03 8.5 4.0
101 8.20 6.5 5.5 418 0.26 8.5 4.0
109 1.83 8.5 5.5 433 3.78 7.5 4.0
117 19.33 9.5 6.0 498 0.12 8.0 4.0
119 2.45 7.5 6.0 519 0.28 8.0 3.5
TOTAL 54.43
30(2) 206 1.17 2.5 7.5 485 0.16 7.0 4.0
276 0.12 3.0 8.0 487 0.20 7.5 4.0
329 3.40 8.5 5.0 501 0.30 8.0 4.0
394 0.22 8.0 4.0 61 0.11 1.0 8.0
419 0.32 8.5 4.0 TOTAL 00
TOTAL 6.00
30(3) 182 1.25 2.5 7.0 410 0.62 9.5 4.0
TOTAL 1.87
31 421 H 0.36 9.0 4.0 EDK 488 H 0.14 8.0 4.0 BDL
134 H 1.95 6.5 6.0 ADK 532 H 2.07 7.0 3.0 CEK
154 H 2.53 4.5 6.0 AFK 45 H 0.34 1.0 2.0AFK
424 H 0.22 8.0 4.0 BDK 60 H 0.27 1.0 8/1AFK
457 H 2.93 5.5 4.0 AFO 63 H 0.06 1.0 8.0 AFL
TOTAL 10.87
32 151 H 2.69 4.5 6.0 AFK 522 H 0.32 8.0 3.0BEK
258 H 3.36 5.0 8.0 AFK 547 H 0.22 8.0 3.01BEK
472 H 0.48 7.0 3.0 PDK 64 H 0.08 1.0 8/1AFK
TOTAL 7.15
33 231 1.85 6.5 8/1 221 1.25 6.5 8.0
160 1.17 5.5 7.5 240 1.57 4.5 1.0
180 0.66 2.5 7.5 413 0.20 9.5 4.0
198 1.31 5.5 7.0 19 1.13 1.5 4.5
205 2.91 3.5 7.5 68 0.31 1.0 7.0
TOTAL 12.36
34 217 7.64 6.5 7.5 541 0.22 8.0 3.0
218 3.80 7.5 7.5 66 0.26 1.0 7.5
222 0.85 6.5 8.0 69 0.14 1.0 7.0
393 0.16 8.0 4.0 TOTAL 13.07

35 71 0.17 1.0 6.5
TOTAL 0.17
36(1) 120 3.92 6.5 6.0 500 0.28 8.0 4.0
292 0.20 4.0 2.0 22 1.43 1.0 3.5
TOTAL 5.83







(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b __ __a b
36(2) 126 0.60 6.0 6.0 175 1.23 2.0 7.0
129 6.13 7.5 6.0 308 2.13 4.5 3.0
133 1.81 7.0 6.0 427 0.30 8.0 4.0
137 0.68 6.5 6.0 18 0.36 1.0 6.5
159 1.81 2.5 6.5 29 0,68 1.0 4.0

TOTAL 15.73
36(3) 125 1.29 5.0 6.0 389 0.26 8.5 4.0
128 0.24 6.0 7.0 450 3.16 5.5 3.5
145 0.46 6,5 7.0 470 1.55 6.5 3.0
186 1.49 4.5 7.0 517 0.16 7.0 3.5
189 3.22 5.5 7.0 70 0.35 1.0 6.5
192 1.07 6.0 7.0 183 1.41 2.5 7.0
194 0.40 6.0 7.0 207 0.30 3,0 8.0
TOTAL 15.36
36(4) 164 1.31 5.5 7.0 465 0.87 4.0 3.0
172 0.40 3.0 7.0 506 0.18 8.0 4.0
185 0.52 3.0 7.0 543 0.18 8.0 3.0
404 0.46 8.5 4.0 78 0.27 1.0 6.0
451 3.16 5.5 4.0
TOTAL 7.35
36(5) 98 1.19 4.0 5.5 538 0.48 8.0 3.0
196 1.93 5.5 7,0 6 0.21 1.0 5.0
406 0.36 9.0 4.0
TOTAL 4.17
36(6) 127 0.40 6.0 6.0 347 0.20 8.0 5.0
136 2.33 6.5 6.0 415 0.24 8.5 4.0
155 1.69 4.0 6.0 67 0.27 1.0 7.5

__TOTAL 5.13
36(7) 138 1.85 7.5 6.0 454 0.93 4.5 4.0
176 1.07 2.0 7.0 466 0.97 4.0 3.0
423 0.34 8.0 4.0 57 0.55 1.0 8/1
428 0.34 8.0 4.0 73 0.19 1.0 6.0
444 2.67 6.5 3.5 TOTAL 8.91
TOTAL 8.91
36(8) 161 1.13 3.0 6.5 429 0.26 8.0 4.0
173 0.99 2.5 7.0 442 2.69 6.5 4.0
255 0.70 6.5 8.0 452 0.48 4.5 3.5
TOTAL 6.25
37(1) 118 1.19 7.5 6.0 341 2.21 10.5 4.0
124 0.78 6B.5 6.0 387 0.34 8.5 4.0
144 0.38 6.5 7.0 480 0.34 8.5 4.0
178 0.70 2.0 8.0 542 0.12 8.0 3.0
187 2.31 4.5 7.0 23 0.69 1.0 4.0
212 2.95 4.5 7.5 65 0.49 1.0 7.5
327 0.30 7.0 3.0
TOTAL 12.80
37(2) 148 0.28 4.0 7.0 453 0.46 4.5 4.0
200 0.85 4.5 7.0 4 0.38 1.0 5.0
386 0.46 8.0 4.0
TOTAL 2.43







(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
I a b b_ a b
37(3 188 1.37 5.5 7.0 213 1.55 4.5 7.5
199 1.27 5.0 7.0 496 0.16 8.0 4.0

TOTAL 4.35
38 166 0.99 4.5 7.0 169 1.41 3.5 7.0

TOTAL 2.40
39(1 79 0.52 2.0 6.0 288 0.74 3.0 -2.0
89 1.45 3.5 5.0 290 0.28 3.0 2.0
131 0.64 4.0 7.0 463 2.41 3.5 3.5
190 2.96 6.5 7.0 509 0.18 8.0 4.0
201 0.50 4.0 7.0 607 2.93 15.0 3.0
248 0.30 6.0 8.0 2 0.42 1.0 5.5
250 1.97 5.5 8.0
TOTAL 15.30
39(2) 232 1.13 6.0 8/1 293 0.87 3.5 2.0
229 1.79 6.5 8.0
=TOTAL 3.79
39(3) 247 0.76 5.5 8/1 348 0.34 8.0 5.0
249 0.46 6.0 8.0 462 1.33 3.5 4.0
287 0.80 3.0 2.0 30 0.24 1.5 4.0

