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The Women's Empowerment in Agriculture Index

2013· report· en· W4213192306 on OpenAlexfundno aff
Sabina Alkire, Ruth Meinzen‐Dick, Amber Peterman, Agnes Quisumbing, Greg Seymour, Ana Rita Vaz

Bibliographic record

VenueUniversity of Oxford · 2013
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Practices
Canadian institutionsnot available
FundersBundesministerium für Wirtschaftliche Zusammenarbeit und EntwicklungAustralian Agency for International DevelopmentGeorg-August-Universität GöttingenUniversity of OxfordInternational Development Research CentreEconomic and Social Research CouncilInternational Fine Particle Research InstituteYale UniversityUnited Nations Development ProgrammeRobertson FoundationUNICEF
KeywordsEmpowermentIndex (typography)AgricultureAgricultural economicsEconomicsGeographyEconomic growthComputer scienceWorld Wide WebArchaeology

Abstract

fetched live from OpenAlex

The Women's Empowerment in Agriculture Index (WEAI) is a new survey-based index designed to measure the empowerment, agency, and inclusion of women in the agricultural sector.The WEAI was initially developed as a tool to reflect women's empowerment that may result from the United States government's Feed the Future Initiative, which commissioned the development of the WEAI.The WEAI can also be used more generally to assess the state of empowerment and gender parity in agriculture, to identify key areas in which empowerment needs to be strengthened, and to track progress over time.The WEAI is an aggregate index, reported at the country or regional level, based on individual-level data collected by interviewing men and women within the same households.The WEAI comprises two subindexes.The first assesses the degree to which women are empowered in five domains of empowerment (5DE) in agriculture.It reflects the percentage of women who are empowered and, among those who are not, the percentage of domains in which women enjoy adequate achievements.These domains are (1) decisions about agricultural production, (2) access to and decisionmaking power about productive resources, (3) control of use of income, (4) leadership in the community, and (5) time allocation.The second subindex (the Gender Parity Index [GPI]) measures gender parity.The GPI reflects the percentage of women who are empowered or whose achievements are at least as high as the men in their households.For those households that have not achieved gender Alkire, Meinzen-Dick, Peterman, Quisumbing, Seymour and Vaz The Women's Empowerment in Agriculture Index parity, the GPI shows the empowerment gap that needs to be closed for women to reach the same level of empowerment as men.This technical paper documents the development of the WEAI and presents pilot data from Bangladesh, Guatemala, and Uganda, so that researchers and practitioners seeking to use the index in their own work would understand how the survey questionnaires were developed and piloted, how the qualitative case studies were undertaken, how the index was constructed, how various indicators were validated, and how it can be used in other settings.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.015
GPT teacher head0.193
Teacher spread0.178 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations128
Published2013
Admission routes1
Has abstractyes

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