Farming systems and farmer-driven problem solving

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Farming systems and farmer-driven problem solving
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Agriculture -- Florida   ( lcsh )
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Includes bibliographical references (p. 34-37).
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by Robert Zabawa and Christina Gladwin.
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Paper presented at the Conference on Domestic Farming Systems sponsored by the Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida, Gainesville. September 10-13, 1984.

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FARMING SYSTEMS AND FARMER-DRIVEN PROBLEM SOLVING

BY

Robert Zabawa and Christina Gladwin





















Paper presented at the Conference on Domestic Farming Systems sponsored by the
Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences,
University of Florida, Gainesville. September 10-13, 1984.









*Robert Zabas~e has a Ph.D. in Anthropology and is a Research Assistant in
the Food and Resource Economics Department, University of Florida. Christina
Gladwin is an Assistant Professor in the Food and Resource Economics Department,
University of Florida. The research was supported by a National Science Founda-
tion grant awarded to Christina Gladwin. The Co-authors are grateful to NSF,
the farmers of Gadsden County, and John Russell, Extension Director. The content
of this paper is solely the responsibility of the authors.









~FARMING SYkSTEMS ND FARMEi-DRIVEN~ PROBLEM SOLVING

BY

ROBERET ZABAWA AND CHRIiSTINIA GLAD~WIN





Farming systems research and extension programs are `now

generally viewed as having some hope of increasing food

production on small rainfed farms in the Third World

(Gilbert et al. 1980; Shaner et al. 1981). Recently, the

farming systems approach has also been effectively tried on

small-scale family farms in the United States as well, as

the participants in this conference have shown. Approaches

to farming systems programs are varied, with debates raging

about "downstream" versus "upstream" approaches, and FSIP

versus FSR/E (the farming systems' approach to

infrastructural support and policy' versus its approach to

technology generation, evaluation, and delivery> (Norman and

Gilbert 1981; Norman 1982).

In general, however, all farming systems programs share:


A concern with small-scale family farmers wJho
generally reap a disproportionately small share of
the benefits of organized research, extension, and
other developmental activities;

A recognition that a thorough understanding of the
farmers' situation is critical to increasing their
productivity and to forming a basis for improving
their welfare; and

The use of scientists and technicians from more
than one discipline as a means of understanding
the farm as an entire system rather than the
isolation of components within the system
rHildebrand and Waugh 1983:4).






Page 2

The focus of a farming systems project is the farmer,

rather than the crop, the technologyJ, or the environment

(CIMMYT Economics Program 1980). The farming systems

approach thus starts with the farmers' constraints and

develops, through experiments on their fields-,

recommendations to improve their family' s standard `of

living. Most farming systems programs accomplish this aim .

via a multidisciplinary team that, first, diagnoses farmers'

problems, goals, and constraints; second, identifies new

technologies or strategies to deal with or alleviate those

constraints; third, tests the promising technologies or

strategies via experimentation and on-farm tests; and

fourth, diffuses or extends the new technologies or

strategies to the local farmers (Gilbert et al. 1980).

A9s farm trials and farmers' tests are on farmers'

fields,. and the farmer is' consulted dur ing both the

diagnostic and the evaluation stages, the farmer is clearly

at the center of the program and farming-systems projects

all espouse the goal of involving farmers more explicitly at

each stage (of diagnosis, technology development, and

technology assessment). In attempting to reach this goal it

is vital, therefore, that the farming systems program should

"...know what decisions the farmer is making, what

alternatives he is considering in each decision context, and

why he chooses a particular outcome" (Gladwin 1983:148).

This perspective then, necessarily adds a new dimension to

the farming systems project. Not only is the farmer the

focus of the research, but he or she is also the main driver






Pace 3


of the research. Farming systems research is not only

directed toward the farmer; the farmer, in a manner,

directs the research as well.

One approach to this goal is the "ethnoscientific"

approach that concentrates on the cultural symbols used by

the farmers. The aim is "to grasp the native's point of

view, his relation to life, to realize his vision of his

world" (Malinowski 1922:25). To see the insider's world

through the insider's eyes is the goal of ethnography, which

differs from other social sciences in its emphasis on

indigenous folk knowledge rather than on scientific

knowledge. Because "the subject matter in ethnoscience is

not environmental phenomena as such, but people's knowledge

and interpretation of these phenomena"(Glick 1964:273), an

ethnoscientific approach of involving farmers in farming

systems research is quite different from previous

approaches. It differs most notably in use of trained

personnel and choice of research tools. To acquire an under-

standing of folk or indigenous knowledge systems in a

natural way (Brokensha et al 1 980) e thn os cienti st s

participate' and live in the culture they are observing,

often for extended periods (Spradley 1979). To test their

understanding, they model farmers' knowledge of the meaning

of important cultural symbols in the farming systems. This

indigenous or folk knowledge can be summarized and

represented in taxonomies, plans or scripts, goals, and

decision models. To describe and illustrate the usefulness

of these tools, we present models of farmers' classification






Prage 4


systems, decision processes, goals, and plans, and show how

we use them to understand and evaluate traditional farming

systems of family farmers in a north Florida county,

Gadsden. We conclude by describing how such knowledge can

be used to better design on-farm trials in a farming systems

program.



THE STRUCTURE OF FARMINGC IN GADI3SDENI COUNTY



For the better part of its agricultural history, Gadsden

County's farming tradition has been based on shade, or cigar

wrapper, tobacco. At its height, shade tobacco was planted

on over 6,000 acres, produced over seven million pounds

annually, and "represented a 100 million dollar industry of

which 25 million dollars was. invested in land, equipment,

barns, packing houses, and operating capital" 'in a four

county area in Florida and Georgia (Womack 1976: 98). The

importance of shade tobacco in Gadsden is further

illustrated by the fact that despite its declining markets

dur ing the .late 1960's, shade still represented an

economic force in the county.

The last three complete census years (1969, 1974, 1978)

are illustrative of the comparative value of shade tobacco

to total farm production value. In 1969, farms numbered 443

units with 149, or 33.6 percent, involved in the pro-

duction of shade tobacco. The total value of agricultural

production for that year was $25,917,000. The value of

shade tobacco production for that year was $15,622,244. In






Page 5

other words, one-third of the county's farms accounted for

two-thirds of the county's production value, on an average

of 33.1 acres of shade tobacco per farm. In 1974, despite

the drop in production, this crop accounted for almost half

(46.3 percent) of the value of agricultural production :in

the county. In 1978, the year after the final crop of shade

tobacco, total farm production declined further to

$19,069,000; and the value of tobacco production, now only

flue-cured tobacco, accounted for only two percent of the

total (USDA 1969, 1974, 1978).