TOTAL 3.93
39(4) 147 3.08 6.5 7.0 507 0.14 8.0 4.0
289 0.84 3.0 2.0 11 0.32 1.0 5.0
295 0.32 4.0 2.0
TOTAL 4.70
40 108 6.17 8.5 5.5 77 0.18 1.0 6.0
363 3.44 5.5 5.0 TOT
TOTAL 9.79
41 84 3.92 4.5 5.0 484 0.56 7.0 4.0
95 2.93 3.0 5.5 593 0.34 8.0 3.0
282 0.54 4.0 1.0 55 1.89 5.5 5.0
339 2.93 9.5 5.0 5 0.11 1.0 5.0
355 2.85 7.5 4.5 15 1.63 1.5 4.5
359 1.65 7.0 5.0 74 0.21 1.0 6.0
365 0.70 5.0 5.0
TOTAL 20.26
42 80 1.57 2.5 6.0 456 0.84 4.5 4.0
165 2.07 5.5 7.0 505 0.16 8.0 4.0
171 0.36 3.5 7.0 512 0.36 7.5 4.0
253 1.91 6.5 8.0
TOTAL 7.27
43(1) 111 2.15 9.5 6.0 388 0.42 9.0 4.0
163 4.44 4.5 6.5 405 0.28 8.5 4.0
191 0.99 6.0 5.0 435 5.19 7.5 4.0
202 2.45 3.5 7.0 511 0.56 7.5 4.0
214 0.80 4.5 8.0 26 0.14 1.0 4.0
380 0.74 6.5 4.0 72 0.40 1.0 6.0

TOTAL 18.56
43(2) 181 0.32 2.0 7.0 27 0.13 1.0 4.0
211 1.07 4.5 8.0
TOTAL 1.52










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
Sa b I a b_
44(1); 143 B2 0.44 6.5 6.5 AFK 402 H 0.22 8.0 4.0 EDK
91 H 1.51 4.5 5.0 ADK 409 P2 0.20 9.0 4.0 BDK
113 H/B2 3.50 8.5 6.0 AJK 411 H 0.32 9.5 4.0 PEK
204 H 1.43 3.5 7.5 ADK 416 B1 0.34 8.0 ,0 EEK
299 B1 2.27 3.5 2.0 ADK 432 H 0.54 7.5 4.0 BEK
324 B1 0.28 6.5 3.0 EDK 437 H 0.60 6.5 4.0 ADO
392 H 0.24 8.0 4.0 BEK 459 H 1.39 4.5 4.0 AFO
398 H 0.52 7.5 4.0 BEK 7 H 0.06 1.0 5.0 AFK
1 40 H 0.28 1.0 5.0 AEK
TOTAL 14.14
44(2) 110 2.07 10.0 6.0 412 1.91 9.5 4.0
168 2.13 4.5 7.0 464 1.47 3.5 3.5
TOTAL 7.58
45 382 3.42 6.5 4.0 534 0.46 6.5 3.0
468 1.49 5.0 3.0 1 0.70 1.5 5.0
TOTAL 6.07
46 439 H 1.79 5.5 4.0 AFK 514 H 0.18 7.0 4.0 EDK
443 H 0.54 6.5 3.5 BDK 75 H 0.48 1.0 6.0 AFK
478 H 0.48 7.0 3.5 AFK
TOTAL 3.47
47(1) 184 H 3.48 12.5 5.0 AEK 441 H 0.56 6.0 4.0 AEO
342 H 4.48 9.5 4.0 AEL 693 H 6.51 13.5 5.0 AEK
349 H 2.55 7.5 5.0 BEK 3 H 0.43 1.0 5.5 AFK
375 H 0.70 5.0 4.0 AEK 9 H 0,23 2.0 4.0 AFK
440 H 2.01 5.5 4.0 AJV 10 H 0.47 1.0 5.0 AFK
TOTAL 21.42_
47(2) 226 0.38 5.5 4.0 345 0.58 7.5 4.0
344 1.09 9.5 4.0 8 0.21 1.5 4.0
TOTAL 2.26
47(3) 407 H 0.78 9.0 4.0 BEK 17 H 0,25 2.0 4.5 AFK
379 H 0.58 6.5 4.0 BEK 21 H 0.57 1.5 4.0 AFK
381 H 1.01 6,5 4.0 AEK 28 H 0.30 1.0 4.0 AEM
35 H 2.47 11.5 5.0 AFKO L
TOTAL 5.96
48 422 H 0.32 8.5 4.0 BDK 54 H 4.04 6.5 5.0 ADK
93 H 0.60 3.5 5.0 AEK 12 H 0.83 1.0 4.5 AEK
367 H 8.96 5.5 4.5 AEK 76 H 0.17 1.0 6.0 AFK
385 H 0.40 8.0 4.0 BDK
TOTAL 15.32
49 105 H 1.95 7.5 5.0 AEK 353 H 8.80 8.5 4.5 AEK
331 H 1.17 7.5 5.0 AEK 13 H 0.71 1.0 4.5 AEK
340 H 1.35 9.5 5.0 AEK
TOTAL 13.98
51(1) 585 5.65 9.5 3.5 605 7.70 14.5 3.0
588 6.70 10.5 4.0 608 0.74 13.0 3,0
598 0.26 12.0 4.0 612 1.49 11.5 3.5
600 0.22 12.5 4.0 616 0.93 11.0 3.0
OTAL 23.69
51(2) 307 1.05 13.5 3.0 601 0.66 13.5 4.0
596 0.26 11.0 4.0 602 1.77 13.5 4.0
597 0.24 12.0 4.0 614 0.32 11.0 3.0
599 0.26 12.5 4.0
a TOTAL 4.56 -










(7) 1


(9)


(1


0)
I b


(11)


(8)


(10)
a b


(11)


51(3) 603 1.75 14.0 4.0 609 3.90 12.5 3.5
604 3.26 14.5 3.0 613 1.21 11.5 3.0
TOTA, 10.12
52(1) 266 0.40 11.5 3.0 615 0.44 11.0 3.0
277 0.48 11.0 3.0 669 1.09 11.0 3.0
586 12.96 10.5 3.5 671 3.06 11.5 3.0
594 0.60 11.0 4.0 675 3.42 11.5 3.0
TOTAL 22.45
52(2)1 587 1.19 11.0 4.0 592 0.36 11.0 4.0
589 0.91 10.5 4.0 618 0.36 11.0 3.0
TOTAL 2.82
52(3)j 281 0.87 11.0 3.0 673 1.99 12.0 3.0
591 0.18 11.0 4.0 TOTA 3.04
53 593 H 0.30 11.0 4.0 AEK 677 H 1.39 11.0 3.0 AFK
617 H 0.38 11.0 3.0 AEK
TOTAl 2.07
S54 568 H 0.22 9.0 3.0 PEK 629 H 0.34 10.5 3.0 AEK
570 H 0.24 9.0 3.0 BEK 637 H 0.36 9.5 3.0 AEK
619 H 5.65 10.5 3.0 AEK 646 H 1.13 11.5 3.0 PEK
TOTAL 7.94
55 564 0.26 9.0 3.0 620 1.03 10.5 3.0
569 0.20 9.0 3.0 621 0.36 10.0 3.0
579 0.46 9.5 3.0 676 1.53 11.0 3.0
TOTAL 3.84
56 503 0.16 8.0 4.0 628 3.58 10.5 3.0
625 1.19 9.5 3.0 636 0.85 9.0 3.0
TOTAL 5.78
57 744 1.81 10.5 3.0 711 1.77 9.5 3.0
640 0.22 10.0 3.0 751 1.07 11.0 2.5
557 0.16 8.0 3.0 558 0.36 8.5 3.0
559 0.18 8.0 3.0 565 0.40 9.0 3.0
561 0.18 9.0 3.0 626 0.70 10.0 3.0
635 0.38 9.0 3.0 560 0.16 8.5 3.0
641 0.36 10.0 3.0 634 0.36 9.5 3.0
649 0.20 12.0 3.0 719 0.42 12.0 3.0
679 0.54 13.0 3.0 748 0.58 11.0 3.0
682 0.34 12.0 3.0 627 0.32 10.0 3.0
TOTAL 10.51
58 576 H 2.98 9.5 3.0 CFR 662 H 3.02 11.5 3.0 AEK
623 H 2.93 10.5 3.0 AEK 686 H 4.12 13.5 3.0 ADK
TOTAL 113.05
59)1) 555 H 0.68 8.5 3.0 lEK 666 H 0.42 11.0 3.0 AFK
584 H 0.76 9.5 3.0 AEK 683 H 0.34 12.5 3.0 BFK
653 H 0.88 11.0 3.0 AEK 718 H 0.91 8.5 3.0 AEK
658 H 0.42 11.0 3.0 AFK 739 H 1.23 12.5 3.0 BFK
TOTAL 5.64
59(2) 556 0.18 8.0 3.0 631 3.05 10.5 3.0
575 0.22 9.0 3.0 654 0.76 11.5 3.0
580 0.20 9.0 3.0 659 2.13 11.0 3.0
TOTAL 6.54









