Drilling through Conservation Policy: Oil Exploration in Murchison Falls Protected Area, Uganda
Bibliographic record
Abstract
Approximately 2.5 billion barrels of commercially-viable oil, worth $2 billion in annual revenue for 20 years, were discovered under the Ugandan portion of the Albertine Rift in 2006. The region also contains seven of Uganda's protected areas and a growing ecotourism industry. We conducted interviews and focus groups in and around Murchison Falls Protected Area, Uganda's largest, oldest, and most visited protected area, to assess the interaction of oil exploration with the three primary conservation policies employed by Uganda Wildlife Authority: protectionism, neoliberal capital accumulation, and community-based conservation. We find that oil extraction is legally permitted inside protected areas in Uganda, like many other African countries, and that the wildlife authority and oil companies are adapting to co-exist inside a protected area. Our primary argument is that neoliberal capital accumulation as a conservation policy actually makes protected areas more vulnerable to industrial exploitation because nature is commodified, allowing economic value and profitability of land uses to determine how nature is exploited. Our secondary argument is that the conditional nature of protected area access inherent within the protectionist policy permits oil extraction within Murchison Falls Protected Area. Finally, we argue that community-based conservation, as operationalized in Uganda, has no role in defending protected areas against oil industrialisation.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".