"Shade," as a type of tobacco, was first developed

during the latter part of the 19th century. It was during

the 1890's that the area's tobacco industry- was being

revived through the production of "sun," or cigar filler,

tobacco (Womack 1976:99-101) It wa s soon~ discovered,

however, that the lighter colored, silkier leaves found

near the shaded base of the plant and on plants shaded

naturally by trees, brought the highest. prices at market

because these leaves made the best cigar wrappers (Womack

1976:101; Love 1940:3).' This discovery led to the

introduction of artificial shade to cover the plants, first

built of wooden slats to be later replaced by cloth

stretched over a wooden frame, to create a uniform crop. In

this way, "sun" tobacco (tobacco growJn under the sun) was

put under a shading structure and became known as "shade"

tobacco.

The development of the shade tobacco industry in Gaadsden

County was ideal for ecological, employment, and financial






Pase 6


reasons. Tobacco in general, and shade tobacco in

particular, is a land intensive crop. Because Gadsden's

farmland is ecologically distributed among relatively small

fields with rich soils separated by timberland, swamps,

hills, and other uncultivatable land (so that less than

one-half of- its land in farms is harvested), a labor-using,

land-saving crop was, and still is, ideal for-its geography.

Economically, shade tobacco required a large number of

man-hours in both fields and packing house because the

utmost care was needed to protect the individual leaves from

the slightest damage. For example, a perfect high-quality

leaf could bring in as much as $6.00 a pound. A small hole

on one side of the leaf could reduce its value to $1.50 a

pound; and small holes on both sides of the leaf could

reduce its value to as little as $0.30 a pound (W.T.

Lasley, personal communication). Shaae thus .represented a

major source of employment and supplied nearly 18,000

skilled and unskilled jobs for G~adsden County alone'

(Korsching and Sapp 1976:1).

Financially, shade tobacco was ideally suited for

Gadeden's small farmers since the money to buy production

inputs was supplied by the buyer who therefore established a

formal "forward contract" with the farmer. This

relationship was established because shade tobacco required

a large capital investment to produce. For example, input

costs increased from $1,250 an acre in 1955 to $3,000 and

acre in 1968 to over $7,000 an acre in 1977. At the same

time, however, the farmer's profit margin remained in the






page 7


range of $1,000 to $2,000 an acre, with increasing costs of

production (mostly labor) keeping the profit margin down.

In order to help reduce the tremendous financial burden on

the farmers and insure their own investment, tobacco

companies contracted ahead for a season's production and

supplied up to 75 percent of the input costs as an advance

on the season's profits.

Overall, the high costs of production effectively

disuaded non-contract growers from entering the market while

at the same time, a forward contract helped to insure a good

price for the farmer. Ultimately, because shade tobacco

could be grown on small fields, required large amounts of

hand labor, and had a relatively secure market until the

late 1960's, it wa s an ideal crop for the small-sized

operations in Gadsden County.



THE SHA2DE-CEN\TERiED FARYMING SYSTEM



Shade tobacco was also a part of a more general farming

strategy. Although shade tobacco received the most

attention, other commodities (e.g., cattle and corn) were

managed around the production of shade tobacco. Cattle were

maintained for their manure that wias added to the soil to

maintain soil structure and help the chemical fertilizers.

Corn was produced mainly for cattle feed. Interestingly

enough, while these two commodities had a direct economic

effect on the production of shade tobacco, farmers

frequently stated that the value of cattle and corn was






P'age S3


Associated onlyr with their benefit to shade; in and of

themselves, they were only break-even ventures. Therefore,

due to the hish investment costs of shade tobacco

production, a loss of shade at harvest could hardly be made

up with cattle and corn sales. As one farmer comment ~d:

"Y~ou couldn't pay tobacco debts with corn!"

In this farming system, the best land was put under

permanent shade with overhead irrigation, allowing for two-

to three-year fallow-rotation periods. For example, if a

farmer had a contract to grow 10 acres of shade tobacco, he

might have 20 or more acres under shade, with 10 of those

acres in tobacco followed by a fall crop such a~s pole beans,

and the other 10 acres in irrigated row crops such as corn.

After two years, he would rotate tobacco and corn. The

balance of land not under shade was used for pasture and

rainfed corn for the livestock operations. Through this

farming system, shade tobacco farmers became acquainted with

three different farming strategies: tobacco, row crops, and

livestock.



STRUCTURAL CHANGE IN GAIDSDEN COUNTY



During the decade covering 1967 to 1977, farming in

Gadsden County began to experience the macro-influences of

national and international trends that have led, in general,

to concentration of production in American agriculture.

Factors such as mechanization, market competition at the

international level, and competition for land from non-farm









sources have all led to a general decline in farming in

Gadsden County and of the complete demise of the production

of shade tobacco in particular. The general trend towards

mechanization and modernization started with the gradual

replacement of hand labor for "stringing" tobacco on curing

sticks to the rolling of the cigars. The ultimate

innovation was, the development of synthetic or manu-

factured "homogenized" wrappers made from tobacco leaf

scraps held together by adhesives and a plastic tip so _that

a full leaf was .no longer necessary to bind the cigar

together. In addition, there were tremendous jumps in the

costs of production aqqrevated further by increasing labor

costs. The major jump occurred in the late 196=0's when shade

tobacco production had to come in line with minimum wage

regulations that it had, heretofore, been exempt. This

factor alone almost doubled the cost of labor, and applied

to all laborers: men, women, and children. This situation

was fur the r exac erbat ed by cheaper labor and production

competition from Central~ America where shade tobacco

industry was deve lo ped by the U.S. Gove rnment Some

Gadsden farmers also participated in the Central American

shade industry not only to increase their incomes, but also

to be able to compete with this new, lower priced market.

Lastly, despite occasional jumps in demand, for example

during the cigarette cancer "scare" of the mid 1900's, there

was a declining demand for cigars (Plath 1970:1-4).

Additional pressure on the G~adsden farming sector has

come from adjoining Leon County. More specifically, the






Pagej 10


recent surge in development of the state capital area around

Tallahassee has been the source of competition for Gadsden

farmland from an expanding population seeking rural

residences.





