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Record W2973623020 · doi:10.1177/0268580919865103

Decolonizing microfinance: An Indigenous feminist approach to transform macro-debit into micro-credit

2019· article· en· W2973623020 on OpenAlexaff
Jacqueline M. Quinless, Francis Adu-Febiri

Bibliographic record

VenueInternational Sociology · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsCamosun CollegeUniversity of Victoria
Fundersnot available
KeywordsMicrofinanceOppressionSociologyIndigenousGrassrootsGender studiesFeminismPovertyNeoliberalism (international relations)ColonialismSocial sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Nancy Fraser’s theoretical critique of feminism’s unintended facilitation of neoliberal capitalism discusses the reproduction of poverty at the grassroots among Indigenous women. This article situates the discussion in gendered colonialism to show the ways that microfinance is actually a form of structured colonization and gender oppression. The authors argue that neither the emerging literature on microfinance nor Nancy Fraser’s theory provides Indigenous women a practical way out of the existing oppressive structures of microfinance practice. Rather, they suggest that these ideas are better understood through talking circle conversations with local Indigenous women food producers in Ghana. Through conversations, the authors learned about how these women are actively decolonizing and indigenizing microfinance and what Corntassel has described as everyday acts of resurgence and renewal within native communities. The authors reason that racialized, capitalist, gender oppression can be overcome by decolonial feminism.

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)0.003
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.021
Scholarly communication0.0030.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.018
GPT teacher head0.268
Teacher spread0.250 · 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
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

Citations5
Published2019
Admission routes1
Has abstractyes

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