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Record W2047197531 · doi:10.1353/cub.2011.0024

Oxfam Canada in Cuba: Gender Injustice, a Key Obstacle to Development

2011· article· es· W2047197531 on OpenAlexaboutno aff
Patricia Daniel

Bibliographic record

VenueCuban studies · 2011
Typearticle
Languagees
FieldSocial Sciences
TopicCuban History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsGender equalityInjusticePolitical scienceGender equityWork (physics)Gender studiesSociologyEconomic growthLawEngineering

Abstract

fetched live from OpenAlex

La igualdad de género ha sido entre los principios fundamentales del programa de Oxfam en Cuba desde 1997. Como cabeza del programa, Oxfam Canada, entre otras actividades en el programa, ha apoyado cursos a nivel de posgrado en estudios de la mujer en Holguín, en el este de Cuba; ha ayudado financiar publicaciones; y ha patrocinado congresos internacionales bianuales auspiciado por la Universidad de La Habana. Después del VII Taller Internacional "Las Mujeres en el Siglo xxi," que se llevó a cabo en La Habana, en mayo de 2009, Marian de Vries y Beat Schmid respondieron a las preguntas de Patricia Daniel acerca del trabajo de Oxfam Canada relacionado con la igualdad de género en Cuba, y Elaine Henderson actualizó las respuestas en el verano de 2011.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.980
Threshold uncertainty score0.511

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.003
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.000

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 head0.175
GPT teacher head0.333
Teacher spread0.159 · 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 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

Citations4
Published2011
Admission routes1
Has abstractyes

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