Ownership and Control of Natural Resources under the Nigerian Constitution 1999 and Its Implications for Environmental Law and Practice
Bibliographic record
Abstract
The right to ownership and control of natural resources under the Nigerian law is constitutional. The Constitution of the Federal Republic of Nigeria 1999 (as amended) section 44 (3) and item 39 Schedule II of the Exclusive Legislative List vests the control and management of the natural resources and hydrocarbon operations on the federal government for the common good and benefit of the citizens. This article aims at examining the constitutional provisions and its implications for environmental law and practice. It examines some theories of ownership of mineral resources and analyses the decisions of the Supreme Court of Nigeria on the subject, particularly the case of Attorney-General of the Federation v. Attorney General of Abia State & 35 Others (No. 2) (2002) 6 NWLR (Part 764) 542 where the Supreme Court of Nigeria made several judicial pronouncements on the constitutional question of the derivation principle and ownership and control of natural resources in the Nigeria Federation. This article concludes by advocating for reforms and further research on the subject matter. It recommends the adoption of what is obtainable in other jurisdictions like Canada and South Africa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".