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Record W2898576564

Wells and Well-being in South India: Gender dimensions of groundwater dependence

2018· article· en· W2898576564 on OpenAlexfundno aff
Divya Solomon, Nitya Rao

Bibliographic record

VenueUEA Digital Repository (University of East Anglia) · 2018
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsnot available
FundersUniversity of CambridgeInternational Development Research CentreDepartment for International DevelopmentGovernment of the United Kingdom
KeywordsLivelihoodGroundwaterAgrarian societyGeographyEconomic shortagePsychological resilienceWater resource managementAgricultureEnvironmental planningSocioeconomicsNatural resource economicsSociologyEconomicsEnvironmental sciencePsychology
DOInot available

Abstract

fetched live from OpenAlex

Groundwater has played a pivotal role in transforming the rural agrarian landscape, augmenting rural livelihoods and improving household wellbeing. Through our research, we attempt to understand how the growing prevalence and importance of groundwater has impacted intra household relations, in particular the gendered divisions of labour, and use of assets. Further, we explore the impacts of failed borewells on gendered vulnerabilities, identities and wellbeing. Our research indicates that groundwater usage in semi-arid regions has increased the short-term resilience of communities in the region, but simultaneously increased gendered risks, especially for small-holders, by promoting unsustainable livelihood trends and risky coping strategies to groundwater shortages.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.151
Teacher spread0.144 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2018
Admission routes1
Has abstractyes

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