Bibliographic record
Abstract
Mental Health in Elite Sport: Applied Perspectives from Across the Globe provides a focused, exhaustive overview of up-to-date mental health research, models, and approaches in elite sport to provide researchers, practitioners, coaches, and students with contemporary knowledge and strategies to address mental health in elite sport across a variety of contexts. Mental Health in Elite Sport is divided into two main parts. The first part focuses globally on mental health service provision structures and cases specific to different world regions and countries. The second part focuses on specific mental health interventions across countries but also illustrates specific case studies and interventions as influenced by the local context and culture. This tour around the world offers readers an understanding of the massive global differences in mental health service provision within different situations and organizations. This is the first book of its kind in which highly experienced scholars and practitioners openly share their programs, methods, reflections and failures on working with mental health in different contexts. By using a global, multi-contextual analysis to address mental health in elite sport, this book is an essential text for practitioners such as researchers, coaches, athletes, as well as instructors and students across the sport science and mental health fields.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".