(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b ___ a b
60(1) 713 0.68 9.0 3.0 678 5.06 12.5 3.0
549 3.34 8.5 3.0 700 0.12 11.0 3.0
624 1.25 10.5 3.0 702 0.16 11.0 3.0
639 1.17 8.5 3.0 717 0.48 8.0 3.0
642 1.57 10.5 3.0 721 1.13 8.5 3.0
650 0.18 12.0 3.0 775 1.15 11.5 ,2.0
656 2.73 11.5 3.0
TOTAL 19.02
60(2) 554 0.60 8.5 3.0 770 0.48 10.0 2.0

TOTAL 1.08
60(3) 643 0.89 11.0 3.0 701 0.14 11.0 3.0
651 1.23 11.5 3.0 715 0.16 8.0 3.0
657 1.93 13.5 2.5 720 0.36 8.5 3.0
674 1.07 12.5 2.0 772 0.52 10.5 2.0
689 1.31 12.5 2.5
TOTAL 7.61
60(4) 553 0.22 8.5 3.0 669 0.12 11.0 3.0
664 1.35 11.5 3.0 741 0.52 9.0 3.0
665 0.80 12.5 3.0 771 0.44 10.5 2.0
685 2.07 12.5 2.5
TOTAL 5.52
61(1) 445 H 1.33 14.0 3.0 AEK 735 H 0.88 10.5 2.0 AFK
705 H 0.82 11.5 3.0 AFK 753 H 1.95 11.0 2.5 AFK
732 H 1.29 9.5 2.0 BEK
TOTAL 6.27
61(2) 684 2.89 12.5 3.0 709 0.91 10.5 3.0
574 0.18 9.0 3.0 726 1.23 8.5 2.5
672 0.46 12.0 3.0 733 0.80 10.0 2.0
703 0.94 11.5 3.0
TOTAL 7.41
61(3) 606 2.39 16.5 3.0 716 0.34 8.0 3.0
610 0.78 12.0 4.0 722 0.52 8.5 3.0
647 0.60 11.5 3.0 728 0.56 9.0 2.0
668 1.63 11.0 3.0 736 4.36 10.5 2.5
670 0.50 11.5 3.0 747 0.74 11.0 3.0
712 1.05 12.0 3.0
TOTAL 13.47
61(4) 566 0.50 9.0 3.0 707 1.27 12.5 3,0
633 0.87 9.5 3.0 708 0.20 10.0 3.0
638 2.11 9.5 3.0 724 0.36 8.5 3.0
648 0.46 11.5 3.0 742 2.51 9.5 3.0
697 0.50 11.0 3.0 913 1.45 15.5 2.0
698 1.75 13.0 3.0
TOTAL 11.98
61(5) 645 0.70 11.5 3.0 767 1.51 10.5 2.0
730 2.47 13.5 3.0OTAL
TOTAL 4.68
62(1) 681 H 4.48 12.5 3.0 AFK 745 H 3.88 9.5 3.0 CEK
690 H 0.84 13.5 3.0 AFK 746 H 1.45 10.5 3.0 AEK
704 S 1.85 11.5 3.0 AFK 729 H 1.23 9.5 2.5 BEK
723 H 0.36 8.0 3.0 EDK
TOTAL 14.09









(1) 97) (8) (9) (10) (11) (7) (8) (9) (10) (11)
Sa b a b
62(2) 692 0.74 14.0 3.0 727 0.32 9.0 2.0
245 0.20 9.0 3.0 725 0.34 8.5 3.0
582 0.20 9.0 3.0 752 1.13 10.5 2.5
691 1.37 13.5 3.0
TOTAL 4.20
64(1) 425 H 1.23 8.0 4.0 BEL 791 H 0.12 13.0 2.0 AFL
695 H 25.72 15.5 3.0 AFL 795 HES1 0.50 13.5 2.0 BFL
749 S3 1.89 12.5 3.0 AFL 797 H 1.13 12.5 2.0 EDL
750 H 5.69 11.5 2.5 AFL 880 S2 0.60 18.5 2.0 BFL
[ TOTAL 36.88
64(2) 239 2.57 13.5 3.0 737 2.39 15.5 3.0
495 0.08 8.0 4.0 796 0.32 13.5 2.0
562 0.14 8.0 3.0
TOTAL 5.50
65(1) 680 1.19 12.0 3.0 766 3.86 10.5 2.0
710 0.18 12.0 3.0 776 4.68 11.5 2.0
754 2.15 11.5 2.0
T OTAL 12.06
65(2) 563 0.20 8.5 3.0 757 1.99 11.5 2.0
743 0.66 10.0 3.0 O
S.TOTAL 2.85
65(3) 309 1.05 10.5 2.5 769 0.36 10.0 2.0
706 1.53 11.0 3.0 773 0.42 11.0 2.0
755 0.68 11.0 2.0
1 IrOTAL 4.04
66(1) 738 H 1.23 15.5 3.0 AFL 801 H 0.24 13.0 2.0 BEK
759 S 0.70 12.5 2.0 AFW 789 H 1.31 13.5 2.0 AEK
777 H 0.32 11.0 2.0 EEO 798 H 0.56 12.5 2.0 BEK
782 H 0.74 13.0 2.0 AEK 24 S 0.72 AFK
I OTAL 5.82
66(2) 316 1.25 12.5 2.0 764 2.89 11.5 2.0
317 0.18 13.0 2.0 788 0.32 13.0 2.0
696 1.05 11.5 3.0 793 0.18 13.0 2.0
731 0.64 9.5 2.0
I TOTAL 6.51
66(3) 765 1.01 11.0 2.0 792 0.18 13.0 2.0
TOTAL 1.19
67 660 H 2.47 14.5 2.0 AFL 794 H 0.32 13.0 2.0 BEK
781 H 1.79 12.5 2.0 AEK 799 H 0.30 13.0 2.0 BEK
783 H 3.26 12.0 2.0 CEK 997 H 7.72 18.5 2.5 NFL
790 H 0.24 13.0 2.0 BEK
SI __ OTAL 16.10
68 321 H 4.82 13.5 2.0 AHK 787 H 2.95 13.0 2.0 CIK
785 H 5.71 12.5 2.0 AHK
rOTAL 13.48
69(1) 403 1.73 15.5 2.0 828 0.48 15.0 2.0

