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Record W4412689204 · doi:10.5772/intechopen.1011464

The Caribbean Certificate of Secondary Level Competence in Context: Local Adaptations and Global Lessons

2025· book-chapter· en· W4412689204 on OpenAlexaboutno aff
Viola Rowe

Bibliographic record

VenueEducation and human development · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCertificateCompetence (human resources)GeographyPsychologyComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

This chapter discusses the Caribbean Certificate of Secondary Level Competence (CCSLC) programme, its justification in the context of the Caribbean region, and how it compares to the Curriculum for similar grades in other contexts, such as Australia, Canada, the United Kingdom, and the United States of America. The CCSLC programme was developed by the Caribbean Examinations Council (CXC) in response to a call by the Caribbean Common Market (CARICOM), heads of governments for a foundational programme to better prepare students at the lower levels of secondary school (Grades 7–9) for them to perform better at higher Grades and the Caribbean Secondary Education Certificate (CSEC) examination. CCSLC is adapted across several Caribbean countries. Guyana embraced the programme in 2024 and continues to prepare teachers and school administrators as the country advances to full implementation. Ninety-two per cent of the 73 schools trained thus far have implemented the programme. Implementation challenges include the lack of training, the need for retraining, the scarcity of specialist teachers, and limited material resources. This chapter also highlights teachers’ perspectives on adapting to Guyana’s context and finds that there is widespread buy-in for the programme’s implementation due to its potential to improve students’ performance. To retain teachers’ enthusiasm for supporting the programme and ensuring effective delivery and intended educational outcomes, an expanded support system is recommended.

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: Other · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.936

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 head0.139
GPT teacher head0.375
Teacher spread0.236 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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