Compliance with the Requirements of the Environmental Impact Assessment Guidelines in Zimbabwe: A Case Study
Bibliographic record
Abstract
This research set out to find out how well projects are complying with the requirements of the Environmental Impact Assessment Guidelines in Zimbabwe. Data was collected from EIA reports completed between 2007 and 2012. Questionnaires and interviews were used to collect the experiences of practitioners in the EIA sector. The results show that EIA reports contain below 65% of required information for decision making. Critical sections of the EIA report are the most deficient. Compliance varies significantly between consultants, stage of EIA process and size of project. Recommendations are: need to review and expand the existing guidelines and promote their use, building objectivity into the EIA report review process, upholding professional standards of practice for the consultants, improvement of compliance monitoring and enforcement, the use of economic incentives and disincentives other than enforcement to promote compliance, increased awareness raising of EIA in the business sector, and increased political will and transparency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".