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Record W162871375 · doi:10.5206/cie-eci.v43i2.9251

‘South-South’ Borrowing: Lessons from the Caribbean and implications for post 2015 agenda

2014· article· en· W162871375 on OpenAlexaffvenue
Elaine Lam

Bibliographic record

VenueComparative and International Education · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRealmAbandonment (legal)Best practicePolitical scienceRhetoricDeveloping countryEconomic growthPsychological interventionPublic relationsPublic administrationEconomicsPsychology

Abstract

fetched live from OpenAlex

This article aims to draw attention to complexities of ‘education borrowing’ and outline considerations for setting education goals beyond 2015, the projected expiry date for Education for All goals. While policies from multilateral agencies advocate sharing best practices between developing nations to support improvements to quality education, qualitative research in Barbados and Trinidad & Tobago indicates that best practices are not shared nor implemented. At best, foreign ideas from industrialized countries are used to legitimize local policies. It appears that directives aimed at fostering ‘South-South’ cooperation do not account for cultural differences. Findings also suggest a lack of cross-national attraction as developing nations are more concerned about ‘international standards’. Policy development considerations for 2015 include a stronger emphasis on identifying locally driven approaches and goals in place of ‘South-South’ borrowing rhetoric. Abandonment of a common realm of values is not necessary; however the reduction of interventions by multilateral agencies may be a worthwhile goal for post 2015.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.468

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 studies0.0010.000
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 head0.197
GPT teacher head0.486
Teacher spread0.289 · 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 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

Citations0
Published2014
Admission routes2
Has abstractyes

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