Bibliographic record
Abstract
Guyana has been subjected to the myth of capitalist resource extraction as “development” both as a colony and well after it gained independence. Guyana's colonial history, its history of structural adjustment, and its ongoing situation of foreign domination have all made “development” an elusive goal for the country. This article discusses why it is unlikely that oil will “develop” Guyana, and Guyanese frustration with foreign dominance in the oil and gas sector as is seen through various lawsuits raised against the government and ExxonMobil. I argue that oil presents a new opportunity in Guyana for a reignited and transformed movement for racial and national unity, which was not previously present in other extractive industries like sugar or mining. Whereas the aforementioned extractions allowed for some redistribution – via a decentralization of the power brokers in those sectors to include Guyanese – that opportunity is not present with oil. Oil extraction requires a lot more equipment and specialized knowledge – which has shut out small and local producers present in the other sectors– thus has, and will continue to, place Guyanese in confrontation with foreign capital in the oil and gas sector. Today, successful legal mobilizations in Guyana means that direct political mobilizations are unlikely to occur.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".