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Record W4381568675 · doi:10.33137/cq.v7i1.40016

Indigenous Erasure and Resistance in the Caribbean

2023· article· en· W4381568675 on OpenAlexaffvenue
Elizabeth Wong

Bibliographic record

VenueCaribbean Quilt · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCaribbean history, culture, and politics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsErasureIndigenousResistance (ecology)EthnologyGeographySociologyAnthropologyComputer scienceEcologyBiology

Abstract

fetched live from OpenAlex

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 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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.030
GPT teacher head0.297
Teacher spread0.267 · 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
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

Citations0
Published2023
Admission routes2
Has abstractyes

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