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Record W3164620885 · doi:10.22584/nr51.2021.004

Arsenic Lost Years: Pollution Control at Giant Mine from 1978 to 1999

2021· article· en· W3164620885 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Northern Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsYukon University
Fundersnot available
KeywordsGovernment (linguistics)ArsenicEnvironmental protectionPolitical scienceGeographyChemistry

Abstract

fetched live from OpenAlex

Arsenic pollution of the air, land, and waters surrounding the Giant Gold Mine in Yellowknife, Northwest Territories, has been an ongoing public health crisis since the mine was opened in 1948. This article focuses on the story of Giant Mine from 1978 to 1999, paying particular attention to environmental health policy reform in the mine’s later years in the 1990s. I argue that regulatory action was delayed and ultimately prevented by the inability of regulators to respond to the risks that continuous exposure to low doses of arsenic posed to the community around Giant Mine. This article uncovers a trail of government, activist, and industry discourse that illuminates the extent to which the Canadian environmental regulatory structure was paralyzed by a lack of certainty on how toxins like arsenic interact with the human body.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.793
Threshold uncertainty score0.999

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)0.0020.004

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 head0.025
GPT teacher head0.301
Teacher spread0.276 · 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