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Record W2528740696 · doi:10.29173/cjs28211

Mining as Canadian Nation-Building: Contentious Citizenship Regimes on the Move

2016· article· en· W2528740696 on OpenAlexafffundvenueabout
Max Chewinski

Bibliographic record

VenueThe Canadian Journal of Sociology · 2016
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsTechnocracyCitizenshipState (computer science)ImpunityPolitical economySociologyCapital (architecture)Ideal (ethics)MandateCorporate social responsibilityPublic administrationLawPolitical scienceHuman rightsPolitics

Abstract

fetched live from OpenAlex

This article presents Canadian mining abroad as an imperial, nation-building practice that can be traced to state discourses. In analyzing state discourses, it is argued that an ideal citizenship regime is constructed, in part, due to a specific set of values and identities. This citizenship regime is corporate in nature, and operates as a vehicular idea that facilitates the flow of travelling technocrats, minerals and capital by reshaping the policies and practices of host nations. In the discourses examined, it becomes clear that the Canadian state actively forms both the conditions for the expansion of nation-building projects and actively participates in securing and promoting contentious mining projects. By mobilizing corporate citizenship, Canada remains committed to managing resistance movements that pose a risk to accumulation instead of addressing corporate impunity. The article concludes by considering how MiningWatch Canada and the movements they support create fissures in the corporate citizenship regime.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.093
Threshold uncertainty score0.672

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0320.028
Scholarly communication0.0120.003
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.028
GPT teacher head0.216
Teacher spread0.188 · 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

Citations1
Published2016
Admission routes4
Has abstractyes

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