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Record W1991784046 · doi:10.3152/146155109x465931

The Victor Diamond Mine environmental assessment process: a critical First Nation perspective

2009· article· en· W1991784046 on OpenAlexaffabout
Graham S. Whitelaw, Daniel D. McCarthy, Leonard J. S. Tsuji

Bibliographic record

VenueImpact Assessment and Project Appraisal · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsUniversity of WaterlooQueen's University
Fundersnot available
KeywordsContext (archaeology)Environmental planningGovernment (linguistics)Environmental impact assessmentFirst nationPolitical scienceEnvironmental resource managementGeographyEnvironmental protectionPublic administrationArchaeologyLawEnvironmental scienceIndigenous

Abstract

fetched live from OpenAlex

Restrictive scoping has emerged as a contentious issue in environmental assessment (EA) with developments in northern Canada on Aboriginal territorial homelands. Restrictive scoping potentially leads to the exclusion of potentially affected stakeholders, constrained impact assessment, and inadequate collection of baseline information and traditional knowledge. The First Diamond Mine in Ontario, Canada, is located on the Attawapiskat River in the western James Bay region. We examined whether the scoping applied in the EA process that led to the approval of the mine addressed the needs of First Nations located southeast of the mine, specifically Fort Albany First Nation on the Albany River. Our findings indicate that the proponent, De Beers Canada Inc., with the approval of government authorities, primarily consulted and worked with Attawapiskat First Nation through the EA process and largely excluded other First Nations in the region. Limitations of EA in the context of northern Canada are identified. The potential of emerging community-based and regional land use planning in Ontario's far north is discussed.

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)0.056
metaresearch head score (Gemma)0.055
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 score0.609
Threshold uncertainty score0.777

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0560.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0280.036
Scholarly communication0.0280.012
Open science0.0040.007
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.394
Teacher spread0.375 · 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

Citations41
Published2009
Admission routes2
Has abstractyes

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