Examining the Impact of the Rio 2016 Paralympic Games on Explicit Perceptions of Paralympians and Individuals with Disabilities
Bibliographic record
Abstract
One of the goals of the Paralympic Games is to improve social attitudes toward individuals with physical disabilities (PD) through exposure to parasport and Paralympic mass media messaging. This study assessed whether this goal is achieved by examining changes in explicit perceptions toward Paralympians and individuals with PD over the course of the Rio 2016 Paralympics. Adults without PD (n = 119) were randomized into two groups: (1) an exposure group that was e-mailed local Paralympic Games coverage information before each day of the Games; and (2) a control group that received no e-mails about coverage. All participants completed measures assessing explicit perceptions (i.e., warmth and competence) of Paralympians and individuals with PD two weeks before, two weeks after, and three months following the Games. Exposure to Paralympic media was also assessed. No differences were present between groups for time spent watching the Games, explicit perceptions, or demographics (ps > .05). Thus, data was collapsed across groups for the main analyses. Repeated measure ANOVAs with Bonferroni adjustments indicated that explicit perceptions of warmth decreased over time for both Paralympians and individuals with PD (p ≤ .005). However, Paralympians were rated as significantly more competent and warmer than individuals with PD (ps < .001) at each timepoint. Findings suggest that public exposure to the Paralympics may have more value for Paralympians than the larger disability community. Further research should explore how to disseminate communication regarding the Paralympics to improve social attitudes and optimize integration of all people with disabilities in society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".