Repurposing the (Super)Crip: Media Representations of Disability at the Rio 2016 Paralympic Games
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.
Bibliographic record
Abstract
Mega-events attract ever larger media audiences, and the 2016 Rio Paralympics were no exception. As audiences grow, media coverage extends to ever more varied domains, which are themselves then colonised by an increasing range of discourses. One of main discourses to develop since the early 2000s has been that of the so-called supercrip, one which challenges the notion of “impairment” often connected with disability by foregrounding the para-athletes’ triumph over adversity, celebrating instead their courage, grit, and perseverance leading to athletic success and personal and increasingly national prestige. In this article, we analyse the continuing importance of the supercrip discourse in coverage of the Rio Paralympics but also move on to highlight its tactical alignment with other—both competing and complementary—discourses of nationalism, sexualisation, militarisation, and celebritisation. We analyse textual and visual manifestations of these discourses using both critical discourse analysis and Foucauldian discourse analysis. We conclude by paying particular attention to the increasing visibility of discourses which, while acknowledging the potentially positive role of the supercrip discourse in focussing on athletic success, repurpose that discourse by foregrounding instead the day-to-day experiences of belittling misrepresentation and neglect, including political neglect.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it