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Record W4410632657 · doi:10.22215/etd/2025-16359

A Feminist Analysis of Social Impact Investments: Implications for Food Sovereignty and Social Reproduction in Rural Senegal

2025· dissertation· en· W4410632657 on OpenAlexafffundabout

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of CanadaConsortium of International Agricultural Research CentersGovernment of CanadaUnited States Agency for International DevelopmentForschungsinstitut für biologischen LandbauGlobal Affairs Canada
KeywordsFood sovereigntyReproductionSocial reproductionSovereigntyDevelopment economicsPolitical scienceSociologyEconomicsEconomic growthGender studiesGeographyFood securitySocial scienceSocial capitalAgricultureEcologyBiologyLaw

Abstract

fetched live from OpenAlex

This thesis research explores the program Adaptation and Valorization for Entrepreneurship in Irrigated Agriculture (AVENIR); funded by the Government of Canada and Mennonite Economic Development Assistance (MEDA). The program operates in Sedhiou and Tambacounda, Senegal, and aims to empower women in rural food systems. Foreign aid programs targeting gendered empowerment, otherwise known as social impact investments, are financial mechanisms that require investigation. Grounded in a decolonial feminist analysis, this thesis investigates food sovereignty, social reproduction, and social-ecological reproduction. Semi-structured interviews discuss the challenges of foreign imposition, agricultural programs and the future of agroecology. A critical policy analysis (CPA) discusses AVENIR policies and frameworks, offering gaps in the program, its potential consequences and avenues for development. Interview contributions illuminate potential paths forward for Canadian-funded programs and the future of food systems in Senegal. The insights feed into community participation and consultation, agroecological methods, and knowledge-sharing practices.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.055
GPT teacher head0.330
Teacher spread0.275 · 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.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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