Athletic identity affects prevalence and disclosure of emotional abuse in Finnish athletes
Bibliographic record
Abstract
The present study offers novel insight into the topic of experienced and observed emotional abuse by researching factors that affect athletes' responses to emotional abuse by coaches. The research aimed to explore three main questions: (1) whether athletic identity was associated with the prevalence of emotionally abusive coaching practices, and (2) disclosure of emotional abuse, and (3) whether demographic variations existed in the frequency of emotional abuse, athletic identity, and disclosure of the abuse. Study participants who filled in an anonymous digital survey consisted of athletes from elite to leisure levels living in Finland (N = 3687, aged 12–80, gender 61% female, 37.7% male, 0.8% other genders). The research findings highlighted three key insights. Firstly, Pearson correlations revealed that a salient athletic identity was related to a higher prevalence of emotional abuse. Secondly, ANOVA/Kruskal-Wallis tests between-groups indicated that particularly children were susceptible to the abuse. Thirdly, a mediation analysis showed that self-identity (aspect of athletic identity) influenced the relationship between experienced emotional abuse and disclosure, by reducing disclosure. As a result, holistic identity development is recommended for athletes and particularly children in sports.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".