METHODOLOGY



TAXONOMIES



The pillar of ethnoscientific tools is taxonomy, based

on the relationship "x, is a kind of y" (e.g., trees and

flowers are kinds of plants; oaks and elms are kinds of

trees; white and red are kinds of oaks: etc:.). More

formal definitions are found in Frake (1971), Kay (1971),

and Werner and Schoepfle (1979). Taxonomic analysis

searches for the internal structure of domains, which are

sets of cultural symbols that carry meaning for and to

members of the culture.

To understand how the Gadsden shade farmer considered

his post-shade cropping strategies, one must understand how

they thought about shade tobacco and what meaning shade

tobacco had in the culture of Cadsden County, which had,

after all, developed for 80 years around that crop.

Taxonomic analysis is one such method used to enter this

domain of knowledge. As Brush states, taxronomies can be of

"crucial" importance to understanding agricultural systems

because "..crucial decisions (regarding variety, where to






Pag~e 11


plant, and related inputs and technology> can best be

understood through the information matrix underlying the

folk taxonomy" (1980:37).

To find a substitute money crop for ex-shade producers,

a member of a farming systems team could consult the USDA

classification of different kinds of foreign and domestic

tobacco (Gardner 1951:18). But, because farmers' decisions

and survival plans depend on and are influenced by their own

knowledge or perception of tobacco, rather than the USDA's

knowledge of tobacco, a more useful approach is to

understand shade tobacco as the farmers do. Thus, an

ethnoscientist would elicit the classification structure of

tobacco internal to the Gadsden farmer.' Briefly, this

taxonomy (Figure 1) says that, first, Cadsden farmers

classify tobacco by use, into cigar tobacco (sun and shade

tobacco) and cigarette tobacco (f lue- cured and Maryland

tobacco) (Zabawa and Gladwin 1983; Zabawa 1984). At the

next level, shade tobacco, used for cigar wrappers, is

distinguished from sun tobacco, used for cigar filler.

Produced in Gadsden through the 1930s, sun tobacco

production declined as shade tobacco became more prominent.

Since the 1930s, the federal government has controlled

production by granting farmers the right to grow ilue-cured

tobacco in small areas or allotments, with a ceiling of 175

acres total in Gadsden County. Mzryland tobacco was briefly

introduced in the 1960s, but production declined shortly

thereafter when pressure from Maryland legislators forced

Gadsden farmers to include Maryland tobacco as part of their






Page 12!


flue-cured allotment. This action effectively killed any

attempt by G~adsden farmers to adopt Maryrland tobacco because

they had been growing it to increase their production over

and above their flue-cured allotment.

The lower taxonomic Icvelis further specify different

varieties of shade tobacco (Type 61l or Connecticut shade and

Type 62 or Florida shadc>, and different varieties or

Florida shade (R~g, Dixie shade, F1 shade, and the hybrids).

Partonomies or part-whole relationships then distinguish

meaningful parts of the individual plant for the farmer:

the roots, stalk, and leaves are important parts of the

tobacco plant. Because the shade leaves contain the

economic value of the plant, "sand" leaves (the bottom two

or three marketable leaves> are distinguished from the

"middles" (the next 4-19 leaves, among which the most

desired leaves are usually found), and the "tops" (the upper

two to four marketable leaves of the plant> (Kincaid 1960).

The taxonomic structure can be carried one stage further in

the marketability of specitice kinds of leaves. For example,

the highest quaity, and therefore the most profitable

"middles" were called "number one string" and sold -with no

further grading, whereas the rest of the leaves went through

a grading procedure developed by the tobacco companies (see

Spu~rlock 1933).

The taxonomy of shade: tobacco thus represents the

knowledge structure Gadsden farmers have developed while

growing shade. Farming systems team can consult

taxonomy' for possible substitute money crops. Indeed, the






Page 13


second level taxa--fLue-cured and Maryland tobacco--would

have been logical alternatives it government controls had

not prevented increases in the production of these crops.

Gadsden-s farmers thus had to switch to money crops

out side the domain of tobacco. How did'they make that

decision? In most cses, they searched for and found

alternative crops such as tomatoes, nursery crops, or pole

beans and squash) that caused only a small disruption to the

original, formerly successful crop plan or farming system.

A knowledge of how they grow shade--their plan or

script--would be essential in identifying such similar

crops.



PLANS AN~D SCRIPTS



Instead of deciding how to do something every year,

farmers develop a plan or inherit a plan already developed

by their parents or grandparents. The plan, "how to do x,"

is a sequence of mental instructions or rules that tell the

actors who does what, when, and for how long (Werner and

Schoepfle 1979). To the insider or decision-maker, however,

they are not decision rules, because he or she is not awrare

of having had to make a decision. The decision is made so

frequently, so routinely, that the decision rules become

part of a pre-attentive plan or "script," like the script

in a play that tells the actor what to say and do (Schank

and A2belson 1977). By means of these scripts, the farmers

do not have to make a million decisions: they know how and






Pavse 14l


when to plant shade tobacco, probably because they were

taught by their parents.

Eventually, this knowledge will be passed on to a new

generation as a "traditional" way of doing things. When the

new generation of farmers is aLsked why they do the things

the way they do, they may reply, "it is the custom." Some of

them may even forget the original decision criteria; they

only know that, for some reason, the traditional way is "the

best" way to do x, given the original constraints or

constraints used or faced by their grandparents and parents.

Examples of such inherited scripts or "adaptive" strategies

abound in the literature of economic and ecological

anthropology (Bariett 1980; Bennet 1969; Brush 1976;

Cancian 1972; Chibnik 1981; Johnson 1971; Mayer 1979;

Moran 1979).

The Gadscden farmers; plan or script for shade tobacco

(Table 1) (K~incaid 19630) was quite similar to that for

staked tomatoes iTable 2). For example, tobacco seed beds

are planted and maintained in the same months when plastic

is put out for rows for tomatoes. Tobacco' seedlings and

tomato plants are transplanted in a similar, labor-intensive

way. In June and July, both tomatoes and tobacco are

harvested by hand; and, in August, fields are cleaned up

after harvests of both crops. Given the similarity of these

plans, it is not surprising that many ex-shade producers

decided to become tomato producers.

The importance of a plan or script as a tool in farming

systems research and extension is that it tells the






Pavre 15


investigator something specific about the person or group of

people carrying out a particular action sequence. plans are

the highlights that show the outsider the insiders: methods

to achieve their goals and satisfy the roles that place them

within their culture.



HIERARCHICAL, DECISION MODELS



A knowledge of farmers' traditional cropping plans or

scripts, however essential to an FSE(/E team designing

on-farm trials, does not alwJays tell the team what happens

when the script or plan is interrupted or the desired goal

is changed. A knoniedse of farmers' decision criteria and

perceived alternatives and options is, therefore, necessary

to a team that want s to design adoptable ~technroloy or

evaluate technology already generated.

