Examining the Connection between Exposure to People with Physical Disabilities and Staring Behaviour among Able-bodied Adults
Bibliographic record
Abstract
Previous work suggests that interacting with people with disabilities is an effective strategy for improving attitudes and behaviours towards this stigmatized group. However, the optimal context for such interactions is unknown. Studies have found that portraying an individual with a disability as physically active may improve how able-bodied individuals perceive him/her. This study applies the stereotype content model to evaluate whether experience interacting with people with physical disabilities in a physical activity setting is a more effective strategy for mitigating negative behavioural reactions (staring) towards this population than interaction in a non-physical activity setting, or no interaction at all. The study uses eye tracking to evaluate staring behaviours in response to four image types: disabled/active, disabled/inactive, able-bodied/active, and able-bodied/inactive. Thus, this research will also examine interaction effects between experience level and image type. This study will provide evidence as to whether interacting with individuals with physical disability in a physical activity setting should be targeted as a real-word intervention for improving the way in which people with physical disabilities are treated.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".