Between Elite Interests and Pro-Poor Resistance: The Nigerian Courts and Labour-Led Anti-Fuel Price Hike Struggles (1999–2007)
Bibliographic record
Abstract
Abstract Between 1999 and 2007, a popular Labour-led movement led a pro-poor struggle to resist the fuel price hike policy of the Nigerian government. Waged in the context of the poverty in which nearly 70 per cent of Nigerians lived, the operation of powerful incentives to raise fuel prices, and Labour's extraordinary socio-political leverage, these struggles triggered much government frustration. One of the strategies adopted by the government to legitimize its attempt to repress the movement was to resort to the courts. This article analyses, from a socio-legal perspective, the key cases relating to the validity of the government's attempts to repress the struggles. The article concludes that, although both pro- and anti-movement trends can be observed in the jurisprudence, the anti-movement tendency having so far prevailed in terms of formal legal precedent, the pro-movement (ie pro-poor) decisions have, as a result of their massive popular legitimacy, actually functioned as the “living law.”
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".