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Record W4312017153 · doi:10.1515/eduling-2022-0008

Slicing the onion: reflections and projections on language education policy in the Caribbean

2022· article· en· W4312017153 on OpenAlexfundno aff
Shondel Nero

Bibliographic record

VenueEducational Linguistics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
FundersYork UniversityCouncil for International Exchange of Scholars
KeywordsCreole languageColonialismFraming (construction)IdeologyLanguage policyCraftSociologyPolitical scienceHistoryPoliticsLinguisticsPedagogyLawArchaeology

Abstract

fetched live from OpenAlex

Abstract The history of plantation slavery and European colonization in the Caribbean has left in its wake a rich and complex linguistic landscape, a colonial education structure, and a set of contradictory (creole/colonial) identities and language attitudes that make it fertile ground for a critical examination of language education policy development in the region. Using Jamaica, a former British colony as an illustrative case, this article takes a critical look at the historical and current framing and development of the multilayered “onion” that is language education policy in the Caribbean – a uniquely creole/colonial region with conflicting language ideologies. I examine the goals, actors, processes, and challenges and possibilities of LEP implementation (Nero, Shondel. 2018. Challenges of language education policy development and implementation in Creole-speaking contexts. In Jodi Crandall & Kathleen Bailey (eds.), Global perspectives on language education policies , 205–218. New York: Routledge and TIRF – The International Research Foundation), and also look ahead, recommending ways that we might craft viable 21st century education and LEP goals for the Caribbean and other former colonies around the world, given their colonial legacy and transnational present and future.

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)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.894
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
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 head0.069
GPT teacher head0.514
Teacher spread0.445 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

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