TOTAL 2.21
69(2) ab 1.33 5.5 2.0 779 1.99 14.5 2.0

_OTAL 3.32









(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b __ a b
70 197 10.83 16.5 3.0 883 0.42 19.0 2.0
567 2.91 15.5 2.0 894 0.26 19.0 2.0
688 1.49 16.5 2.0 937 0.78 17.5 2.0
841 0.14 16.0 2.0 956 3.34 22.5 2.0
845 0.26 16.0 2.0 965 0.66 17.0 2.0
860 0.32 16.5 2.0 1000 0.42 15.0 2.0

TOTAL 21.83
71(1) 431 1.75 15.0 2.0 940 6.07 14.5 2.0
661 1.11 14.0 2.0 946 0.68 20.0 2.0
807 0.87 14.5 2.0 1001 0.30 15.0 2.0
873 1.79 18.5 2.0 834 0.42 15.0 2.0
884 0.40 1u.5 2.0
TOTAL 13.39
71(2) 502 H 0.72 14.5 2.0 AEK 837 H 4.48 15.5 2.0 AFK
809 H 0.22 14.0 2.0 EEK 882 H 0.48 18.5 2.0 BDK
820 H 0.64 14.0 2.0 EEK 915 H 0.80 16.5 2.0 AEO

TOTAL 7.34
71(3) 768 0.80 14.5 2.0 917 1.21 17.0 2.0
872 0.30 18.0 2.0 947 2.27 20.5 2.0
874 0.22 18.0 2.0
TOTAL 4.80
71(4) 758 1.95 14.5 2.0 876 0.26 18.0 2.0
852 0.56 17.5 2.0
TOTAL 2.77
71(5) 583 2.19 23.5 2.0 824 0.56 1 5.0 2.0
611 0.50 18.0 2.0 912 4.48 10.5 2.0
806 0.40 13.5 2.0 916 0.30 17.0 2.0

TOTAL 8.43
72 523 H 1.33 16.5 2.0 AFO 810 H 0.32 14.0 2.0 BEK
667 H 0.80 14.0 2.0 AFK 853 H 1.01 16.0 2.0 AFL
694 H 0.60 14.5 2.0 AFN 877 H 0.52 18.5 2.0 EFK
760 H 1.47 14.5 2.0 AFO 905 H 0.52 18.5 2.0 AFK
774 H 1.35 14.0 2.0 AFO
SII TOTAL 7.92
73(1) 426 0.60 19.5 2.0 856 1.29 16.5 2.0
578 4.56 17.5 2.0 888 0.12 19.5 2.0
734 3.58 16.5 2.0 963 0.32 17.5 2.0
763 2.01 12.5 2.0 972 0.12 17.0 2.0
778 0.30 11.0 2.0 990 0.18 18.5 2.0
839 0.10 15.5 2.0
TOTAL 13.18
73(2) 483 2.77 23.5 2.0 866 0.44 16.5 2.0
652 2.57 17.5 2.0 875 1.79 18.5 2.0
762 0.50 13.0 2.0 881 0.84 17.5 2.0
831 0.12 14.5 2.0 952 0.68 17.0 2.0

TOTAL 9.71
73(3) 644 0.42 18.5 2.0 859 0.78 16.5 2.0
761 2.25 12.5 2.0 879 3.56 17.5 2.0
822 0.22 14.5 2.0 896 0.34 19.5 2.0
TOTAL 7.57










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b __ a b
74 193 H 6.61 16.5 2.0 AFK 978 H 2.59 19.5 2.0 AFK
812 H 0.16 14.0 2.0 BDK 980 H 0.28 19.0 2.0 AFK
865 H 0.28 16.0 2.0 FFK 989 H 1.27 18.5 2.0 AFK
892 H 1.99 21.0 2.0 ADK 992 H 0.30 18.0 2.0 BFK
974 H 1.99 20.5 2.0 AFK TOTL
TOTAL 15.47
75(1) 493 4.70 16.5 2.0 977 1.49 19.0 2.0
826 4.88 15.5 2.0 983 0.18 19.0 2.0
832 0.20 15.0 2.0 995 1.79 17.5 2.0
908 1.15 19.5 2.0 998 2.19 18.0 2.0
TOTAL 16.58
75(2) 401 0.40 18.0 2.0 886 0.60 21.0 2.0
803 0.32 14.0 2.0 891 0.97 19.5 2.0
811 0.32 13.5 2.0 934 0.42 17.5 2.0
814 0.12 13.5 2.0 964 0.34 21.5 2.0
823 0.40 15.5 2.0 975 1.39 19.5 2.0
827 0.60 15.5 2.0 976 1.27 19.5 2.0
842 0.34 16.5 2.0 981 0.58 19.0 2.0
TOTAL 8.07
75(3) 984 0.34 19.0 2.0 993 0.30 18.5 2.0

TOTAL 0.64
75(4) 818 0.32 14.0 2.0 833 0.28 15.0 2.0

__ TOTAL 0.60
75(5) 817 0.46 14.0 2.0 903 3.30 19.0 2.0
399 1.01 17.0 2.0 919 1.73 16.5 2.0
815 0.16 14.0 2.0 985 0.16 19.0 2.0
830 0.76 14.5 2.0
TOTAL 7.58
75(6) 400 2.15 17.5 2.0 986 0.28 18.5 2.0
816 0.14 14.0 2.0 994 0.30 18.0 2.0
819 0.38 14.0 2.0
TOTAL 3.25
75(7) 805 0.38 13.0 2.0 862 0.26 16.0 2.0
844 0.28 16.5 2.0
TOTAL 0.92
75(8) 590 0.76 15.5 2.0 850 0.48 17.0 2.0
655 1.39 17.5 2.0 863 0.28 16.0 2.0

TOTAL 2.91
77 632 H 4.84 18.5 2.0 AFK 951 H 1.51 17.5 2.0 AFK
813 H 0.28 13.5 2.0 BDK 960 H 1.73 20.5 2.0 AFK
864 S 0.08 16.0 2.0 EFK 961 H 2.75 12.5 2.0 AFK
895 H 0.26 19.0 2.0 PEK 988 H 0.28 18.0 2.0 AFK
TOTAL 11.73
78 918 H 6.31 18.5 2.0 AGK OTAL
IItOTAL 6.31









