Gender related aspects of agricultural labor in Northwestern Syria

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Gender related aspects of agricultural labor in Northwestern Syria
Series Title:
Conference on Gender Issues in Farming Systems Research and Extenion, University of Florida, February 26 to March 1, 1986
Rassam, Andree
Tully, Dennis
Place of Publication:
Gainesville, Fla.
University of Florida
Publication Date:


Subjects / Keywords:
University of Florida. ( LCSH )
Spatial Coverage:
Asia -- Syria -- Middle East

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Full Text

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Conference on



Andree Rassam and Dennis Tully
Famning Systems Program
ICARDA (International Center
for Agricultural Research in
the Dry Areas)
Aleppo, Syria

Paper presented
Gender Issues

at the conference on
in Farming Systems
and Extension

February 26-March 1, 1986
University of Florida
Gainesville, Florida


In rural Syria, men and women work in agriculture, mostly in

small farms. Mechanization of some tasks, new opportunities for

off-farm employment, and the increase of skilled rural jobs have

affected the division of labor between men and women and between

household and hired labor.

This paper draws on a survey of 47 landowning households in

four villages of Aleppo Province, Syria, supplemented by visits to

villages supplying labor. The labor market and opportunities for

men and women are discussed. Various factors are evaluated for

their effect on the choices to use male or female, household or

hired labor in crop and livestock production.



This study was supported in part by grants from the Ford

Foundation and the Population Council which are gratefully

acknowledged. Special thanks are forwarded to the organizers of

this conference for their financial support in realizing this

participation. Our appreciations to Dr. M.J.Jones for his helpful

comments and to Ms. Anna Maria Roumieh for having cheerfully typed

this paper.



It is well known that the development of technology is an

essential part of economic and social development (Cain, 1981).

It is also clear that technical changes can have far-reaching

effects on rural communities. Therefore, policy makers, donors

and agricultural research centers are giving greater attention to

socioeconomic factors in the design and extension of new

technologies. Of particular interest to this workshop are

gender-related issues.

New technologies may shift the sexual division of labor,

increasing men's or women's work loads, sometimes with negative

effects. They may also affect the balance of opportunities and

access to economic resources. One common pattern is for the

mechanization of tillage to reduce men's labor, since tillage is

often a male task. However, improved tillage or increased crop

area may lead to more crop production, which increases

post-harvest, female tasks (Spence and Byerlee, 1976; Nyanteng,


On the other hand, where new technology reduces women's

labor, this may have a negative effect if poor women depend on the

income from agricultural labor. In Java the introduction of rice

mills is said to have replaced 12 million female work hours (ILO,

1981), while herbicide use in Kenya has eliminated weeding as a

job opportunity for some rural women (UNGA, 1978).

Hand in hand with technical changes, a second major factor

affecting many rural populations is the development of off-farm

income opportunities. These are usually in urban areas and often

most available to males. Off-farm incomes can stabilize household

incomes and offset declining farm sizes; however, the absence of

adult males may increase the labor burden of women, children, and

old persons (Dasgupta, 1977; Nash, 1983; Tully, 1984).

Paradoxically, men's migration may reduce household women's and

children's labor if non-agricultural income satisfies household

needs. They may be replaced by hired labor if it is available, or

else a general labor shortage may develop. For example,

agricultural decline in Oman and Yemen has been related to

extensive labor migration (Birks and Sinclair, 1980).

Thus, data on the division of labor and income-generating

activities are becoming increasingly important in Farming Systems

Research. Labor issues need to be assessed, since they may limit

the adoption and diffusion of technological change (Somel, K. and

T. Aricanli, 1983). Studies by ICARDA's Farming Systems Program

have addressed gender-related issues (Nour, 1985). Gender issues

will also be considered in a new project on mechanization and

labor constraints in the Middle-East and North Africa, which will

be conducted in collaboration with national research

organizations. The results are expected to have implications for

research design, organization and priorities.


Syria is among those Middle Eastern countries where

agriculture is a major factor in the national economy. It is a

rich country with regard to its land and water resources.

