An exploration of Para sport administrators' role in disseminating knowledge related to classification
Bibliographic record
Abstract
Classification aims to create fair and equitable competition for athletes with disabilities; however, literature shows athletes’ and coaches’ knowledge of classification is often limited. Sport administrators may play a critical role in disseminating information about classification to their members, yet their understanding of classification has not been explored. Similarly, administrators’ role in educating athletes and coaches about classification are not yet been documented. We sought explore these topics through semi-structured interviews with six administrators at national sport organizations. Critical realism, wherein reality is believed to exist outside of ourselves and, although reality can be observed, its existence is not dependant on observation, was adopted. Analysis sought to identify observed and unobserved events and experiences as well as causal mechanisms for the phenomena. Three broad, explanatory themes were generated. First, we identified that classification creates tension within parasport pathways. This theme describes the dual-purpose of classification to create participation and high performing pathways. Second, we determined that parasport administrators’ roles are responsive to the dynamic and unique needs of their sport. Therefore, while similar actions are undertaken by administrators across organizations their aims differ greatly. Third, a lack of clarity within and about the classification system was identified as impacting administrators’ and therefore athletes’ experiences with classification. Primarily, poor knowledge of classification affects administrators’ abilities to set athletes’ expectations for their progression through sport, the experience of classification, and potential outcomes they may receive. This work identifies gaps in practice and advances our understanding of the classification system used within parasport.
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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 | 0.024 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| 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".