Review of the environmental oversight framework in Kenya, in light of a nuclear power programme
Bibliographic record
Abstract
By means of an Environmental Impact Assessment (EIA), environmental impacts associated with Nuclear Power Plants (NPPs) can be identified and evaluated. International approaches and guidelines indicate that nuclear newcomer countries such as Kenya need to ensure that the national legal and regulatory framework for environmental protection accounts for the unique safety and environmental aspects of such an endeavor. In particular, existing laws may require amendment and/or supplement. Moreover, the responsibilities of the environmental agency and nuclear regulatory body, in environmental oversight of NPPs will need to be legally defined in order to prevent overlapping of responsibilities and to minimize the potential for project delay. Case histories of countries with advanced nuclear power programmes were performed to identify strategies which align with best environmental management practices, as relevant to newcomer countries such as Kenya. A review of the environmental assessment framework for United States and Canada indicates similar approaches whereby the nuclear regulatory body has the sole responsibility in EIA. However, in Sweden, NPPs are required to receive authorisation from the Radiation Safety Authority as well as from an environmental court. Kenya has an existing environmental protection framework, and as a standard requirement, a nuclear regulatory body will be designated to regulate NPPs in order to ensure protection of people and the environment. In light of a nuclear power programme, a review of the national legal framework in Kenya should be done in order to ascertain if amendment and/or supplement of the environmental law and supporting regulations is required. Moreover, in order to ensure effective environmental regulation of NPPs, the responsibilities of the environmental agency and nuclear regulatory body need to be legally defined in order to prevent overlapping of responsibilities. This paper also suggests two alternative structures for the EIA process and authorisation for NPPs in Kenya.
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| 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".