Bibliographic record
Abstract
Indigeneity has, for the most part, been absent in literature on the Caribbean, even in de-colonial writing. Writing on the Caribbean has often portrayed Indigenous people as extinct and thus as irrelevant to contemporary life in the Caribbean. Yet Indigenous peoples have played and continue to play a central role in Caribbean politics. This essay discusses how and why Indigenous people have been erased from discourse on the contemporary Caribbean. I argue that Indigenous erasure is a longstanding colonial tactic that is still used to justify the dispossession of Indigenous peoples. Drawing on the case of the Maya peoples’ struggle for land in Belize, I describe some of the ways that Indigenous people continue to resist colonial and capitalist violence. Having identified and historicized the myth of Indigenous erasure in the Caribbean, I begin to sketch possibilities for shifting the discourse on the Caribbean such that it highlights rather than ignores the historical and ongoing contributions of Indigenous communities to the Caribbean. I suggest that diaspora and entanglement are two concepts that may be helpful for clarifying the Caribbean’s complex colonial histories in a way that underscores the importance of Indigenous peoples to the Caribbean.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.026 | 0.027 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".