With this information, researchers can build models at

the decision-making process that incorporate -farmers'

decision criteria and constraints. The models of

decision-making are hierarchically (Gladwin 1976;, 1980)

ordered on the basis of the characteristic to be maximized,

incorporating alternative branches based on the constraints

and criteria of the farmers.

Hierarchical decision models !RDMs! are decision

" t r ees ," fl owc har t s lists, a set of rules, etc. For

example, given the shared knowledge about the different

cropping alternatives open to them, former Gadsden County

shade tobacco farmers have based their chance of crop






Page 16


decisions on: knowledge and experience, especially of the

farming system shade tobacco cattle and corn discussed

previous'ly, and financial and market options.

A hierarchical decision model outlining this process is

seen in Figure 2. The decision criteria aspects,. or

constraints are denoted by the diamonds (C >) at the "nodes"

or the branching points of the tree. These criteria are the

goals "motivating" the decision, the aspects to be

"maximized" ~ or ordered on, or the constraints that must. be

passed or satisfied. In this case, the farmer must decide

between growing tomatoes, raising cattle, or cutting back on

farm participation. For example, the second criterion in

Figure is: "Do you want to grow a crop similar to shade

in managerial style and use of: resources: land, labor.

equipment, and capital?" If the farmer answers "yes," the

tree deterministically (with probability of 1) sends him--or

more accurately his responses--down the left hand branch of

the tree to consider crops very similar to shade. If the

farmer answers "no," the tree sends the farmer down the

middle branch, to consider crop not so similar to shade

ie.g., row crops>. If the farmer cannot pass the

constraints to row cropping, he is sent to the right hand

branch to consider dissimilar cropping .strategies such as

livestock-centered farming systems. If the farmer fails

this last list of constraints, he has no alternative but to

cut back on the farm operation by hiring a manager, getting

a partner, Leasing, or selling. The latter decision is

described at length elsewhere !Cladwin and Zabawa 19,83,






Eage 17


1484; Za$awa 1984).

Criterion 2 can also be thought of as an ordering aspect

in a stage twJo decision process
very similar to shade are considered before crops not so

similar which then preceded crops dissimilar-to-shade. Th se

same subsets of crops also share the same order on

profitability: in general, tomatoes and nurseries are more

profitable than soybeans wJhich are more profitable than beef

cattle.

Each subset of crops has its owYn set of constraints,

which must be passed before a farmer proceeds to an outcome

!denoted byr Cj) npecifiying adoption of a particular crop.

For example, nurseries have a high capital constraint due to

the las time between initial investment and first returns

i criterion ) ; whi le t omat oe s have a high market risk

factor
particularly, subdecisions with more in-depth stage one

criteria involved. For example, the fourth criteria

concerning tomatoes is also a more complete subdeci-sion that

includes the risk, market problems l and, labor, and

capital, particular to tomato production (see Zabacwa 1984).

If a farmer fails to pass constraints of a crop vr

similar-to-shade (and veyprofitable), he proceeds to a

not-so-similar and not-so-profitable crop and attempts to

pass those constraints.

The outcomes in Figure 2 show that, or the 52 farmers

who arew shade tobacco, there were 34 cases of farmers who

chose very similar-to-shade cropping strategies, 5 cases of






Page 18


farmers who chose row crops, 6 cases of farmers who chose a

cattle-centered farming system, and 35 cases at farmers wJho

decided to cut back on their farming operations. (It

should be noted here that a farmer can enter the decision

model more than once. This accounts for the number of ca~es

exceeding the farmer sampic size.)

The meaning of these results is seen more clearly when

they are compared to the data found in Table 3. Table 3

re resents the farming strategies chosen by the ex-shade

farmers the year after they quit producing shade tobacco

(column 1) and the strategies chosen by these same farmers

in 1982 (column 2). From Table 3, it is seen that at the

end of shade tobacco, the farm sample divided itself evenly

between similar-to-shade alternatives--40.4 percent and the

cut back alternative--42.3 percent, while only 17.3 percent

of the sample chose dissimilar-to-shade alternatives. By

1982, this trend continues, as seen in the second column of

Table 3. The number of similar-to-shade cases remains high

at 32.7 percent, while the number ofcases of farmers

employing the dissimilar-to-shade strategies have been

significantly; reduced to 3.8 percent. Conversely, those

cases representing farmers who have cut back have increased

to d3.5 percent. Because dissimilar-to-shade cropping

strategies of row crops and livestock proved not profitable

enough to support a large number of full-time farmers, there

has been a transition away from the dissimilar strategies to

cut back strategies.

The decision model in Figure 2 reflects the above







Pagce 19


transition.. The model is composed of the total number of

decisions employed by the sample from the time they dropped

shade tobacco until 1982. This model shows that 34 cases,

or 42.5 percent, adopted similar-to-shade strategies and

that 35 cases, or 43.8 percent, adopted cut back strategies,

the model also shows that there are only 11 cases ror 13.8

percent) of farmers who have attempted a dissimilar-to-shade

farming strategy. These farmers are part ofthe 17.3

percent of the sample found in the first column in Table 3.

More importantly, this model examined along with Table 3,

shows that these particular farmers ended up adopting the

cut back strategy, illustrated by the decrease in the number

of dissimilar strategies and an increase in the number at

cut back strategies in the second column in Trable 3. Asain,

these results show that Gadsden's shade tobacco farmers

either switched to very similar cropping strategies to shade

or they got out of' full-time farming and became part-time

farmers or gardeners.

In conclusion, knowledge of the decision criteria that

the farmers consider important (riskiness,

capital-intensity, equipment and land requirements> is vital

for a team trying to identify a suitable substitute money

crop, as is a knowledge of their plans or scripts to grow

the crops in question. Further, it is knowledge that cannot

be picked up tor all substitute crops on a "quick and dirty"

five-day reconnaissance survey !Franzel 1983: Gladwin

1983); it requires follow-up survey using careful

procedures to elicit information trom farmers in a






Pase 20


systematic w.ay (Gladwvin 1979a).



THE PROBLEM OF STRUCTURAL CHANGE



Just as micro-level decision processes are formed within

contexts which "frame" the decision (Tversky and Kahneman

1981), farmers: problem solving occurs within an economy

influenced by macro-level of structural forces. In the case

of the Gadsden County shade tobacco farmer, the macro-level

forces of mechanization and te chno logical change,.

international competition for markets and escalating costs

or capitalization of production, all contributed to the

demise of a tradition-bound arming system and lead to the

re-structuring of Gadsden County farming..



