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Record W4413098883 · doi:10.1139/facets-2025-0039

Perceptions of reclamation success as “as close as possible to the pre-mining state” undermine public participation and Indigenous consent in mineral governance

2025· article· en· W4413098883 on OpenAlexafffundvenueabout
Krystal Isbister, Liza Piper, Simon M. Landhäusser

Bibliographic record

VenueFACETS · 2025
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsYukon UniversityUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of AlbertaWeston Family FoundationPolar Knowledge Canada
KeywordsLand reclamationIndigenousPublic participationCorporate governanceState (computer science)Political scienceGold miningPublic relationsEnvironmental planningEnvironmental resource managementBusinessGeographyEnvironmental scienceEcologyArchaeologyComputer science

Abstract

fetched live from OpenAlex

Indigenous peoples and local communities in mineralized regions are under increasing pressure to support mining on their lands. The promise of reclamation is commonly used to help secure support for a project, yet proposed reclamation outcomes are often vague during impact assessment. We asked how local understandings of reclamation success interact with deliberations on whether to support a proposed mine through a case study in the Yukon Territory, Canada. We conducted a qualitative content analysis of written submissions by Yukon people and organizations to public engagements about mining from 2010 to 2021. We found Yukoners require “proper” reclamation for approval of mining and conceptualized success as “as close as possible to the pre-mining state”. We problematize the concept of “reclamation as reversal” as it (falsely) implies that mining is a reversible process. We further demonstrate how reclamation as reversal appears ethically responsible but constrains Indigenous self-determination in decision-making and can create artificial agreement on goals. We conclude that a robust understanding of realistic reclamation outcomes is required during impact assessment for meaningful public participation and for Indigenous peoples to provide/withhold consent. To achieve this, local engagement on reclamation must be premised on transformational change to landscapes, not a return to a past state.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score0.289

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 head0.016
GPT teacher head0.283
Teacher spread0.268 · 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 designObservational
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

Citations2
Published2025
Admission routes4
Has abstractyes

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