Bibliographic record
Abstract
Guyana is a racially an ethnically plural society comprising six race groups, the relations among whom colour societal outcomes. The race groups comprise Blacks, East Indians, Amerindians, Chinese, White/Portuguese and Mixed. Though ethnic groups often coincide with race groups in the society they are in fact more numerous. Within the East Indian race group for example, there are Hindus and Muslims each forming a distinct ethnic group. The nine Amerindian tribes in Guyana while comprising a single race group can be considered to be ethnically different. Among Blacks, Rastafarians have an ethnic character of their own. Ethnicity and race combine to provide the Guyana society with its essentially plural character. This plurality on the one hand has contributed to the richness and diversity of Guyanese culture and institutions. On the other hand it has been a source of tension and torment, particularly between the majority East Indians and Blacks, induced by mistrust, prejudice and discrimination with concomitant negative impacts on political, social and economic development of the nation. In this paper I focus on the relationships between race and development of the nation.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.031 | 0.018 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".