Mining amid decentralization. Local governments and mining in the Philippines
Bibliographic record
Abstract
In recent years, as part of its neoliberal development paradigm, the Government of the Philippines has engaged in efforts to encourage extraction of the nation's mineral resources. The Philippines is also a country where decentralization has devolved substantial powers to local governments. Concern over potentially adverse environmental effects has led to opposition to mining by some local governments in the Philippines. This opposition has led to the withholding of consent to mining projects by local governments and, in some cases, the implementation of moratoriums banning mining. Central to this opposition have been the activities of civil society groups, and their collaboration with local governments. This collaboration has involved the drafting of legislation prohibiting mining and support of candidates for office who are opposed to mining. Collectively, Filipino local governments and civil society groups are examples of the concept of governance, a dispersed process wherein society manages itself for the betterment of all its members. For mining companies seeking to implement projects, it is no longer sufficient to have the consent of the national Government — that of local governance forces must also be considered.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".