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Record W2320142587 · doi:10.1080/09540253.2016.1149554

Feminist pedagogy and social change: the impact of the caribbean institute in gender and development

2016· article· en· W2320142587 on OpenAlexaff
Charmaine Crawford, Fatimah Jackson-Best

Bibliographic record

VenueGender and Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPraxisDialogicGender studiesSociologyFeminismTransformative learningGender analysisFeminist pedagogyExperiential learningSocial changePedagogyGender and developmentCitizen journalismPolitical scienceSocial transformation

Abstract

fetched live from OpenAlex

This paper examines the utility of a feminist pedagogical framework in establishing and organising the Caribbean Institute in Gender and Development (CIGAD), which is a biennial intensive gender and development training programme that has taken place in Barbados since 1993. To highlight the major impact that CIGAD has had in educating and empowering Caribbean men and women, the authors will first discuss the importance of feminist pedagogies in teaching, learning and activism in this programme by locating them within an intersectional postcolonial/transnational framework. Secondly, the authors consider the ways in which feminist pedagogy and praxis have been central in training women and men in the Caribbean region in gender analysis, helping them recognise the important role gender plays in development planning and policy as well as how it can be integrated into their work to improve their communities. Finally, through a feminist dialogic, participatory and experiential approach, the authors assess the impact that the CIGAD has had on participants, and community development training will be discussed based on the monitoring and evaluation of the exercise completed in 2014.

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)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0160.023
Scholarly communication0.0090.002
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.081
GPT teacher head0.368
Teacher spread0.287 · 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 designQualitative
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

Citations7
Published2016
Admission routes1
Has abstractyes

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