Government Policies and Engineers’ Roles in Facilitating Nigeria’s Transition to Circular Economy
Bibliographic record
Abstract
Abstract There are ongoing global efforts at changing from the traditional linear economy to a circular economy. Nigeria as the largest economy in Africa cannot afford to lag behind. This study evaluated potential impacts of the current Nigerian resource use and exploitation policies as well as engineering practitioners’ training and practices on Nigeria’s transition to circular economy. The study further attempted to identify changes in government policies and engineering training and practices that would be necessary to facilitate Nigeria’s successful transition to a circular economy. This paper is based on a desk and literature review, a web-based research on government policies, engineering training and engineering practices in Nigeria. Contributions of this study include provision of insights to the government officials on regulations that need to be improved to facilitate Nigeria’s transition to circular economy. It also provided agencies regulating engineering education and engineering practices in Nigeria opportunities to see areas of deficient that may need to be improved for successful transition to a circular economy
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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 | 0.000 | 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 | 0.002 |
| Open science | 0.000 | 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".