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Record W2603415174 · doi:10.3138/jcfs.38.2.307

Labour Division and Family Cohesion among Bedouin Flock Raiser Households in Scattered Rural Settlements in the Negev Desert, Southern Israel

2007· article· en· W2603415174 on OpenAlexvenueno aff
Ilan Stavi, Gideon M. Kressel, Yitzchak Gutterman, A. Allan Degen

Bibliographic record

VenueJournal of Comparative Family Studies · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFlockHuman settlementSocioeconomicsGeographyLivelihoodSociologyAgricultureEcologyArchaeologyBiology

Abstract

fetched live from OpenAlex

There are approximately 8,000 Bedouin families living in scattered rural settlements (also known as spontaneous hamlets) in the Negev desert, southern Israel, and about a thousand of these raise sheep and goats for their livelihood. These families are considered to be on the economic margins of Israeli society, in that analyses of Bedouin flock raising have shown marginal profitability and even losses. Why then do these families continue raising sheep and goats? The aim of this study was to examine the reasons for the maintenance of the flocks, focusing on genealogical and labour division issues. Data were collected using participant observation and structured interviews from 24 families living in such scattered settlements and raising flocks. Flocks were divided into small, medium and large, with 8 flocks in each group. Results showed a clear division of labour tasks related to the flock between sexes and among generations. The flock functioned as a cohesive factor among family members due to the mutual work and responsibility to the flock imposed on each family member. Reciprocal commitment and loyalty among family members was strengthened as a consequence of the division of flock ownership among them.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.092
GPT teacher head0.370
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2007
Admission routes1
Has abstractyes

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