THE TRAN~SFORMA9TION OF FULL-TIME SHAD~E PRODUCERiS



To illustrate the transformation of the Gadsden shade

farmers, the different farm work strategies they employed

during their last year of shade production are compared in

Table 4 to those strategies employed by the same farmers in

1982. For example, during their last year of shade tobacco

production, 981 percent of the sample farmers were

considered full-time farmers (defined here as an average of

40 or more hours per week of tarm work) and 1.9 percent of

the farmers wecre part-time defined as farm work averaging

at least 8 hours per week but less than 40 hours per week).

By 1982, full-time farmers represented only 36.5 percent o






Pagxe 21


the sample, part-time tarmers represented 21.2 percent of

the sample, and non-farmers (that is, those averaging less

than 8 hours per week of farm work) represented 42.3 percent

of the sample (the majority of these farmers were retired).

These data clearly show that there has been a move away- from

full-time ~farming; and a chi-squared analysis of these

"before and after" strategies finds this transition to be

significant i0( =44.96, p=0.001).

For the former shade farmer, the impact of these

macro-forces has not stopped with the and of shade

production, however. These forces also aftoct the choices

that are considered as shade replacement crops, as well as

what crop will ultimately be adopted as the shade

replacement crop. For example, from the taxonomy in Figure

1, flue-cured and Marviand tobacco were tobacco alternatives

to shade; however, government controls severely limited the

widespread adoption of these crops. Similarly, from the

plans or scripts in Tables 1 and 2, tomatoes are shown to be

verycompatible with the shade arming system;

unf ortunat e ly, c omp et it ion from the large producers in

southern Florida, California, and Mexico limits entry of the

Gadsden farmer into this market as well.

Concerning the influence of macro-level forces, it has

been shown that since the demise of shade tobacco in Gadsden

County starting in the early 1970s, a significant number or

full-ime armers have changed their tarming strategy and

adopted part-time, non-farm, and retirement strategies.

That is, through the data presented, it can be shown WHAIT









these farmers did atter shade: some maintained a full-time

farm operation and others cut back. However, an additional

concern now needs to be addressed, and that is NHYI these

farmers chose the paths to their ultimate 1982 outcomes

given their specific decision environment or context. For

example, it can be correctly hypothesized that: 1

specific group of farmers chose the part-time strategy

because they were in the superior position of having low

debts and high assets and wanted to keep those assets at the

least risk; 2) those farmers with high debts and low

assets would cut back and sell some land to regain

financial stability; and 3) those with a relatively stable

debt and asset position, but advanced in age, would seek

retirement. These assertions, how ever correct, elicit

further questions of why would these farmers pick the end of

shade tobacco to decide that their farming (economic)

position would become more or less stable in the future?

The-answer, or at least part of the answer, to this

question lies in the farming alternatives open to the

producers of shade after the demise of this crop,

alternatives directly influenced by forces. such as increased

competition and costs. Specifically, ex-shade producers

faced with the loss of their money crop had to consider a

ma jor reorgani zat ion of the ir t arming strategies that

included going out of business entirely or cutting bac~.k

production substantially if they could not find a

comparable high-valued and environmentally compatible

substitute money crop.






F;~cTr ~_i


As discussed before, after the demise of shade tobacco,

a former shade producer had three main alternatives. He

could: 1) adopt a similar-to-shade cropping strategy ie.g.,

nurseries, tomatoes, polebeans and squash, etc.); 2) adopt

a dissimilar-to-shade cropping strategy (e.g., row cropping

or cattle); or 3) he could cut back on his farm

participation and lease his land, sell out, and/or find

off-farm work or retire. These statecries are outlined in

Tab le s 5 and 6. Tab le 5 rep re sent s the cropping

Ilternatives adopted by the ex-shade producers the year

after their last crop of s;hade tobacco and Table tj

represents the cropping alternatives adopted by the ex-shade

producers in 1982.

Three observations can be made concerning the fi-fty-two

former shade farmers the year after they ceased shade

production. First, those farmers who continued with a

similar-to-shade farming strategy in=21) had the most owned

acreage, the lowest debt, and the lowest debt-to-asset

ratio. Conversely, those farmers who cut back the year

after their last crop of shade (n=22) had the least o~n~ed

acreage, the least assets, the most debt, the highest

debt-to-asset ratio, and were the oldest in age. Finally,

those farmers w~ho adopted a dissimilar-to-shade cropping

strategy, while the youngestt in age, struck a middle ground

between the similar-to-shade and cut. back strategies.

By 1982, the picture presented above had changed

significantly. Though there has been the expected shifting

of the sample due to the adoption, rejection, re-adoption of







Page~ 24


various alt ernat ives three observ~ations can be made from

Table 65. First, those farmers who were in the

similar-to-shade cropping alternative category in 1982

(n=17) continued to have the most owned acreage and the

highest assets; by 1982, however, they also had the largest

debt as well as a significant increase in their

debt-to-asset ratio. Second, by 1982, those farmers wJho

were in the cut back category (n=33) hacd increased by 50

percent, mostly from farmers who had initially adopted a

dissimilar-to-shade cropping strategy, had the lowest debt

and debt-to-asset ratio. Finally, those farmers who were in

the dissimilar-to-shade category in 1982 (n=2) had decreased

their owJned acreage and assets, but had also increased both

their debt four times and debt-to-asset ratio by over two

times;.

Tables 5 and 6 present a clearer picture of what the

shade tobacco farmer experienced in post-shade agriculture

vis-a-vis the cropping alternatives open to him. First, the

farmers' in the similar-to-shade category were in the best

position to continue farming. By 1982, however, these

farmers show the effects o" adopting new, capital-intensive,

and often unproven income generating, high risk crops.

Second, because of its low income generating potential,

there is move among farmers who originaliv adopted

dissimilar-to-shade strategies to enter the category of

farmers who cut back.. Finally, those tairmers who have cut

back on their ta~rm operations (e.g., part-time, non-tarm,

and retired farmers), have reduced their debt wJhile they






P~are 25


also have retained and even increased their assets.

It also becomes clearer that the farmers who, in 1982,

have retained the full-time strategy (n=19) have done so at

the expense of their equity, and those with the greatest

debt and asset movement are the farmers who have adopted a

similar-to-shade cropping strategy; in=37), particularly, the

easily accessible tomato alternative tn=8).