Fundamental changes have occurred in the last thirty years, both

in technique and in the organization of production. New

technologies were rather quickly adopted in Syria. For example,

land preparation is almost completely done by tractor today and an

increasing percentage of harvesting, particularly of cereals, is

being mechanized. When cereal is hand harvested, virtually all is

threshed by standing mechanical threshers, rather than the

animal-drawn sled formerly used. Herbicides are used by the

majority of wheat farmers in wetter areas, and seed drills have

replaced broadcasting to some extent.

The organization of production has also changed tremendously

with the Agrarian Reform of the 1960s. Land was distributed in a

more equitable way to increase the number of small holdings.

Currently, three quarters of the holdings are less than 10

hectares, 24 percent of farms are from 10 to 100 hectares, and

fewer than 1 percent are more than 100 hectares (FAO, 1982). As

part of the reform, cooperatives and credit facilities were

organized to give farmers access to inputs and new technologies.

Although farms are small, agricultural production has shown

remarkable progress in recent decades. Agriculture's contribution

to GDP grew at a respectable 4.4% rate in the 1960s and at 7.2% in

the 1970s. Syria also increased its food production per capital by

68% during the 1970s, while most Middle Eastern countries have

been unable to increase food production at the rate of population

increase. However, the industrial sector and oil production have

grown faster than the agriculture sector, resulting in a decrease

of agriculture's relative importance in the national economy. The

percentage of the labor force in agriculture dropped from 53

percent in 1965 to 33 percent in 1983. The contribution of

agriculture to GDP decreased from 29 percent to 19 percent from

1965 to 1981 (World Bank, 1985).

Overall, rural development with the increase of agricultural

production, industrial labor demand (off-farm employment) and the

extension of new technology have affected the division of labor

between men and women and between household and hired labor. This

has also led, as will be shown later on, to a predominance of

women in the unskilled rural labor force while most of skilled

jobs within or outside rural areas are dominated by men.


This paper draws on a survey of 47 landowning households in

four villages of Aleppo Province in Syria, supplemented by visits

and interviews to major labor supplying villages.

Data were collected on farm labor for the production of crops

and livestock for the 1982/83 cropping season. Twelve households

were randomly selected from each of four villages located in

Northwestern Aleppo Province. Two villages, with approximately

450 mm mean annual rainfall, were selected in zone 1, where wheat,

barley, legumes and summer crops (melons, sesame, etc.) are grown.

Two other villages with approximately 325 mm mean annual rainfall

were selected in zone 2. The same patterns of crops are found

except that chickpea is not grown in zone 2. Data from the

households were collected at three different periods corresponding

to the different seasonal tasks. Both husband and wife were

present at each interview session, and information was collected

from both of them. Labor has been disaggregated by age and sex,

and household labor has been distinguished from hired labor. The

number of hours spent by each age and sex category has been

calculated for each task and each crop. (For more details on the

method used in the study, see Rassam, 1985.)


Labor input of agricultural tasks by gender, whether it is

provided by the household or hired labor, differs among crops and

the techniques used in accomplishing the tasks. Some tasks are

mostly carried out by males, particularly the mechanized

operations. Male tasks include land preparation, chemical weed

control, mechanical harvesting and threshing. Among manual tasks,

chemical fertilizer application and seeding are generally done by

males in the villages studied. Females' contribution in these

tasks usually consists in heTping; however, in some villages where

men are heavily involved in non-agricultural work, women may

broadcast seed or fertilizer themselves. Activities such as

spreading manure in the field, selecting seed, planting summer and

tree crops and hand weeding are normally done by females. Seed

preparation and the various steps in the harvest process seem to

be shared jointly by male and female labor although there is also

specialization by sex within the processes themselves. On the

other hand livestock activity is found to be divided between

males' and females' tasks. For example feeding livestock is done

mostly by household females, while herding animals is usually

carried out by household males. Shepherds from the villages and

children also contribute to this task. Selling sheep is a male

task while selling poultry is a female task. Dairy product can be

sold by either sex.

