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Record W2919328640 · doi:10.2166/wp.2019.154

Women, irrigation and social norms in Egypt: ‘The more things change, the more they stay the same?’

2019· article· en· W2919328640 on OpenAlex

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

VenueWater Policy · 2019
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsWestern University
Fundersnot available
KeywordsIrrigationGovernment (linguistics)BusinessPolitical scienceSocioeconomicsEconomic growthSociologyEconomics

Abstract

fetched live from OpenAlex

Abstract This paper explores how women and men participate in irrigation activities in Egypt, drawing from a survey administered to 200 men and 202 women and qualitative information from 150 interviews. Women participated in irrigation activities in 78% of the 402 households surveyed, suggesting that women are far more actively engaged in irrigation efforts in Egypt, and possibly in the wider MENA region, than is generally assumed. The diffusion of certain irrigation technologies such as drip, sprinkler and tatweer in recent years has made irrigation more socially acceptable for women to perform although some women had also been irrigating land long before these technologies became available. We identify land ownership, educational attainment, institutional support from government, donors and NGOs, and access to training in irrigational technologies as factors that enable women to optimally undertake irrigation. These factors enabled women to participate meaningfully in public institutions related to irrigation, such as water user associations (WUAs). Finally, we discovered that desire and ability to participate in WUAs declined dramatically for both women and men when institutional support was withdrawn or eroded. Thus, the paper concludes that we must look at a variety of social categories and relationships to understand women's involvement in irrigation and to identify ways to strengthen 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)0.000
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 score0.917
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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