CONCLUSION



Thi s paper has presented examp le s of the use o

ethnoscientific tools and hierarchical decision models that

can be useful in programs designed to generate a tro riate

t ec hn ologry for small-scale family farmers through a multi-

disciplinary team effort. In designing on-farm trials,

farming systems researchers can benefit from knowledge of

farmers' indigenous classification systems, plans or

scripts, and cropping decisions. The case of Gadsden County

in the 1970s, when full-time farmers had to switch from

shade tobacco to tomatoes or go out of business, and the

case of Gadsden County today, where some farmers are trying

to switch from risky tomatoes to other alternative crops and

Part-time farming, shows the necessity of an in-de th

knowledge ot how farmers make cropping decisions and plans

along with a knowledge of: the context within which these

decisions are made.

In addition, the taxonomy illustrates the structure of

the G~adsden farmer's knowledge about tobacco, and helps to






F~lse ~~


pinpoint the logical alternatives open to farmers, given

the failure of one of the crops in the taxonomic domain.

Given government restrictions on alternative varieties of

tobacco as a replacement to shade, a knowledge of farmers'

plans and scripts to grow shade helps the researcher

understand the adoption of alternative cropping strategies

outside the domain of tobacco (e.g., tomatoes, nurseries,

pole beans, and squash). Finally, a look at the macro-level

structural forces affecting farmers today, such as market

competition and government regulation, helps to show how

such exogenous variables can influence the organization and

reorganization of a farming system as well.

We conclude that farming systems research and the design

of on-farm trials can help U.S. farmers solve their

problems if and only it some of those trials are oriented

towards the future farming systems in the country. Because

U.S. agriculture is so dynamic, it is not enough for a

domestic farming systems program to design ~a~rm trials based

on the knowledge of farmers current cropping systems. The

multidisciplinary- team should also be knowledgeable of

farmers' problems with the present cropping system, and

farmers. expectations of future cropping systems. Some of

the on-farm trials should be designed to help tarmers learn

about future farming systems that may come under considera-

tion in the future. The farmine systems team should be able

to assess whether and how many farmers will switch to these

new systems, and why~.

OtherT trials should be explicitly: oriented toward .the






Pagce 27


part-time farmer in U.S. agriculture, because so manyr

full-time farmers in the less than $500,000 sales category

are transforming into part-time farmers (Sulauf 1984). Due

to the structural change in U.S. agriculture, the case of

Gadsden County is not an isolated instance. Unfortunately,

the majority of U.S. farmers, like the Gadsden farmers,

face dual problems of unstable world demand for their

products and the structural change in U.S. agriculture.

The Cadsden farmer has faced these problems and has adopted

post-shade tobacco cropping alternatives and also switched

to an emphasis on off-farm work and part-time farming. In

order for on-farm trials to help solve the problems of the

present day farmer, the farming systems team must first

understand the indigenous knowledge systems, cropping

strategies, and decision making processes of the farmers

they are trying to help.






























FIGURES, TABLES, and REFERENCES






(T) Tobacco (T)


Cigar
Tobacco


Cigarette
Tobacco


(T)


shade Tobacco Flue-cured
~(cigar wrapper) (cigarette -
er) (T) (T) filler)



Type 61 Type 62
(Conn. Shade) (Fl. Shade)



Rg (old) Dixie Florida
(1935)~ Shade Shade


Maryland
[air-cured]
cigarettei
filler)


Sun Tobacco
(cigar fill
er and bind


(1953)


(T)) (T (T)



F1 15 F1 17 Fl 20 C80a C76 C63
(1964) (1968) (1968)


Hybrids
(1960's)


Rg (new)
(1960)


DS-L-4
(1962)


Individual
Shade Tobacco


Stalk


Sand Middles Tops




#1 String other grades


Figure 1: Taxconomy of Gadsden County Shade Tobacco

























































Can you withstand
hemarket fluctuation
of the hog industry?


101 cases
19 errors


Raise Hiogs ye
8 cases
(4 errors)


Success rate 1 0.812


Develop U-Pick/ 4-- I no 0css
Orchard Operation
5


TmteGrow 4-`- yes/ no: 45 cases
Tomatoes


15 caeros Can you make a
(3 errrs) / living growing


no: 31 cases


. '


'


101 cases
(INursery; U-Pick; Tomatoes; Pole Beans, Squash,
Flue-Cured Tobaco; liogs; Row Crops; Cattle)


Figure 2: The Decision to
Change Crops after Shlade Tobacco

.N=101 cases of 52 shade and 21
non-shade farmers.


(Did you grow shade tobacco 1 no aI ExtDcso1cae(s)
\as your maj or money crop? ~~LIxtDcso 1css(s


I


boyou want to gro~
with similar manage
style and use of rt
land, labor, equipr
capital?


yes \802casss/
w a croP\ -Is the possible
erial a row crop center
sources: the possible pro
ment, and stock centered o
Or are you alreai
row cropping ver

no: 15 cases


I/


profit from
red operation >>
fit from a live-
peration and >> 07
dy' set up for
sus livestock?


yes:
65 cases /
Doyou have the capital
encouragement and inter-
est to develop a nursery
operation?


mo: 14 canner


Doyou have the acreage (>500
and equipment needed to row
crop efficiently?
yes


Develop Row Crop I no: 30 cases
Centered Farm
Operation
2 cases
(1 error)


Is the possible profit from \11
a livestock centered (cattle)
operation >> 0 on your present
set up? Or are you already
set up for a livestock opera-
tionl


yesno 61 ass
develop Nursery 1 6 ns
I plato Do you have the\


capital to rtait
for u-pic~k/orchard /
;naturation period?


4


yes


Develop Livestock
Ce pterad Fanr

6 cases
(3 errors)


4 cases
(1 error)


no: 35 cases


Are you willing to buy or rent \10
more land to increase acreage
along with any needed equipment /


'hTO yOU willing
to accept the risks
f growing tomatoes


1 c898


'Are you willing to invest in\1
necessary livestock inputs
(buildings, fences, etc.) and
possibly increase acreage via
.purchase or rental for feed
and pasture to increase pro-
duction and profit?
S yeso


Develop Livestock Cut Back:
Centered Farm I Sell, Lease,
Operation etc.
O cases 35 cases
(4 errors)


yes


Develop Row Crop
Centered Farm
Operation
3 cases
(2 errors)


,: 27 casee










Table 1 t Gadsden County Farmers' Plan for Shade Tobacco.

