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Record W2598995145 · doi:10.3828/bjcs.2017.4

Water (in)security in Canada: national identity and the exclusion of Indigenous peoples

2017· article· en· W2598995145 on OpenAlexaboutno aff
Maura Hanrahan

Bibliographic record

VenueBritish Journal of Canadian Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousEthnologyOpposition (politics)Political scienceNational identityIdentity (music)Gender studiesSociologyGeographyLawArtPoliticsAesthetics

Abstract

fetched live from OpenAlex

With the exception of First Nations, Métis, and Inuit people, most Canadians enjoy water security. Indigenous people are ninety times more likely than other Canadians to lack piped water. These disparities result from and maintain the colonial relationship between Canada and Indigenous peoples. As displaced people with values often in opposition to neo-liberalism, Indigenous people present an existential threat to Canadian identity, this identity having been created around possession of a vast land that extends to the North Pole, and subsequent heavy resource extraction throughout this land. To maintain Canada’s national identity and the activities that support it, Indigenous people have to be pushed to the figurative and literal fringes and rendered invisible. Five short case studies of water insecurity demonstrate how neo-liberalism props up and legitimises decentralised water governance in Canada, which in turn promotes and maintains environmental inequality, Indigenous marginalisation and, ultimately, the Canadian identity.

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)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.571

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0250.007
Scholarly communication0.0050.001
Open science0.0010.004
Research integrity0.0010.001
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 head0.019
GPT teacher head0.271
Teacher spread0.252 · 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
Published2017
Admission routes1
Has abstractyes

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