Discovery of Oil: Community Perceptions and Expectations in Uganda’s Albertine Region
Bibliographic record
Abstract
This study was conducted to interrogate local perceptions and expectations from the discovery of oil in the Albertine Graben of Uganda. We interviewed 50 residents (30 men and 20 women) from Butiaba and Wanseko (Buliisa district), Kyehoro and Kabaale villages (Hoima district). The villages were purposively selected to have a representation of the districts in the Albertine region where Oil discovery activities are currently being implemented but also to explore any differences in perceptions that may be linked to livelihood options of the respondents. We applied narrative analysis. Overall, we observed minimal pessimism as residents expressed concerns over environmental degradation, political tensions and land conflicts following oil activities, but there was a dominance of optimism as communities envisaged that the oil industry will create employment, infrastructural development, improved access to electricity, and enhanced social status. The findings demonstrated that communities living in areas where extractive resources such as oil and gas have been discovered tend to be more optimistic with very minimal pessimism in their expectations during the phase of upstream activities of the oil value chain. The findings challenge the dominant narrative that residents where energy development and other land use changes are being implemented tend to have negative expectations -a phenomenon known as NIMBY (Not-In- My-Back-Yard). We identify the need to develop strong institutional frameworks that harness benefits from oil to improve local livelihoods without compromising the environment and enhancing participation of locals in decision making processes.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".