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Record W2486584485

"Supercrip" vs human interest: Examining stereotypes towards paralympians following the viewing of Canadian paralympic committee videos

2015· article· en· W2486584485 on OpenAlex
Celina H. Shirazipour, Shane N. Sweet, Marie-Josée Perrier, Kathleen A. Martin Ginis, Amy E. Latimer‐Cheung

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Exercise, Movement, and Sport · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsMcMaster UniversityYork UniversityQueen's University
Fundersnot available
KeywordsPsychologyStereotype (UML)Competence (human resources)Social psychologyPerception
DOInot available

Abstract

fetched live from OpenAlex

The media typically portrays Paralympians by emphasizing their superhuman qualities (i.e. a supercrip portrayal) or the characteristics of their disability (i.e. a human interest portrayal). While these portrayals may be of interest to people without physical disabilities (PD), they are perceived negatively by people with PD. No studies have examined the effect of different types of media portrayals on disability stereotypes. Therefore, the objective of this study was to compare the effect of these two portrayals on stereotype perceptions of individuals with and without PD. Participants (n=148 with PD; n=180 without PD) watched two Canadian Paralympic Committee videos, in counterbalanced order, that presented the same Paralympian using either a supercrip or human interest portrayal. After each video, participants rated Paralympians on measures of warmth and competence, two indicators of stereotypes. A 2(disability status) x 2(video) x 2(warmth and competence) mixed model ANOVA demonstrated that people without PD rated the human interest portrayal higher in warmth (M=4.12; SD=0.64) than those with PD (M=3.89; SD=0.80; p=.014), suggesting increased presence of stereotypes towards this portrayal amongst those without PD. Furthermore, regardless of group, warmth scores were significantly higher following viewing of the human interest portrayal (M=4.01; SD=.73) compared to ratings after viewing the supercrip video (M=3.87; SD=.77; p

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.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.096
GPT teacher head0.347
Teacher spread0.251 · 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