January 1st Plant seed beds.
Januiary- Prepare soil, fumigate, and fertilize with manure and
February chemical fertilizer.
Note: labor for the history of shade tobacco was local
with the majority of the laborers being Black.

March 1. Harrow soil into rows four feet apart approximately
three weeks before transplanting.
2.-Install shade cloth shortly before planting.

Late March- 1. Transplant seedlings in the shade.
Early April 2. Water at transplanting at a rate of 10 barrels of
water/acre.
3. Reset hills with missing or weak plants within a
week.
4. Dust plants with insecticides on a seven day
schedule.
5. Plow the rows twice a week (discontinue near harvest
time to prevent damage to the leaves).

April String plants (starting when plants reach one foot),
spirally from the stalk near the ground, to the
overhead wire above the row. Continue to string,
spirally between the leaves, once or twice a week
depending on rate of growth.

May Water when needed using overhead irrigation system.

June "Top" plants to prevent budding if desired.

July' Harvest seven to eight weeks after transplanting. The
harvesting procedure consists of:
1. Pick the desired leaves off each plant, i.e.,
"priming" (there can be 2-5 leaves per priming and
6-10 primings per plant).
2. Place the leaves in the order picked and haul them
to the tobacco barn.
3. String the tobacco in the barn.
4. Cure the tobacco in the barn (3 to 5 weeks).
5. Deliver the tobacco to the packing house.

August Clean up and prepare for a fall crop (e.g. polebeans)
if desired.

Source: Kincaid 1960.










Table 2 : Gadsden County Farmers' Plan for Staked Tomatoes.


December-
January





February



March








April


1. Prepare the soil, lime.
2. Order plants.
Note: labor for the preparation, transplanting, staking,
and stringing of the tomatoes is supplied mainly by
local Black residents. Harvesting is performed mainly
by migrant workers of Spanish descent from South:-
Florida, Texas, and Mexico.
1. Put plastic out on the rows (the plastic retains mois-
ture, prevents leaching of the fertilizer, prevents
weeds, etc.).
2. Fumigate, fertilize.
1. Plants arrive.
2. Transplant into the fields around March 15th (plants are
watered through trickle irrigation that is under the
plastic; soil treatments are applied under the plastic
as well; plant treatments are applied through overhead
irrigation if available, or by portable sprayers).
3. Spray plant treatments on a five to seven day schedule
to prevent insects and disease.
1. Stake plants approximately two weeks after planting.
2. Start horizontal stringing approximately two weeks after
staking and continue on a two week schedule for a total
of four horizontal rows of string per row of tomatoes.
1. Complete stringing.
2. Irrigate as needed.
1. Start hand-harvesting the "green" tomatoes using local
and/or migrant labor and deliver the tomatoes to the
packing house for shipment.
(The harvesting cycle is to pick through one field, move
to the next field, let the fields rest and the tomatoes
mature, start picking again).
2. Start picking "pink" tomatoes when they represent about
10% of the tomato population--approximately two to three
days after harvesting begins (the "pinks" are harvested
by independent migrants who pay the farmer a flat rate
per box of picked tomatoes and then sell the tomatoes at
farmer's markets).

3. Open fields for u-pick operation at the end of harvest
and before clean-up operations begin (u-pick is saved
for last to prevent damage to the plants and the spread
of disease from other fields).
Clean up:
1. Burn the plastic string off the old plants with a 2--row
propane burner.
2. Pull up the stakes and store them.
3. Mow the old plants down and harrow them into the ground.
4. Prepare for a fall crop (e.g. pole beans) if desired.


May

June


July


Late July
August













Table 3 : Cropping Alternatives to Shade Tobacco.


Total 52 100.0 100.0% 52 100.0 100.0%

Note: aExamples are pole beans, flue-cured tobacco, squash.







Table 4: -Farm Uork Strategies for the Shade Tobacco Farmer.

Last year in ST 1982
ST Number Percent Number Percent

FTP 51 98.1 19 36.5
PTF 1 1.9 11 21.2
NF 0 0 22a 42.3

Total 52 100 52 100

X2 = 44.96, p =0.001
Note: al3 farmers retired








Tables 5: Financial Aspects of Different Post-Shade Cropping
Strategies After Last Crop of Shade (Nt52).

Strategy N Percent Age 0AC Debt($) Assets($) D/A(%)

Similar 21 40.4 49.9 466.7 24,650 328,693 9.70
Dissimilar 9 17.3 44.1 371.7 38, 889 359,811 15.56
Cut Back 22 42.3 51.5 283.7 53,015 247,238 23.30



Tables' 6: Financial Aspects of Different Post-Shade Cropping
Strategies in 1982.

Strategy N Percent Age 0AC Debc($) A4ssets($) D/A(%)

Similar 17 32.7 52.1 475.9 187,036 726,696 33.15
Dissimilar 2 3.8 58.0 106.5 150,000 300 ,000 37.50
Cut Back 33 63.5 62.1 246.0 6,364 263,026 2.41


Year after ST
Similar:


Number Percent


Number Percent


Nursery 2 3.8 3 5.8
U-Pick 0 0 1 1.9
Tomato 7 13.5 40.4% 8 15.4 32.7%
P.B. F.C. SQa 5 9.6 2 3.8
Hogs 7 13.5 3 5.8

Dissimilar:


Row Crope
Cattle
Cut Back


5 9.6
4 7.7


1 1.
1 1.9


17.3%


3.8%


22 42.3 42.3%


33 63.5 63.5%








REFERENCES


Barlett, Peggy F.
1980 Adaptive Strategies in Peasant Agricultural Production. Annual Review
of Anthropology, 9:545-573.

Bennett, John F.
1969 Northern Plainsmen: Adaptive Strategy and Agrarian Life. Chicago: Aldine.

Brokensha, David W., and D.M. FWarren and Oswald Werner.
1980 Indigenous Knowledge Systems. Lanham, Maryland: University Press of America.

Brush, Stephen B.
1976 Introduction to Cultural Adaptations of Mountain Ecosystems. Human
Ecology, 4(2):125-133.

1980 Pota'to Taxonomies in Andean Agriculture. In Indigenous Knowledge Systems.
David W. Brokensha, D.M. Warren, and Oswald Werner, eds. Pp. 37-47, Lanham,
]Maryland: University Press of America.

Cancian, Frank
1972 Change and Uncertainty in a Peasant Economy. Stanford: Stanford Univer-
sity Press.

Chibnik, Michael
1981 The Evolution of Cultural Rules. Journal of Anthropological Research,
37(3):256-268.