To simplify the presentation we omit the contribution of

children under the age of 13 (and usually over 10) who work

approximately 7 percent of labor hours. Their productivity in

major tasks, such as harvesting and weeding, is estimated by

farmers at about half that of an adult. Children tend to work

with their mothers, especially in hired labor; the correlation

between children's and adult women's hours in labor hired from

outside the village is 0.87. Henceforth, the percentages of

various categories of labor presented will be based on the total

adult labor hours.

In general males' and females' contributions to agricultural

labor (in terms of hours of physical work and including both

family and hired) are almost equally divided (Table 1). Household

labor provides 61 percent of the total workhours. Female provide

57 percent of household labor hours. On the other hand, hired

labor is equally divided by gender in the total agricultural


The work provided by each sex depends on the degree to which

the production is mechanized. For example, in cereal crops where

most of the operations are mechanized, the contribution of hired

males is higher than that of hired females (33 percent vs. 5

percent). The opposite is found in legume crops where most of

operations, mainly harvesting are not mechanized. Female's and

male's contributions are 36 percent and 12 percent respectively.

Tables 2 and 3 show the contributions of males and females by crop

and by activity as well as the proportions of hours devoted to

each task.

The cereal harvest is a good example of current trends,

because it is partly mechanized and partly manual, and both sexes

are involved in manual harvesting. Only one farmer manually

harvested the entire cereal area, but an additional 12 farmers

harvested some cereal by hand, so it is possible to make a

comparison between groups by technique (Table 4). Even when the

cereal is combined harvested, there is also associated hand

labour, primarily gathering up the straw for use as feed.

In households which hand harvest part or all of their

cereals, there is more work for both males and females, but

especially females. Thisvalso true for hired labor; the male

contribution is not significantly different for hand and

mechanical harvesting, but the female contribution is much higher

where hand harvesting is done. Interestingly, while mechanization

decreases the female proportion of total labor in this task, it

does not significantly affect the female proportion of household

labor. The mechanical operations are largely done by hired

persons, and thus do not affect the household ratio. The mean

female proportion of hired labor is extremely small where

harvesting is done by combine.

Thus, mechanization of the cereal harvest substantially

reduces female labor inputs, from a mean of 180 hours per family

to a mean of 51. This is in spite of larger crop areas associated

with combine harvesting. Approximately half of the reduction

comes from household labor, while the other half comes from hired

labor. The amount of hired male labor, on the other hand, is not

significantly affected by mechanization.


In this section we will be describing the gender differences

in off-farm activities, whether these activities are carried out

for agricultural or non-agricultural tasks. The discussion will

be divided into two parts. Emphasis firstly will be placed on the

four survey villages, with few landless families; then villages

will be discussed with a higher percentage of landless households.

Working off-farm depends largely on farm size, the crop

productivity, and access to work opportunities. In the survey

villages, 63 percent of income comes from crops and livestock vs.

37 percent from off-farm activities. Thus farming is the most

important activity. Even so, there is a difference related to the

productivity of agriculture. Off-farm income provides only 29

percent of income in the wetter two villages (zone 1) compared to

44 percent in the drier less productive area (zone 2). In fact

working outside the village is more frequent in the drier

villages; from the 24 households in zone 2, 42 percent of the

family heads work in non-agricultural activities compared to 22

percent in zone 1. The farmers from zone 2 usually work as

labourers, mainly in the construction industry. The off-farm

activities of zone 1 farmers consist of running a business in the

village, driving a taxi or teaching in the village school.

No women from the four survey villages work in

non-agricultural activities outside the village. A few women work

off-farm, but their tasks consist of agricultural labor within the

villages, mainly planting summer crops or harvesting legume crops.

Their work is limited to a few days per year, and is not an

important component of household income.

By contrast, in many villages having less land, agricultural

labor, especially by women, is a major operation Men in such

villages mostly pursue off-farm activities, while the women work

more in agricultural labor. For example, in one village of 5000

people, 37% of the households are landless. Approximately 300 men

commute 50 km to Aleppo every day to work as labourers in a

government construction company. Another 100 men and some women

work in construction in the village, while others work driving

tractors, pickup trucks, etc. Approximately 300 women work

regularly in agricultural labor, as well as about 100 men,

(usually either unmarried young men or old men). By combining

planting summer crops, weeding, and harvesting of various crops,

approximately six months of work are provided over the course of

the year. This source of income is not as regular or as well-paid

as urban work, but it clearly forms a larger portion of household

income than in villages with more land.

