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Record W3102159928 · doi:10.1017/9781108555791.024

Sustainable Mining, Environmental Justice, and the Human Rights of Women and Girls

2021· book-chapter· en· W3102159928 on OpenAlexaff
Sara L. Seck, Penelope Simons

Bibliographic record

VenueCambridge University Press eBooks · 2021
Typebook-chapter
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsIndigenousNatural resourceSustainable developmentEconomic JusticeEnvironmental planningNatural (archaeology)Resource (disambiguation)Scale (ratio)BusinessEnvironmental justicePolitical scienceEnvironmental resource managementGeographyEcologyLawEconomics

Abstract

fetched live from OpenAlex

Resource extraction of minerals and metals is often touted as a pathway to sustainable development, especially for poor countries and communities of the Global South. While large-scale mining projects can bring with them certain benefits, and opportunities, they can also have significant detrimental impacts, particularly for Indigenous communities, who “often rely on natural resources that mining activities disrupt, threaten, or poison, and [who] have cultural and spiritual relationships to landscapes that may be destroyed or degraded.” For industrial mining to meet accepted understandings of sustainable development, it must be responsive to the concerns of local communities, including Indigenous peoples, and women, who must all have the opportunity to choose to actively participate in, and benefit from, mining development.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.990
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.155
Teacher spread0.148 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2021
Admission routes1
Has abstractyes

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