Beyond the blood, the beach & the banana: new perspectives in Caribbean studies
Bibliographic record
Abstract
Beyond the Blood, the Beach and the Banana emphasises the significance of the Caribbean in an increasingly globalised social world and draws attention to the contribution that scholarship in Caribbean Studies makes in coming to terms with a multi-cultural heritage. The compilation deliberately ranges in focus across periods, geographies, linguistic divisions and subject matter to present the fruition of significant research projects by 25 researchers from the Caribbean, North America and Europe. Contributors on the Hispanic, Dutch, African, Indian and Anglophone Caribbean juxtaposed with work on the Caribbean diasporas of the USA, UK, Canada and the Netherlands enrich the text with multiple perspectives. Cogently written with a comprehensive bibliography accompanying each chapter, the book strategically examines the Caribbean and its diasporas by dividing the analysis into methodological considerations; history; migration; governance and politics; visual and material culture; and literature. Beyond the Blood, the Beach and the Banana is an essential read for those beginning or undertaking research in Caribbean Studies and for those interested in the historical roots of European and North American contemporary societies.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".