CIMMYT Economics Program
1980 Planning Technologies Appropriate to Farmers: Concepts and Procedures.
El Batan: CIMMYT.

Frake, Charles 0.
1971 The Ethnographic Study of Cognitive Systems. I:r Anthropology and Human
Behavior. T. Gladwin and W. Sturtevant, eds. Pp. 72-93. Washington, D.C.:
The Anthropological Society of Washington.

Franzel, Steven
1983 Planning an Adaptive Production Research Program for Small Farmers: A
Case Study of Farming Systems Research in Kirinyaga District, Kenya.
Unpublished Ph.D. Dissertation, Michigan State University.

Gardner, Wightman
1951 The Production of Tobacco. New York: The Blakiston Company.

Gilbert, E10n H., and David W. Norman and Fred E. Winch
1980 Farming Systems Research: A-Critical Appraisal. Michigan State University
Rural Development Paper No. 6. East Lansing: Department of Agricultural
Economics, Michigan State University.










Gladwin, Christina H.
1976 A View of the Plan Puebla: An Application of Hierarchical Decision Models.
American Journal of Agricultural Economics,58(5) :881-887.

1979a Cognitive Strategies and Adoption Decisions: A Case Study of Nonadoption
of an Agronomic Recommendation. Economic Development and Cultural Change,
28(1):155-173.

1979b Production Functions and Decision Models: Complementary Models. :American
Ethnologist, 6(4):653-674.

1980 A Theory of Real-Life Choice: Applications to Agricultural Decisions. In.
Agricultural Decision Making: Anthropological Contributions to Rural Develop-
ment. Peggy F. Barlett, ed. Pp. 45-85. New York: Academic Press.

1983 Contributions of Decision-Tree Methodology to a Farming Systems Program.
Human Organization, 42(2):146-157.

Gladwin, Christina H., and Robert Zabawa
1983 The Effects of Concentration on the Full-Time Farmer in Gadsden County,
North Florida: His Strategies to Survive and Preserve His Farmland. Paper
presented at the Annual Meetings of the Society of Economic Anthropology,
Iowa City, Iowa, April.

1984 Microdynamics of Contraction Decisions: A Cognitive Approach to Structural
Change. American Journal of Agricultural Economics (December).

Gladwin, Christina H., and Robert Zabawa and David Zimet
1984 Using Ethnoscientific Tools to Understand Farmers' Plans, Goals, Decision
Processes, and FArming Systems. In Coming Full Circle: Farmers' Participation
in the Development of Technology. Peter Matlon, Ronald Cantrell, David King,
and Michel Benoit-Cattin, eds. Pp. 27-40. Ottawa, Canada: International
Development Research Center.

Glick, Leonard
1964 Categories and Relations in Gimi Natural Science. American Anthropologist,
66(4):273-280.

Hildebrand, Peter, and Robert 'Waugh
1983 Farming Systems Research and Development. Farming Systems Support Project
Newsletter, 1(1):4-5.

Johnson, Allen
1971 Security and Risk-Taking Among Poor Peasants. In Studies in Economic
Anthropology. George Dalton, ed. Pp. 143-150. American Anthropological
Association Monograph No.7.

Kay, Paul
1971 Taxonomy and Semantic Contrast. Language, 47:866-887.








Kincaid, Randall
1960 Shade Tobacco Growing in Florida. University of Florida Agricultural
Experiment Station Bulletin, 136:5-41.

Love, James
1940 History of Tobacco Growing in Florida. Presentation before the Florida
Historical Society. Quincy, Florida, 28 March.

Malinowski, Bronislaw
1922 Argonauts of the Western Pacific. London: Routledge.

Mayer, Enrique
1979 Land-Use in the Andes: Ecology and Agriculture in the Mantaro Val ey of
Peru with Special Deference to Potatoes. Lima: International Potato Center
Social Science Unit.

Moran, Emilio
1979 Human Adaptability: An Introduction to Ecological Anthropology. North
Scituate, Mass.: Duxbury.

Norman, David W.
1982 The Farming Systems Approach to Research. Farming Systems Research Paper
No. 3, Kansas State University, Manhattan, Kansas.

Norman, David W., and Ermmy Simmons and Henry Hays
1982 Farming Systems in the Nigerian Savanna. Boulder, Colorado: Westview Press.

Plath, C.V.
1970 Florida Shade Tobacco, Economics of Production, 1969. Florida Cooperative
Extension Service, Institute of Food and Agricultural Sciences, University of
Florida, Gainesville.

Schank, Roger, and Robert Abelson
19.77 Scripts, Plans, Coals and Understanding. New York: Wiley and Sons.

Spradley, James
1979 The Ethnographic Interview. New York: Holt, Rinehart, and Winston.

Spurlock, Alvin
1933 Marketing Florida Shade Tobacco. Unpublished Master's Thesis. Univers it'y
of Florida, Gainesville.

Shaner, W.W., and P.F. Phillipp and W.R. Schmeh1
1981 Readings in Farming Systems Research and Development. Boulder, Colorado:
Westview Press.

Tversky, ~Amos, and Daniel Kahnemani
1981 The Framing of Decisions and the Psychology of Choice. Science 211
(4481):453-458.

United States Department of Agriculture
1969, 1974, 1978 United States Agricultural Census. Washington, D.C.: USDA.









Werner, Oswald, and G. Mark Schoepfle
1979 The Handbook of Ethnoscience: Ethnographies and Encyclopaedias. Evanston,
Illinois: Department of Anthropology, Northwestern University.

Womack, Miles K.
1976 Gadsden: A Florida County in Word and Picture. Montgomery, Alabama:
Taylor Publishing Company.

Zabawa, Robert .
1984 The Transformation of Farming in Gadsden County, North Florida: A Micro-
Level Example of a Macro-Level Phenomenon. Unpublished Ph.D. Dissertation,
Northwestern University.

Zabawa, Robert, and Christina Gladwin
1983 Using Anthropological Tools to Understanid Florida's Farming Systems
and the Survival of Florida's Small Farmers. Florida Journal of Anthropology,
8(2, pt. 2):37-65.

Zimet, David, and Thomas Spreen and Christina Gladwin
1983 Beef Cattle Production in Jefferson County, Florida. Food and Resource
Economics Department, University of Florida, Gainesville.

Zulauf, Carl
1984 Changes in U.S. Agriculture During the 1970s: An Examination of Farm Size
Measured by Constant Dollar Sales Categories. Ohio State University.




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