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Record W2477304870 · doi:10.1080/14616742.2016.1191791

“Empowerment” as efficiency and participation: gender in responsible agricultural investment principles

2016· article· en· W2477304870 on OpenAlexaff
Andrea M. Collins

Bibliographic record

VenueInternational Feminist Journal of Politics · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Waterloo
FundersInternational Fund for Agricultural Development
KeywordsEmpowermentFood securityEconomic growthWomen's empowermentAgricultureAgricultural productivityCorporate governanceEconomicsProductivityPolitical scienceSociologyFinance

Abstract

fetched live from OpenAlex

Amidst global concern over the state of transnational large-scale agricultural investments, several efforts have been made to set global standards for “responsible agricultural investment.” While these efforts have received mixed reviews from the international community, very little attention has been paid to the gendered language of these principles. Through examining two separate sets of agricultural investment principles – one created by the United Nations Food and Agriculture Organization (FAO), the United Nations Conference on Trade and Development, the International Fund for Agricultural Development and the World Bank, and the other by the United Nations Committee on World Food Security – this article finds that, despite different processes and participants in the creation of these principles, they nonetheless share a language of “empowerment” targeted at women and marginalized groups. However, in contrast to early feminist discourses of empowerment, these principles instead perpetuate the notion that empowerment is to be found through efficiency, productivity and participation in land and labor markets. This article takes a critical look at this language of economic empowerment in each set of principles, and points to the dangers of equating efficiency, productivity and participation with feminist empowerment. By not acknowledging the broader gender dynamics of agricultural governance and markets, these discourses risk deepening existing inequalities rather than moving toward meaningful social change.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.172

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 head0.035
GPT teacher head0.279
Teacher spread0.245 · 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

Citations17
Published2016
Admission routes1
Has abstractyes

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