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Record W1965510721 · doi:10.1353/ces.2012.0003

Interviews with Racialized Faculty Members in Canadian Universities

2012· article· en· W1965510721 on OpenAlexvenueaboutno aff
Frances Henry, Carol Tator

Bibliographic record

VenueCanadian ethnic studies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicFeminist Theory and Gender Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyMedia studies

Abstract

fetched live from OpenAlex

This paper is based on 89 interviews conducted with racialized faculty at ten Canadian universities as part of the larger study of racialization at the university. The majority of respondents were in social sciences but education and engineering were also well represented in the sample. Interviews followed a loosely formulated set of questions and most interviews were conducted informally. Respondents were, on the whole, willing and even eager to discuss their experiences of racism. Racialized people know when they experience everyday racism because it is repetitive and consistent with their past experiences. However, White people often do not see it even in their own words and actions. The denial of racism is still strongly held by the more traditional members of the Academy, especially those who are influenced by a liberal ideology that unless there is the intention to be racist, it does not exist. Many racialized faculty, especially Black women, expressed their loneliness and alienation from the university, their departments, and their colleagues. Other important themes that emerged from our interviews was the emphasis in most Canadian universities on the Eurocentric curriculum and, in some disciplines, the dominance of the ‘canon’; Under-representation of racialized faculty; Tenure and Promotion Processes which it is believed adversely affect racialized faculty; Critical, Applied and Community Research which is not valued especially for tenure and promotion purposes; Tokenism; Policies, Practices of the university in general and Senior Administration is particularly criticized because the important positions are often staffed by white men; Departmental Management is accused of being insensitive to minority faculty needs. Cet article s’appuie sur 89 entrevues menées auprès de professeurs non-blancs de dix universités dans le cadre d’une étude plus large sur la racialisation dans le milieu universitaire. La majorité des répondants enseignait en sciences sociales, mais les facultés d’Éducation et d’Ingénierie étaient aussi représentées dans l’échantillon. Les rencontres se sont faites autour d’une série de questions plus ou moins formatées, et la plupart ont eu lieu de manière informelle. Les participants ont, en général, volontiers discuté de leur expérience du racisme. Quiconque appartient à une minorité visible sait quand il y est confronté au quotidien, parce que c’est un comportement répétitif et conforme aux expériences déjà vécues. Les Blancs, cependant, ne le voient souvent pas, même dans leurs propres mots et actions. Le déni de racisme est encore fort chez les membres plus traditionnels du monde académique, particulièrement chez ceux qui sont influencés par une idéologie libérale, voulant que ça n’existe pas, sauf si c’est intentionnel. Une bonne partie du corps professoral racialisé, notamment les Noires, a exprimé la solitude et l’aliénation subies à l’université, dans leurs départements et du fait de leurs collègues. D’autres thèmes importants ont émergé de nos entrevues, dont l’emphase dans la plupart des universités canadiennes sur un curriculum eurocentrique ainsi que, dans certaines disciplines, la dominance du «canon», une faculté dont les membres non-blancs sont sous-représentés, une recherche critique, appliquée et communautaire non reconnue – entre autres pour obtenir une titularisation ou une promotion – des mesures symboliques, des politiques et pratiques de l’institution en général et de la haute administration en particulier – spécialement critiquée parce que les positions importantes sont souvent occupées par des hommes blancs – et, enfin, une gérance départementale insensible aux besoins d’un personnel professoral racialisé.

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)0.012
metaresearch head score (Gemma)0.020
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: Empirical
Teacher disagreement score0.939
Threshold uncertainty score0.658

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.007
Science and technology studies0.0610.012
Scholarly communication0.0070.002
Open science0.0020.006
Research integrity0.0030.003
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 head0.235
GPT teacher head0.435
Teacher spread0.200 · 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

Citations50
Published2012
Admission routes2
Has abstractyes

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