Barbados: Meeting the Challenge of Competitiveness in the 21st Century
Bibliographic record
Abstract
The material within these pages shows that Barbados, a Caribbean country with just over a quarter of a million people, embodies many of the classic vulnerabilities of an island with a small open economy, yet aspires to developed-country status, and is already well advanced on the road to achieving the MDG targets. Viewed in this light, this book raises the question: Is Barbados the little island that can? The authors have approached that question mainly from the point of view of international competitiveness, one of the pillars, along with macroeconomic and financial stability, required for accelerated and sustained growth. Starting with a wide-ranging macroeconomic diagnosis, this monograph examines the strengths and competitiveness challenges facing Barbados from the points of view of the institutional and private sector constraints and environment for competitiveness, labour market conditions and trade policy framework and performance. It also narrows the focus to take a sectoral perspective, examining the leading tourism industry. To convey a sense of the public-policy complexities, the book also includes a brief analysis focusing on the agricultural sector.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".