(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b __a b
79 898 0.91 19.5 2.0 907 0.44 18.5 2.0
740 1.57 14.0 2.0 962 0.89 22.5 2.0
804 0.91 13.0 2.0 971 2.17 20.5 2.0
843 1.55 17.0 2.0 987 2.39 20.0 2.0
849 0.38 17.0 2.0 36 1.41
TOTAL 12.62_
80(1) 857 H 0.26 17.0 2.0 EEK 966 H 0.52 21.0 2.0 AFK
861 H 0.28 16.0 2.0 BEK 979 H 1.53 19.5 2.0 AFK
959 H 1.63 16.5 2.0 AFK 996 H 0.02 17.5 2.0 AFK

-I TOTAL 4.24
80(2) 333 3.21 18.5 2.0 967 1.23 21.0 2.0
848 0.28 16.5 2.0 982 0.60 19.0 2.0
909 0.62 19.5 2.0 991 0.44 18.0 2.0
941 0.52 17.5 2.0
TOTAL 6.90
81(1) 846 0.66 16.0 2.0 914 2.45 16.5 2.0
851 3.12 17.5 2.5 945 0.99 20.5 2.0
910 4.46 18.5 2.0
TOTAL 11.68
81(2) 970 0.95 20.0 2.0 911 2.63 18.5 2.0
847 0.28 16.0 2.0
1 TOTAL 3.86
82 838 H 0.84 14.5 2.0 BEK 948 H 6.91 21.5 2.0 CJK
904 H 10.88 20.5 2.0 AFK
TOTAL 18.63
83 973 1.31 20.5 2.0 900 0.76 20.5 2.0
521 1.47 24.0 2.0 999 1.11 15.0 2.0

TOTAL 4.65
84(1) 334 H 1.69 20.0 4.0 AFL 906 H 0.85 19.0 2.0 AFK
714 S1 0.91 14.5 2.0 AFK 926 H 0.46 22.0 2.0 AFO
871 H 0.66 17.5 2.0 BFO 944 S2 1.71 21.5 2.0 AFO
885 H 1.63 18.5 2.0 BJU 969 H 0.30 18.0 2.0 BFO
901 H 4.24 2.5 2.0 AFK
TOTAL 12.45
84(2) 889 1.03 21.0 2.0 878 0.72 8.0 2.0
322 3.10 13.5 3.0 893 0.44 19.0 2.0
663 1.21 14.5 2.0 942 1.37 22.5 2.0
821 0.26 14.5 2.0
TOTAL 8.13
85 170 2.05 20.5 2.0 571 0.24 9.0 3.0
354 0.95 20.0 2.0 902 1.23 21.5 2.0
TOTAL 4.47
86 482 1.87 23.0 2.0 887 1.23 19.0 2.0
536 0.97 23.5 2.0 899 2.19 20.5 2.0
687 1.87 15.5 2.0 920 1.35 22.5 2.0
800 0.32 13.0 2.0 943 1.19 21.5 2.0
802 0.42 13.5 2.0 953 2.67 23.0 2.0
825 0.48 15.5 2.0O
tOTAL 14.56










(1) (7) (8) (9) (10) (11 (7) (8) (9) (10) (11)
a b __a b
87 486 1.37 23.5 2.0 890 0.26 19.0 2.0
780 1.11 12.5 2.0 955 1.01 22.5 2.0
784 0.32 12.0 2.0 4.07
TOTAL 4.07
88(1) 535 1.35 24.5 2.0 870 0.64 17.0 2.0
786 0.54 12.5 2.0 924 0.76 21.5 2.0
835 1.63 15.5 2.0 930 0.36 23.0 2.0
855 0.60 17.5 2.0 950 5.02 20.5 2.0
TOTAL 10.90
88(2) 581 H 0.93 23.5 2.0 AEK 925 H 0.36 22.0 2.0 AEK
829 H 0.40 15.5 2.0 PDE 929 H 1.49 22.5 2.0 AFK
836 S 0.12 15.5 2.0 ADI 931 H 0.36 23.0 2.0 AFK
867 S 0.80 17.5 2.0 BDP 933 S 1.37 23.5 2.0 AEK
868 H 0.32 17.0 2.0 EDR 949 H 1.59 19.5 2.0 AFK
897 H 0.76 19.5 2.0 BED 968 H 1.23 21.0 2.0 AFK
TOTAL 9.73
89 458 H 1.75 4.5 4.0 AFM 935 H 0.80 24.0 2.0 AFK
516 H 0.40 7.0 4.0 BEF 954 H 1.33 22.5 2.0 AFK
869 H 0.26 17.0 2.0 BED 958 H 0.72 22.5 2.0 CFM
932 H 1.07 23.5 2.0 AFK
TOTAL 6.33
90(1) 927 0.52 22.0 2.0 854 0.28 18.0 2.0
525 3.18 22.5 2.0 858 0.34 17.0 2.0
550 0.85 26.0 2.0 921 0.60 22.0 2.0
573 1.91 24.5 2.0 938 2.23 23.5 2.0
TOTAL 9.91
90(2) 928 1.33 22.5 2.0 577 1.41 24.0 2.0
364 0.34 17.0 2.0 840 0.24 16.0 2.0
397 0.18 24.0 2.0 939 1.23 23.5 2.0
572 0.40 25.0 2.0 957 0.36 22.5 2.0
TOTAL_ 5.49
91 475 0.89 23.0 2.0 922 0.74 22.0 2.0
473 0.80 23.0 2.0 923 0.50 22.0 2.0
551 1.03 25.5 2.0 936 0.50 24.5 2.0
630 0.66 17.5 2.0 TO L
TOTAL 5.12
92 494 0.34 8.0 4.0 112 1.15 9.0 6.0
497 0.14 8.0 4.0 448 1.33 6.5 3.0
50 0.65 1.0 1.5 520 0.38 8.0 3.0
TOTAL 3.99
93(1) 153 H 0.26 5.0 6.0 AFK 336 H 2.21 5.5 6.0 AFK
269 H 2.19 3.5 8.0 AFK 533 H 2.69 6.5 3.0 EDK

TOTAL 7.35
93(2) 141 0.56 7.0 6.5 152 1.35 5.5 6.0
146 1.05 6.5 7.0 325 0.16 7.0 3.0

___ _OTAL 3.12


Grand Total = 1329.32 acres.









APPENDIX D


HANWA
In the following tables gandu numbers 1 to 66 are located in the central
village and 67 to 80 are situated in the unguwa.


Table D1.


