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Record W2026384652 · doi:10.1080/13552074.2014.920992

Using the Social Relations Approach to capture complexity in women's empowerment: using gender analysis in the Fish on Farms project in Cambodia

2014· article· en· W2026384652 on OpenAlex
Emily Hillenbrand, Pardis Lakzadeh, Ly Sokhoin, Zaman Talukder, Tim Green, Judy McLean

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGender & Development · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEmpowermentFood securityLivelihoodGender analysisContext (archaeology)Gender relationsAffect (linguistics)SociologyPolitical scienceSocioeconomicsEconomic growthGender studiesGeographyEconomicsAgriculture

Abstract

fetched live from OpenAlex

Gender-analysis frameworks and tools provide a pre-designed methodology which can be used for the purposes of monitoring, evaluation, and learning, as well as for research undertaken for other reasons by planners, practitioners, and academic researchers. This article focuses on the use of Naila Kabeer's concept, the Social Relations Approach, to frame a baseline gender analysis of a food security project undertaken in Cambodia. The Fish on Farms project was designed to establish evidence of the impact of homestead food production, which included fishponds, on nutritional status, food security, food intake, and livelihoods. Integral to the objectives was the need to understand how the project activities affect gender equality and the empowerment of women. The Social Relations Approach was chosen to explore gender relations in context, and to understand better the subjective meanings of empowerment and the pathways to it.

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.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
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 head0.176
GPT teacher head0.351
Teacher spread0.175 · 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