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Record W1986729488 · doi:10.1017/s0829320100006372

Keeping the Ivory Tower White: Discourses of Racial Domination

2000· article· fr· W1986729488 on OpenAlexaffabout
Carol Schick

Bibliographic record

VenueCanadian Journal of Law and Society / Revue Canadienne Droit et Société · 2000
Typearticle
Languagefr
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsHumanitiesPolitical scienceIvory towerArtSociology

Abstract

fetched live from OpenAlex

Résumé La manière de désigner les espaces et les places est significatif dans l'histoire et la formation du Canada comme pays identifié blanc. Dans cet article, les espaces de l'éducation publique post-secondaire sont analysés comme indicateurs d'appartenance dans la production identitaire des étudiants. Les étudiants blancs de cette recherche ont besoin de la fonction légitimante de l'université tout autant que des processus idéologiques de sa formation pour «devenir des enseignants». Les exigences de l'institution d'apprendre à «gérer» les relations interculturelles les autorisent à devenir des citoyens et des enseignants légitimes. Maintenir le statut de sites d'élites demande de surveiller la production du savoir en termes d'hiérarchies de race, de classe et de genre. Les relations sociales de l'élite désignent également quelles identifications et quelles connaissances seront considérées rationnelles et légitimes. Dans l'enquête qui fonde cet article, des étudiants-enseignants identifiés comme blancs dépendent des hiérarchies raciales d'espaces éducationnels d'élite pour assurer leur propre respectabilité dans la profession d'enseignants à domination blanche. C'est une respectabilité exigée et possible par le fait qu'ils sont blancs.

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)0.008
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.935

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0390.054
Scholarly communication0.0150.006
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.301
Teacher spread0.288 · 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.

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

Citations61
Published2000
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Law and Society / Revue Canadienne Droit et SociétéSame topicCritical Race Theory in EducationFrench-language works237,207