Media representations and athlete identities: Examining benefits for sport psychology
Bibliographic record
Abstract
Although a small body of research in sport psychology has begun to study media representations, the analyses of media representations and athlete identities are on the margins of sport psychology. In this article we outline why the study of media representations and athletic identities is useful for sport psychology. The purpose is accomplished by centralising a social constructionist conception of identity to highlight why focusing on media representations expands understanding of identity and the psychological experiences, social behavioural and health consequences. These points are illustrated with examples from media research in sport psychology grounded in social constructionism (e.g., discursive psychology and cultural studies).We conclude that critical constructionist approaches focusing on media discourse/narratives, athlete identities and the psychological implications are useful because they further critical cultural sport psychology research. This ‘critical research agenda’ focuses on more nuanced examinations of the socio-cultural context of sport and athletic identities to expand possibilities for change, resistance and inclusion of multiple, fluid identities and positive health outcomes.
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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 | 0.009 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".