Number of residents and labour units according to gandu.
Hanwa, June 1966


(1) ( [2) (3) 1 (4) (5) (6)1 (1) (2) (3) (4) (5) (6)


1
4
5
6
7
8
9
10
11
12
13
14
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42


17


30
6
38
11
13
9





26
14
4


39
29
3
12





2
19
31

34
15


r


5.75
4.75
4.50
6.00
1.75
4.00
8.00
5.00
4.25
5.25
9.50
4.00
10.25
8.50
6.25
5.00
3.50
7.25
4.25
12.75
10.00
4.25
4.50
3.25
5.50
8.50
9.25
3,25
4.50
9.75
7.50
3.50
3.25
16.75
4.00
4.25
10.50
5.50
4.00


3.5
2.5
3.0
3.0
1.0
2.5
5.0
3.5
2.0
3.0
5.0
2.5
6.5
4.0
4.0
3.5
2.0
5.0
2.0
9.0
7.0
2.0
3.0
2.5
2.5
5.5
5.5
2.5
3.0
4.5
4.5
2.0
2.5
10.0
2.5
2.0
7,5
4.0
2.5


1.75
1.50
1.75
1.50
0.50
1.25
3.00
2.50
1.50
1.75
3.00
2.50
3.50
4.00
3.00
1.50
1.00
5.00
1.00
5.00
3.75
1.00
1.50
1.50
1.75
2.75
4.00
2.50
1.00
2.50
2.50
2.00
1.50
5.50
0.50
1.00
5.50
2.00
0.50


3.50'
5.00
1.75
2.75
5.50
6.50
4.25
3.75
4.50
5.25
3.50
10.25
1.75
3.75
4.75
6.00
0.00
3.75
2.50
3.00
2.75
2.75
4.75
6.75
5.25
2.50
2.75
4.00
2.25
5.75
9.50
7.00
5.50
5.75
4.25
6.50
3.50
7.50


2.0
3.5
1.0
2.0
2.5
5.0
3.5
3.0
3.0
3.0
2.0
6.5
1.0
3.0
1.0
4.5
1.0
1.5
1.0
1.5
2.0
0.5
2.5
4.5
3.0
1.0
2.0
2.5
1.5
3.5
5.0
4.0
2.5
3.5
3.5
3.5
2.0
4.5


77


-- I


1,00
2.00
1.00
1.00
2.50
5.00
1.50
2.00
3.00
1.00
2.00
2.50
0.50
1.00
0.50
3.50
1.00
1.00
1.00
0.50
1.00
0.50
1.50
4.50
3.00
0.00
2.00
1.50
1.50
2.00
4.00
2.00
1.25
2.00
2.50
2.75
1.25
2.75


--









Table D2.


Distribution and description of fields according to gandu
farming them. Hanwa, 1966


(1) (7) (8) (9) (10) (11)i (7) (8) (9) (10) (11)
a b a b
1 42 H 0.37 2.0 8.0 AEK 205 H 2.35 15.5 7.0 AGO
43 H 1.60 2.0 6.0 AEK 290 H 1.68 16.5 7.0 AGO
OTAL 6.00
2 Included in Compound 1
3 Included in Compound 5
4 8 H 0.50 3.0 8.0 AEK 178 H 3.87 11.5 7.0 AEK
10 H 1.01 3.0 8/1 ADK 184 H 1.85 12.5 7.0 AEO
TOTAL 7.23
5 298 H 0.17 2.0 8/1 AEK 7 H 1.73 3.5 8/1 AGK
174 H 3.02 9.5 6.0 ADK
TOTAL 4.92
6 40 H 1.34 2.0 6.5 AEK 202 H 1.73 15.5 7.0 AEO
146 E 0.50 3.0 5.0 AEK 124 F 0.39 5.0 4.0 ADO
185 H 2.86 10.5 7.0 AEO
TOTAL 6.82
7 16 1.14 2.0 1.0 AEK 192 1.29 10.5 7.0 AEO
,_ __ I ____ETOTAL 2.43
8 72 1.51 2.5 4.0 AEK 297 4.37 11.5 7.0 AEO
194 5.04 12.5 7.0 AEO
TOTAL 10.92
9 48 H 1.04 3.0 6.0 AEK 173 H 4.29 10.5 6.0 AEO
57 H 0.71 2.0 4.0 AEK 181 H 3.02 12.5 7.0 AEM
122 B 1.93 5.5 4.0 AEK 210 H 2.23 13.5 7.0 AEO
TOTAL 13.23
S 10 213 2.10 13.5 6.0 AEO
TOTAL 2.10
11 6 0.50 3.0 8.0 AEK 180 3.70 11.5 7.0 ADK
53 0.17 2.0 4.5 AEM 203 2.94 16.5 7.0 AEO
177 2.91 11.0 7.0 ADK
S __ TOTAL 10.22
12 18 H 0.50 2.0 8/1 AEK 196 H 1.34 12.5 7.0 AEO
195 H 1.97 10.5 7.0 AEO
TOTAL 3.81
13 j 61 S 0.84 3.0 5.5 ADK 156 H 0.39 6.0 5.0 BEO
68 H 3.16 2.5 5.0 BEK 167 H 0.92 4.0 5.5 AEO
148 H 0.72 4.0 5.0 BDK 171 H 3.78 6.5 5.0 AEN
S ___OTAL 9.81
14 22 H 1.50 2.0 1.5 AEK 301 H 0.13 2.0 5.0 EDO
70 H 0.08 2.0 5.0 EDO 301 H 0.25 2.0 5.0 CDO
139 H 0.60 4.0 4.5 ;CDO 303 H 0.97 8.5 5.0 EDO
i j (OTAL 3.53
15 __Included in Compound 16
16 17 H 0.84 2.0 8/1 AEK 216 H 7.70 12.5 6.5 ADN
34 H 1.63 3.0 7.0 ADN 38 S 1.34 2.0 7.5 AEK
HA TOTAL 11.51










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b __ Ea b_
17 54 H 1.09 2.0 5.5 BDK 249 F 0.20 8.5 3.0 AEO
157 H 6.25 6.5 5.5 AEK 256 F 0.12 7.0 3.0 EDO
160 F 0.34 6.0 6.0 AEK 282 S 0.30 7.5 3.0 AEO
TOTAL 8.30
18 158 H 0.13 7.0 6.0 ADO 294 IH S 2.27 8.5 5.0 AFO
159 S 0.22 7.0 6.0 ADO 305 H 0.67 7.0 5.5 ADO
168 H 0.67 3.0 6.0 ADK 284 S 0.76 7.5 6.0 AEO
170 H 3.76 7.5 5.0 ADK
__ OTAL 8.49
19 Has no farm
20 4 0.94 4.0 8.0 AEK 277 0.59 5.5 2.0 AEP
5 1.01 4.0 8.0 ADK 313 0.25 7.5 3.0 AEO
OTAL 2.79
21 35 1.90 3.5 6.5 AGO 164 0.45 5.0 6.0 BDN
46 1.34 3.5 6.0 CGO 223 4.57 6.5 4.5 AEO
58 1.60 2.0 4.5 AEO
TOTAL 9.86
22 90 0.07 3.0 2.5 AEO 136 0.34 3.5 4.0 EDO
99 0.52 4.5 3.0 AEO 279 0.13 6.0 2.0 AEP
TOTAL 1.06
23 52 B2 1.01 2.0 4.5 AEK 101 N2 0.50 2.5 3.0 AEK
75 H 0.62 2.5 4.0 AEK 109 N1 1.09 4.5 3.5 AEK
76 H 0.17 3.0 4.0 EDO 123 N1 1.14 4.5 4.0 AEO
300 SL 0.12 2.6 3.0 AEK 258 SL 0.20 7.0 3.0 EDO
85 El 1.51 2.0 2.5 AEK 247 H 0.76 8.5 3.0 AEO
88 B2 0.12 2.0 2.0 BDK 153 H 1.68 5.5 4.0 AEO
130 SL 0.17 2.5 2.5 BDK 138 SL 0.34 4.5 4.0 ADK
94 SL 0.67 4.5 2.5 AEO 55 N1 0.25 3.5 4.0 ADO
TOTAL 10.35
24 19 H 0.55 2.0 1.0 AEK 197 H, S 7.65 12.5 7.0 AEO
41 ItS 1.29 2.0 7.5 AEM 198 H,S 4.20 15.5 7.0 AEO