The overall pattern of labor input by sex has been presented.

Beyond this, we have attempted to explain patterns of variance

within the data, particularly to determine factors affecting the

male and female labor inputs, and the relative importance of

household and hired labor. The following analysis is restricted

to hours spent in crop production.

The most important variable affecting all labor categories is

holding size. Total land area has a strong and significant linear

correlation with all categories of labor, including male household

(r=.66), female household (r=.56), male total (r=.86), female

total (r=.77), hired total (r=.84), and total labor (r=.85). Thus

all categories of labor increase with higher land areas.

In view of the strong effect of this variable, it is not

surprising that there are also significant correlations among the

labor variables, such as total male labor with total female labor

(r=.83) and household with hired labor (r=.41). As requirements

increase, men and women both increase their labor and hire more

labor as well. It is interesting to note that the female

proportion of hired labor is negatively correlated both with

household labor (r=-.29) and with the female proportion of

household labor (r=-.29); this bears out the point that female

labor is hired mostly for manual jobs that can be carried out by

unskilled family members if they are available.

Because of the strong effect of holding size, in considering

other variables it is essential to consider land simultaneously.

For example, where the male head of household has a steady job,

this appears to have a strong effect on labor inputs, with male

household labor hours averaging 406 if he has no job and 136 if he

does. Large differences in means are found for other labor

variables as well.

However, households with jobs hold an average 10 ha compared

with 19 ha for those without. That is, on farms with small

holdings the male head of household is more likely to seek

off-farm work. When holding size is entered into the analysis of

variance as a covariate, there are no significant differences in

any labor variables between families where the male head has a job

and those where he has not.

However, other factors besides holding size do have an effect

on labor allocation, primarily demographic variables but also

ecological zone. Using multiple linear regression, five variables

were found to explain most of the variance in the labor variables;

these are holding size, number of adults in the family, number of

family members absent on a daily basis (either working, in

military service, or away in school), "excess of females" (number

of adult females minus number of adult males), and ecological


For comparative purposes, regression statistics are shown for

all labor variables with all five independent variables (Table 5).

There are interesting differences among the results.

First, it should be noted that household labor is primarily

linked to household size, and female household labor is also

related to the number of females. Male labor, as one should

expect, is reduced by male absentees. Holding size is also

important; all other things being equal, household members work

more if their farms are larger. However, that variable appears to

be more important than demographic factors. By contrast, the only

variable significantly related to total hired labor is holding

size. Large farms hire more labor than small ones. This fact

also is shown by the ratio of household to total labor; larger

holdings are associated with a greater proportion of hired labor.

Thus it appears that hired labor is used for large farms where

family labor is not sufficient. Family size, increases the

relative contribution of household labor.However, from the total

labor inputs, it appears that farmers do not hire as much labor as

they would use if family labor were available. Family size and

the number of absentees still have an effect on total labor

expended. Thus it appears that either sufficient hired labor is

not available, or family labor is valued more cheaply than hired


Another variable which is sometimes significant is ecological

zone; it appears that more household labor is expended in the

drier area than the wetter. On the other hand, it appears to make

up a smaller proportion of total labor, other things being equal.

As one would expect, the female proportion of household labor

is related to the number of females in the household. So also, it

appears, is the proportion of the hired labor force which is

female; where household females are numerous, hired females are

fewer. This is related to the division of labor, since hired

females are involved in manual labor which can also be

accomplished by household females.

The substitution effect is also apparent in the differences

between male and female hired labor. Male, not female labor, is

hired where family size is small, indicating a higher rate of

mechanization by small holders where hiring males increases when
family males work off-farm. On the other hand, where females are

more numerous, less female labor is hired.The female proportion of

total labor expended is positively associated with household size,

although the female proportion of neither household nor hired

labor is significantly related to size. Possibly this indicates

that large families are more likely to grow legumes, since they

can contribute to the harvesting themselves, but they will still

have to hire from the predominantly female labor force. On the

other hand, the female proportion of total labor is negatively

associated with holding size; on large farms, mechanization

predominates and labor intensive crops may be avoided.


