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Mining with communities

2001· article· en· W2074837079 on OpenAlexaffabout
Marcello M. Veiga, Malcolm J. Scoble, Mary Louise McAllister

Bibliographic record

VenueNatural Resources Forum · 2001
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of WaterlooUniversity of British Columbia
Fundersnot available
KeywordsVitalitySustainabilityClosure (psychology)Equity (law)Environmental planningBusinessSustainable communityEnvironmental resource managementPolitical scienceGeographyEcologyEnvironmental science

Abstract

fetched live from OpenAlex

Abstract To be considered as sustainable, a mining community needs to adhere to the principles of ecological sustainability, economic vitality and social equity. These principles apply over a long time span, covering both the life of the mine and post‐mining closure. The legacy left by a mine to the community after its closure is emerging as a significant aspect of its planning. Progress towards sustainability is made when value is added to a community with respect to these principles by the mining operation during its life cycle. This article presents a series of cases to demonstrate the diverse potential challenges to achieving a sustainable mining community. These case studies of both new and old mining communities are drawn mainly from Canada and from locations abroad where Canadian companies are now building mines. The article concludes by considering various approaches that can foster sustainable mining communities and the role of community consultation and capacity building.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0200.011
Scholarly communication0.0090.009
Open science0.0010.016
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0360.002

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.

Opus teacher head0.009
GPT teacher head0.200
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations180
Published2001
Admission routes2
Has abstractyes

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