Introduction and Assessment of a Socio-Economic Mine Closure Framework
Bibliographic record
Abstract
This paper introduces and assesses the Socio-Economic Mine Closure Framework. The Framework assessment included an online survey distributed to 151 experts, and a field investigation, conducted in Mongolia, in which the local community was invited to participate. A key objective of the case-study was to identify and assess the community investment initiatives implemented by a mining company. The fieldwork also aimed to assess the perceptions of local residents about the success of these initiatives. The study indicates that it would be relevant, timely and appropriate for the mining industry to adopt the proposed Framework. The case-study analysis found that several initiatives were implemented and supported by the company, but that the company’s relationship to local governments was deemed to be too close and as such, was found to overshadow many of its initiatives. This situation resulted in a lack of awareness on the part of local residents regarding the community investments made by the company. Some of the programs available to the community, such as the microcredit program, would need to be reviewed because of a lack of transparency and limited accessibility. Furthermore, local residents expect a greater focus on the development of small businesses and job creation. The engagement and participation of local residents is limited, andlocal residents want to have a say in the decisions that affect the community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".