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Record W2096568174 · doi:10.1177/0306396813497877

Neoliberal settler colonialism, Canada and the tar sands

2013· article· en· W2096568174 on OpenAlexaboutno aff
Jen Preston

Bibliographic record

VenueRace & Class · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsOil sandsIndigenousColonialismTreatyIndigenous rightsNegotiationGovernment (linguistics)State (computer science)Political scienceNatural resourceEconomyPolitical economyPublic administrationLawSociologyPoliticsArchaeologyGeography

Abstract

fetched live from OpenAlex

The Canadian government commenced the treaty-making process with the Indigenous peoples of the Athabasca region in 1870, motivated by the Geological Survey of Canada’s reports that petroleum existed in the area. This, in addition to the discovery of gold in the Klondike region, spurred an influx of unregulated settlement and resource extraction in the north. The trajectory of this history has continued to bring the Canadian settler state – and its oil industry stakeholders – into negotiation with indigenous Nations over the Athabasca tar sands. Currently contested is Enbridge Inc.’s Northern Gateway project, which aims to move oil from the Edmonton, Alberta area by way of two massive pipelines covering 1,170km to Kitimat, British Columbia, where it would then be transported to Asia-Pacific markets by super-tankers. This paper examines the widespread criticism of the project from Indigenous and environmental groups, as well as responses to these objections by public/private partnerships between Enbridge, federal and provincial governments and their national security and counter-terrorism forces. It argues that recognising and naming contemporary forms of white settler colonialism, including these types of neoliberal partnerships, is required for new relations to become possible.

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)0.003
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 score0.105
Threshold uncertainty score0.763

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0340.030
Scholarly communication0.0080.002
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.006
GPT teacher head0.248
Teacher spread0.243 · 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

Citations104
Published2013
Admission routes1
Has abstractyes

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