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Record W3028086721

Rejecting the Colonial Politics of Recognition. Below the Radar podcast

2020· article· en· W3028086721 on OpenAlexaboutno aff
Glen Coulthard, Am Johal

Bibliographic record

VenueSummit (Simon Fraser University) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismPoliticsPolitical scienceComputer scienceSociologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Glen Coulthard is Yellowknives Dene and is an associate professor in the First Nations and Indigenous Studies Program and the Department of Political Science at the University of British Columbia. He is also the author of the acclaimed book Red Skin, White Masks: Rejecting the Colonial Politics of Recognition from University of Minnesota Press. On this special episode live from the Vancouver Podcast Festival, host Am Johal sits down with Glen to talk about who and what influences his work and research, the different projects he’s been involved in over the years, and what continues to inspire him to do the work he does.\nRead more about Red Skin, White Masks: Rejecting the Colonial Politics of Recognition here: www.upress.umn.edu/book-division/b…kin-white-masks\nRead more about The Fourth World here: www.upress.umn.edu/book-division/b…he-fourth-world\nYou can read more about Glen Coulthard on our blog post: sfuwce.org/glen-coulthard/\nThis episode was recorded live at the 2019 Vancouver Podcast Festival, and we’re grateful to them for their invitation to be part of their programming at the Vancouver Public Library. To learn more about the Vancouver Podcast Festival, please visit their website: www.vanpodfest.ca/

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.487
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.237
Teacher spread0.204 · 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 teacher head, 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

Citations0
Published2020
Admission routes1
Has abstractyes

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