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Record W2613563270 · doi:10.1177/0305829817712075

The ‘Missing’ Politics of Whiteness and Rightful Presence in the Settler Colonial City

2017· article· en· W2613563270 on OpenAlexaffabout
Delacey Tedesco, Jen Bagelman

Bibliographic record

VenueMillennium Journal of International Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsColonialismIndigenousPoliticsNexus (standard)UrbanizationIdentity (music)SociologyGender studiesPolitical scienceGeographyPolitical economyLawEconomic growthAestheticsArt

Abstract

fetched live from OpenAlex

This article engages the global nexus of colonisation, racialisation, and urbanisation through the settler colonial city of Kelowna, British Columbia (BC), Canada. Kelowna is known for its recent, rapid urbanisation and for its ongoing, disproportionate ‘whiteness’, understood as a complex political geography that enacts boundaries of inclusion and exclusion. The white urban identity of Kelowna defines Indigenous and temporary migrant communities as ‘missing’ or ‘out-of-place’, yet these configurations of ‘missing’ are politically contested. This article examines how differential processes of racialisation and urbanisation establish the whiteness of this settler-colonial city, drawing attention to ways that ‘missing’ communities remake relations of ‘rightful presence’ in the city, against dominant racialised, colonial, and urban narratives of their absence and processes of their displacement. Finally, this article considers how a politics of ‘rightful presence’ needs to be reconfigured in the settler-colonial city, which itself has no rightful presence on unceded Indigenous land.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score0.750

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0360.052
Scholarly communication0.0120.002
Open science0.0010.008
Research integrity0.0020.004
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 head0.042
GPT teacher head0.385
Teacher spread0.342 · 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
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

Citations23
Published2017
Admission routes2
Has abstractyes

Explore more

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