TOTAL 13.69
25 37 H 1.18 2.0 7.0 AEK 182 H 4.45 12.5 7.0 ADM
175 H 1.68 10.5 6.0 ADM
I I TOTAL 7.31
26 176 5.88 10.5 6.5 AEK 179 6.99 12.5 7.0 AEK

TOTAL 12.87
27 14 1.23 2.0 8/1 AEK
S-- TOTAL 1.23
28 13 H 2.47 2.0 8.0 AEK 293 H 6.86 12.5 6.0 AGO
209 H 8.24 14.5 6.5 AGO
TOTAL 17.57
29 207 H 1.68 15.0 6.5 AFO 306 B1 1.00 12.0 7.0 AEO
200 B2 3.70 16.5 7.0 AEO 165 H 0.89 4.5 6.0 EDO
204 H 0.54 16.0 7.0 AEO 307 H 0.67 6.0 8/1 EDK
287 H 3.87 9.5 8.0 AGO 271 B2 0.76 13.0 6.0 ADO
51 H 1.68 2.0 5.5 AGK 270 H 0.59 13.0 6.0 AEO
___ TOTAL 15.38










(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
Sa b I a b
30 39 H 1.51 2.0 6.5 AEK 308 H 0.17 6.0 8/1 ADO
199 H 3.19 16.5 7.0 AEO 309 H 0.92 5.0 5.5 BDO
211 H 3.70 14.5 6.0 AJO 310 H 0.81 10.5 8/1 AEO
2 H 4.34 7.5 8/1 AGO 268 H 1.26 10.5 8.0 AEO
I_ TOTAL 15.90
31 20 H 1.51 2.0 1.5 AEK
TOTAL 1.51
32 23 1.39 2.0 2.0 AEK
TOTAL 1.39
33 25 0.42 3.0 2.0 ADO 234 1.76 7.0 4.0 AFN
299 1.01 4.0 2.0 AGO 236 6.22 7.5 4.0 ADN
-2 28 1.31 4.5 2.0 AGO 239 2.69 7.5 3.5 ADN
89 0.67 2.5 2.0 AGO 251 1.48 8.5 3.0 AGO
110 0.40 4.0 4.0 BDK 255 0.08 7.0 3.0 BDP
118 1.44 5.5 4.0 AEK 254 0.17 7.0 3.0 EDP
121 0.92 6.0 4.0 AEO 86 0.92 2.0 2.5 AEK
TOTAL 19.49
34 9 1.24 2.5 8/1 AEK 206 9.97 15.5 7.0 AEK
+2 TOTAL _11.21
35 91 0.50 3.0 2.5 AEK 259 0.10 7.0 3.0 BDK
TOTAL 0.60
36 27 H 1.09 4.0 2.0 AEP 116 H 0.50 5.0 3.5 BDO
33 H 1.63 3.0 2.0 CEP 314 H 0.92 5.0 4.0 AGO
79 H 1.85 3.5 3.5 AEM 78 H 0.20 3.0 4.0 BDO
TOTAL_ 6.19
37 21 B1 0.17 2.0 1.5 AFO 253 H 0.45 7.5 3.0 AEK
30 B2 1.18 5.5 2.0 AEP 257 H 0.08 7.0 3.0 BDP
83 B1 0.12 2.0 3.0 AEK 262 H 3.26 7.0 3.0 AEP
92 H 0.25 3.0 2.0 AEP 265 B1 3.36 6.5 3.0 AFP
111 H 0.50 4.0 3.5 BDO 276 B2 0.60 5.0 2.0 AFP
137 N 0.71 3.5 4.0 BDO 311 H 0.55 8.0 3.0 AEP
I TOTAL 11.23
38 77 H 0.17 3.0 4.0 BDO 102 H 0.47 3.0 3.0 CEK
84 S 0.20 2.0 3.0 AEK 131 H 0.50 3.5 4.0 ADK
93 S 1.76 3.5 2.5 AEKOTAL
TOTAL 3.10
39 3 5.55 7.5 1.0 ADP 296 0.18 3.0 1.0 EDP
295 3.02 5.5 1.0 AFP
TOTAL 8.75
40 95 S1 0.84 4.5 3.0 AEO 243 C 0.34 6.5 3.0 AEO
133 H 0.44 3.5 4.0 BDO 252 S2 0.89 8.0 3.0 AEK
134 H 0.72 3.0 4.0 BDO 260 S2 0.67 7.0 3.0 AEK
224 S2 1.63 6.5 4.0 AEN 150 H 1.34 4.5 5.0 AFO
SOTAL 6.87
41 228 H 1.60 7.5 4.0 AEN 237 S 0.50 6.0 3.5 AEK
235 H 1.51 6.5 4.0 AEO 283 H 0.39 9.0 3.0 BDP
T_ T_____ OTAL 4.00
42 Has no farm









(1) (7) (8) (9) (10) (11) (7) (8) (9) (10) (11)
a b a b
43 26 H 0.34 3.5 2.0 ADO 113 F 0.34 4.0 3.0 BDO
74 F 0.12 2.5 4.0 BDO 226 H 1.34 6.5 4.0 AJO
98 F 0.84 3.5 3.0 ADO 278 F 0.07 6.0 2.0 AEP
112 F 0.03 4.0 3.5 BDO 288 H 0.76 5.0 2.0 AEO
S__T OTAL _3.84
44 31 H 3.58 5.5 1.5 AEP 315 S 1.01 12.5 8/1 ADP
316 S 0.92 11.0 1.0 ADP
TOTAL 5.51
45 128 0.20 3.5 & EDO
4 _TOTAL 0.20
46 229 H 1.48 7.5 4.0 ADN 322 H 0.42 9.0 5.0 AFO
292 H 0.74 9.5 4.5 AFN 323 H 0.30 9.5 3.0 EDK
TOTAL 2.94
47 24 0.20 2.5 2.0 EDK 97 0.42 3.0 3.0 AEK
56 0.84 2.0 4.5AEK 104 0.03 3.0 3.0 BDK
82 0.54 2.5 3.0 AEK 114 0.67 4.0 3.0 AEK
269 0.08 2.0 3.0 AEK 129 0.34 3.5 4.0 ADN
87 0.34 2.0 2.5 BDK
TOTAL 3.46
48 117 H 0.67 5.0 4.0 DM 246 H 0.47 9.0 3.0 BDK
126 H 2.23 4.5 4.0 CDN 286 S1 2.49 6.0 2.0 ADO
172 H 2.86 7.5 5.0 AFK 232 31,S 3.58 7.5 4.0 CDO
233 H 2.44 8.5 5.0 AFM
____ TOTAL 14.74
49 Has no farm
50 312 H 0.55 2.5 3.0 AEO 225 H 0.47 6.5 4.0 AEO
TOTAL 1.02
51 142 0.67 3.0 5.0 BDO 275 0.59 5.0 2.0 ADP
144 0.67 3.0 5.0 BDN
T____OTAL 1.93
52 244 1.31 7.0 3.0 AEO 274 0.25 5.0 2.0 ADP
261 0.22 6.5 3.0 AEP 285 0.07 6.0 2.0 ADP
TOTAL 1.85
53 81 0.84 2.5 3.5 ADO 107 0.54 4.5 3.0 ADP
12 0.50 4.5 4.0 ADP 120 0.34 6.04.0 ADO
106 0.13 4.0 3.0 ADP 231 0.29 7.0 4.0 ADO
TOTAL 2.64
54 100 1.51 4.5 3.0 AGP 163 1.80 6.0 6.0 ADK
+5 132 1.18 3.0 4.0 CDO
TOTAL 4.49
55 272 1.83 5.0 3.0 AHP
TOTAL 1.83
56 29 1.01 5.0 2.0 AHP 32 0.34 4.0 2.0 ADP
TOTAL. 1.35
57 281 H 0.08 2.0 4.0 ADK 273 H 0.34 5.0 3.0 ADP
250 H 2.52 8.5 3.0 CDP 317 H 0.25 7.0 3.0 AEP
TOTAL 3.19
58 69 H 0.12 2.0 4.0 kDK 264 H 0.67 6.5 3.0 ADP
263 H 1.34 7.0 3.0 CDPL
OTAL59 Has no farm2.13
59 I Has no farm









