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Record W74367796 · doi:10.5206/cie-eci.v35i1.9072

Framing Possibilities: Representations of Black Student Athletes in Toronto Media

2006· article· en· W74367796 on OpenAlexaffvenueabout
Roger Saul, Carl E. James

Bibliographic record

VenueComparative and International Education · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsYork University
Fundersnot available
KeywordsFraming (construction)SociologyHumanitiesMedia studiesArtHistory

Abstract

fetched live from OpenAlex

This article draws upon a weekly feature in the Toronto Star newspaper, the “High School Report,” to explore the representations of black male student athletes over the school year 2003/2004. These media representations contribute to an understanding of the wider social reality of student athletes. Our investigation points to the fact that the media present black male students compared to their white counterparts as giving priority to athletics over academics. By ignoring the structural inequities they face in schools and society, the media contribute to a popular discourse which frames the social and educational possibilities of black male students in limiting ways. Cet article tire ses renseignements de l'article hebdomadaire du journal Toronto Star: le Rapport sur les écoles secondaires “High School Report,” , pour examiner la représentation des athlètes-étudiants noirs pendant l'année scolaire 2003-2004. Ces représentations dans la presse contribuent à la compréhension d'une réalité plus large dans la société pour les athlètes-étudiants. Notre examen pointe au fait que la presse représente les athlètes-étudiants noirs comme plus inclinés aux sports qu'aux études scolaires que les athlètes-étudiants blancs. En ignorant les iniquités structurelles auxquelles les athlètes-étudiants doivent faire face à l'école comme dans la société, la presse se donne au discours populaire qui encadre les possibilités sociales et éducationnelles des étudiants noirs d'une façon limitée.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.237
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.069
GPT teacher head0.441
Teacher spread0.372 · 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 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

Citations9
Published2006
Admission routes3
Has abstractyes

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