A roadmap for ESIA policy change in Ethiopia should address wide-ranging governance reforms
Bibliographic record
Abstract
Robust governance frameworks are crucial for maximizing the benefits of natural resource development in mining regions and minimising adverse social and environmental impacts. This paper analyses Ethiopia’s current ESIA policy, legal framework and implementation process to identify opportunities for policy reform. To gain perspective on leading practices in other countries, a comparative analysis of policies in Chile, Peru, Ghana, and Canada was performed. Interviews with representatives from government, industry, and civil society in Ethiopia were completed to gain perspective on the policy structures currently in place, and to identify areas for improvement. Results conclude that accountability mechanisms are currently limited in Ethiopia and that at the time of this study, the same authority was responsible for promoting mining and evaluating ESIAs. Contrary to legislative requirements, there was found to be a lack of transparency in the public availability of ESIAs and limited community participation. Compliance and monitoring processes were also found to be inadequate. Addressing these gaps is important to ensure that the expansion of Ethiopia’s mining sector proceeds in a sustainable manner.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".