(1) (7) (8) (9) ( (10) (11) (7) (8) (9) (10) (11)
I__a b a__ b '
60 240 1.11 6.5 3.5 ADO 241 0.50 6.0 3.0 ADO
TOTAL 1.61
61 238 1.26 7.5 4.0 BDN
TOTAL 1.26
62 96 H 1.18 3.0 3.0 ADO 324 H 0.29 7.0 4.0 ADO
105 H 0.50 4.0 3.0 AEN
S __TOTAL 1.97
63 80 H 1.18 3.0 3.5 ADO 242 H 0.17 6.5 3.0 AEO
TOTAL 1.35
64 _Has no farm
65 103 0.84 3.0 3.0 BDK 248 2.10 8.5 6.0 AEO
S108 3.19 4.5 3.5 AEK 245 1.31 7.5 3.0 AGK
i TOTAL 7.44
66 115 0.18 5.0 3.5 AGK 230 3.02 7.5 4.0 AEO
119 1.68 5.5 4.0 AEO 267 0.84 5.5 3.0 AEP
125 0.59 5.0 4.0 AEO 280 4.37 7.5 4.0 CGR
TOTAL 10.68
67 44 0.34 3.0 6.0 ADO 152 3.70 4.5 4.5 AEO
71 1.68 2.5 4.5 ADO 154 2.02 5.0 5.0 AEN
2 140 1.09 3.5 4.5 ADO 222 1.43 6.5 5.0 AEO
Ha n TOTAL 10.26
68 1 Has no farm
69 226 0.06 2.0 6.0 AEO
TOTAL 0.06
70 11 0.67 2.5 8/1 AEK 145 1.26 3.5 5.0 BEK
TOTAL 1.93
71 12 0.84 2.0 8.0 AEK 143 0.84 3.5 5.0 BDK
TOTAL 1.68
72 1 H 1.74 8.0 8/1 DO 169 H 0.50 2.5 6.0 AEK
50 C 0.02 2.0 6.0 AEK 208 H 1.18 14.0 7.0 AEO

73 49 0.54 2.5 6.0 AEK 151 1.68 4.5 5.0 AEO
59 0.84 4.0 6.0 AEN 218 4.20115.5 6.0 AGO
-3 60 0.25 3.5 5.5 BDO 219 1.18113.5 6.0 IGO
141 1.28 3.5 5.0 BGO 227 1.34 7.5 4.0 0FO
149 5.04 4.5 5.0 BDK 291 2.27113.5 6.0 AJO
I TOTAL 18.62_
174 45 H 1.51 3.5 6.0 AEO 161 H 0.42 6,0 6.0 AEK
47 S 0.47 4.5 6.0 AEN 189 H 1.86 9.5 7.0 AEN
65 S 0.08 3.0 5.0 AEK 214 H 2.86113.0 6.5 AEN
67 H 0.08 3.0 5.0 AEK 220 H 2.2311.0 7.0 AEN
135 H 0.50 3.0 4.5 BDK
___ TOTAL 10.01
75 147 0.34 3.0 5.0 ADK 193 5.51 11.5 7.0 ADO
+2 ITOTAL 5.85
76 62 H 0.08 3.0 5.0 ADK 186 H 2.72 9.5 7.0 AEO
162 H 0.64 6.0 6.0 AEK 212 H 1.80 13.5 6.0 IEO
183 H 5.04 12.5 7.0 AEO
S___ _TOTAL 10.28










(1) (7) (8) (9) a (10) (11) (7) (8) (9) (10) (11)
a b__ ___ a b
77 64 H 0.20 2.0 5.0 AEK 318 H 1.13 13.0 6.0 AEO
289 H 0.50 6.0 5.0 AEO 319 H 0.30 4.0 5.0 EDO
201 H 2.52 16.0 7.0 AEO 320 H 0.39 5.5 6.0 ADO
221 H 1.88 11.5 7.0 AEO
TOTAL 6.92
78 15 1.55 2.5 1.0 AEN 155 1.51 5.5 5.0 AEN
36 0.60 3.0 6.5 AEN 188 2.47 8.5 7.0 AEN
66 0.08 3.0 5.0 ADK 217 3.23 13.5 6.0 AEO
TOTAL 9.44
79 63 H 0.08 3.0 5.0 ADO 304 H 0.34 7.0 6.0 ADO
73 H 0.12 2.5 4.0 BDO 321 H 1.43 13.5 6.0 AJO
215 H 2.69 12.5 7.0 AEN 325 H 0.47 13.5 6.0 AEO
S_ TOTAL 5.13
80 166 H 0.84 5.0 6.0 ADO 190 H 1.55 10.0 7.0 ADO
187 H 1.31 9.0 7.0 ADO 191 H 3.02 10.5 7.0 ADO
TOTAL 6.72


Grand Total = 457.44 acres
+ These compounds are multiple gandaye. The number of
gandaye are shown beside the symbol.










APPENDIX E. GLOSSARY OF HAUSA TERMS


In the appendix are given definitions adopted for the Hausa wor:s
used in this report.
Un-uwa (pl. ungwoyi) =hamlet which is physically separated from
the central village or cluster.
Sassa = sections of.a compound separated by fences.
yai = an individual family which usually includes a man, his wives
and his dependent children
Gandu = (pl. gandaye) a work unit which is "a swperate unit of
domestic economy with common production and consump-
tion of food, a single head, a common pot, a common
granary and a common farm" (22, p. 19).
Suna ci daga tukunya daya = those persons eating from one pot.
Kulle = a type of purdah in which wives of Moslems are kept in
seclusion.
Gona = an upland field which can only support crops during the
rainy season.
Fadama = a lowland field or garden plot situated where the water-
table is high, e.g., near streams. With the help of
irrigation such fields will support crops throughout the
year.




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