Bibliographic record
Abstract
The purpose of this commentary is to critique the application of well-being in the field of sport and exercise psychology and to provide recommendations for future research. Over the last decade well-being has been an increasingly popular concept under investigation. In the field of sport and exercise psychology, numerous scholars have examined and conducted research on well-being of athletes. While this research has resulted in an abundance of findings, there is concern in how the concept of well-being was applied, defined, and measured. The construct of well-being can be traced back to two distinct perspectives, hedonic well-being and eudaimonic well-being. These perspectives of well-being are based on different philosophical assumptions, and while they are compatible, they are theoretically distinct. In sport and exercise psychology, well-being has lacked consistent operationalization and measurement (i.e., theoretical alignment, single dimensions of hedonic or eudaimonic measured to make claims about the broader well-being constructs), is vague and loosely defined, and is often studied in isolation from a well-being perspective (i.e., no theoretical foundation). We conclude by offering three recommendations to move the field of well-being in sport research forward.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".