Access to Physical Activity and Sport and the Effects of Isolation and Cordon Sanitaire During COVID-19 for People With Disabilities in Scotland and Canada
Bibliographic record
Abstract
People with a disability are more at risk of experiencing inequalities in relation to sporting and physical activity opportunities, COVID-19 and the resulting restrictions stand to exacerbate these inequalities. This research directly contributes toward the World Health Organization, global research roadmap priority to explore "the impact of restrictive public health measures (e.g., quarantine, isolation, cordon sanitaire)." Social loneliness and social isolation have a significant impact on the health and wellbeing of individuals, therefore, it is imperative to gain an understanding of the effects of self-isolation and shielding during Covid-19 for people with disabilities to help those in policy and agency positions address these issues. This research utilized a qualitative approach, to speak with people with a disability, athletes and non-athletes and those in a position of management and policy making. Six online focus groups, with people participating in sport and physical activity, using live captioning, chat functions, and an online written discussion forum; through Project Echo website as part of a wider study on sport and accessibility were utilized. The study also drew on interviews and one of the focus groups was with senior policy makers and regional managers responsible for disability sport in Scotland.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".