New Colonial Masters, Malaysian Loggers in South America: How Under-Valuation of Forest Resources Exposes Guyana to Unscrupulous Exploitation
Bibliographic record
Abstract
We provide an example from Guyana of how government negligence (or worse) and a weak and inattentive civil society have enabled Samling, a Malaysian multinational logger operating locally from 1991 under the name of the Barama Company, to run down its plywood mills and to shift decisively into log exports for major markets in China and India, while paying derisory sums in forest fees and evading the taxes levied on local enterprises. We suggest some reasons why Guyana’s forest governance administration is weak in spite of externally funded institutional strengthening projects. We use data from Samling’s Initial Public Offering (IPO) to compare the logging costs and forest taxes paid by the company in more strongly administered Sarawak, Malaysia versus weakly administered Guyana. We show how the logging company does not comply with its Foreign Direct Investment (FDI) agreement, but instead has high graded its concession of a few hard heavy timbers in demand in Asian wood processing factories. We suggest ways in which Guyana could obtain net social benefit from its natural forest.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".