Guyana’s Racial Politics: Causes, Issues, and its Welcoming of Western Neocolonialism
Bibliographic record
Abstract
This paper discusses the history of ethnopolitics in Guyana and how the racial divide between the two largest ethnic groups in the country—the Indo-Guyanese and Afro-Guyanese—not only fractured society but allowed for Western superpowers to exert neocolonial influence. It explores the historical origins of race relations between the Indians and Africans in Guyana from the time of British colonization to the modern political era of the 196 0s. It looks at how politics was utilized both as unifying factor and a dividing factor—dependent on the goals the political leaders sought after. This article breaks down the ever-complicated political parties and their general history and discusses the causes of this political divide, both due to internal pressures and external forces. It also aims to show how the racial politics in Guyana were orchestrated by both the United States and Great Britain as it occurred during the ushering in of the neocolonial era. It is built around the argument that the racial divide caused by the Guyanese politics of the 1960s became the basis for the complicated modern day race relations and the various causes. The goal is to essentially tell part of the racial and political history of Guyana in a way that is accessible to everyone. Guyana is a country with such a deep history which is often times obscured, this article aims to dissect just a portion of it, especially a part that has affected and continues to affect the population and diaspora even today.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".