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Record W4255449402 · doi:10.2307/j.ctv6gqt3h

Mining and Communities in Northern Canada

2015· book· en· W4255449402 on OpenAlexfundaboutno aff

Bibliographic record

VenueUniversity of Calgary Press eBooks · 2015
Typebook
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersArcticNetWilfrid Laurier University
KeywordsGeography

Abstract

fetched live from OpenAlex

For indigenous communities throughout the globe, mining has been a historical forerunner of colonialism, introducing new, and often disruptive, settlement patterns and economic arrangements. Although indigenous communities may benefit from and adapt to the wage labour and training opportunities provided by new mining operations, they are also often left to navigate the complicated process of remediating the long-term ecological changes associated with industrial mining. In this regard, the mining often inscribes colonialism as a broad set of physical and ecological changes to indigenous lands. Mining and Communities in Northern Canada examines historical and contemporary social, economic, and environmental impacts of mining on Aboriginal communities in northern Canada. Combining oral history research with intensive archival study, this work juxtaposes the perspectives of government and industry with the perspectives of local communities. The oral history and ethnographic material provides an extremely significant record of local Aboriginal perspectives on histories of mining and development in their regions. With contributions by: Patricia Boulter Jean-Sébastien Boutet Emilie Cameron Sarah Gordon Heather Green Jane Hammond Joella Hogan Arn Keeling Tyler Levitan Hereward Longley Scott Midgley Kevin O'Reilly Andrea Procter John Sandlos Alexandra Winton

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.077
Threshold uncertainty score0.555

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0290.008
Scholarly communication0.0070.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.049
GPT teacher head0.261
Teacher spread0.212 · 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 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

Citations20
Published2015
Admission routes2
Has abstractyes

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Same venueUniversity of Calgary Press eBooksSame topicIndigenous Studies and EcologyFrench-language works237,207