The role of gender in agricultural" labor in northwestern

Syria has been considered. It was noted that male and female time

contributions to crop production are approximately equal; however,

males are more often involved in mechanical operations and other

activities in new technology. Females are more involved with

crops requiring hand labor, such as legumes. Hired labor for

mechanical operations is predominantly male, while that for manual

operations is predominantly female.

Overall the trend in Syrian rural areas has been towards more

mechanization and more off-farm employment of males. Thus the

male rural labor force has been reduced, and those remaining have

been increasingly involved in using new technologies. The female

labor force has also been reduced as families have moved to

cities, and female work opportunities in rural areas have also

declined. Continuing mechanization, particularly of legume and

summer crop production, will continue to reduce female

agricultural activities, including both household and hired labor.

The next task is to assess the effect of these changes on

demographic trends, nutrition, income, equity and agricultural


Table 1 Contribution of males and females as percentages of the
total time spent in on-farm agricultural production.

Contribution Cereal Legume Summer Tree Total
Crops Crops Crops Crops

A. Household labour

Male 23 18 44 47 26
Female 39 34 42 28 35

Sub-total 62 52 86 75 61

B. Hired Labour

Male 33 12 9 24 20
Female 5 36 5 1 19

Sub-total 38 48 14 25 39

C. Grand Total

Male 56 30 53 71 46
Female 44 70 47 29 54

D. % of Area Allocated
to Each Crop. 50 25 19 6 100

E. % of Hours Spent
in Each Crop. 30 40 22 8 100

F. Mean Hours/ha 46 135 94 99 --

Source: From villages surveyed in study.

Table 2 Contribution of males and females as percentages of hours spent in
legume and cereal production.




% Hours
Spent by

% Total
Adult Input

Male Female


Male Female

% Hours
Spent by

% Total
Adult Input

Male Female


Male Female

Tillage Operations

Herbicide Use
Fertilizer Use
Hand weeding
Pest Control








100 0
86 14

15 85 11 26

30 70 18 34






100 0
86 14

38 62 10 39

56 44 23 39

Source: Villages surveyed in study.

Table 3 Contribution of males and females as ptrc ntagr of hours spent in summer crop
and tree crop production.


% Hours % Total Household % Hours %Total Household
Agricultural Spent by Adult Input Only Spent by Adult Input Only
Activities Task Male Female Male Female Task Male Female Male Female

Tillage Operations 11.1 100 0 24 0 16.0 100 0 23 0
Planting 20.0 18 82 18 57 22.0 34 66 19 62

Thinning& weeding 27.0 37 63 37 63 2.0 21 79 21 79
Prunning 24.0 76 24 75 24 35.0 70 30 57 30

& Fertilizer use 3.0 91 9 91 9 24.0 92 8 78 8

Pest control 2.0 32 68 32 68 1.0 17 83 6 83

Harvest and
transport 13.0 45 55 45 55 -- -- -- --

Total 100.0 53 47 44 42 100.0 71 29 47 28

Source: Villages surveyed in study.

Table 4 Mean hour of labor in cereal harvest

Labor Variables









All Combined






Part Manual

76.2 **
94.4 **

60.2 *
85.9 **

140.4 **
180.3 **

.791 )
.40 **

.53 (1)

** F significant at .01
* F significant at .05

Table 5 Regression results on labor variables.




Hired Labor



Labor Ratios



VARIABLES(Beta Values)

Holding Number of number of excess of ecological
Size Adults Absentees Femalesi Zone

.36 0*









.24 *













.79** -.23(NS) .18(NS) -.31*

1 Adult females
2 two values; 1
** t significant
* t significant
(+) t significant
(NS) sig. of t>.1

minus adult males.
is wetter, 2 is drier.
at .01
at .05
at .06



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