An Appraisal of Legal and Regulatory Frameworks for Guaranteeing Mine-Host Communities’ Right to Food in the ICGLR Sub-Region: Part I
Bibliographic record
Abstract
The ICGLR sub-region is naturally endowed with plenty of resources such as waters, forests and minerals. Such resources present a great potential to contribute towards local communities’ (mine-host communities) well-being when properly harnessed. Minerals for example which are finite by nature calls for robust legal and institutional framework if at all Mine-host communities (MHCs) are to benefit from them. Inversely however, mining is shown to plunge MHCs into poverty vicious cycle through steering civil unrest, military coup detat and massive displacement that triggers food insecurity concerns. Minerals instead of contributing towards their socio-economic advancement are instead contributing to human rights violation, in particular the right to food. This work is a product of desk review of primary documents such as; international conventions, protocols, declarations, case laws and sporadic reference to state laws. As such, the study confined itself to the ICGLR framework where protocols and declarations relevant to mineral resources, land and good governance are reviewed. Also, the study randomly picks and refers to domestic laws of respective ICGLR member states in framing up arguments. Review of primary documents is complimented by a qualitative review and analysis of secondary documents such as; journal articles, books, newspaper articles, internet sources to name but a few. The review and analysis presented in themes in this paper finds that weak legal framework in the ICGLR sub-region is contributory to gross violation of MHCs right to food. The study recommends for reforms of the ICGLR legal framework with the view to maximize the guarantee of MHCs’ right to food.
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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 | 0.039 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".