A Comparative Review of Climate Change and Sustainable Development in Canada and Nigeria: The Path to a Greener Future.
Bibliographic record
Abstract
Over the years, climate change and sustainable development have become global concerns that have attracted global attention. This is owing to the fact that human activities calculated to bring about economic growth and sustainable development have wrecked great havoc and disrupted the balance that exists between growth and the environment. It has therefore become crucial for nations to work towards a common goal which is to fight against climate change in order to achieve sustainable development.\nThis can be achieved by reducing activities that contribute to greenhouse gases in the atmosphere and to climate change. Also, countries will need to adjust their laws to accommodate enhanced policies that promote sustainability in all sectors and to hold people whose activities are likely to degrade the environment accountable for their actions.\nThis research compares Nigeria and Canada – their sustainable laws and impact assessment processes regarding oil and gas activities with the focus on climate change and sustainable development. It exposes the inadequacies present in the existing environmental impact assessment process of both Canada (a developed country) and Nigeria (a developing country) and demonstrates that Canada has been more compliant to sustainable development goals than Nigeria. It also shows that there is further room for improvement in the environmental impact assessment processes of both jurisdictions, especially pertaining to the issues of climate change, public participation, and the achievement of the sustainable development goals as agreed on by the international community. Hence, the need arises to bridge the gaps that exist between international and domestic environmental standards.\nKeywords: Climate Change, Economic Development, Emissions, Environment, Greenhouse Gases (GHGs) and Sustainable Development.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.025 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".