Positive Coaching: Ethical Practices for Athlete Development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Positive coaching has traditionally been defined and understood through a modernist lens (Smoll & Smith, 1987; Thompson, 1995, 2003) and a combination of privileged scientific knowledges. One effect of this is that coaches' problemsolving approaches tend to disregard the complex social, and relational dimensions of coaching (Nash & Collins, 2006) and ignore how problems get selectively framed and named (Lawson, 1984). As a result, many problems in sport remain misunderstood or solved ineffectively. Drawing on the work of Michel Foucault we critique these reductionist understandings of effective and ethical coaching and argue that for coaches to become a positive force for change, they must engage in an ongoing critical examination of the knowledges and assumptions that inform their problem-solving approaches. Further, we conclude that for coaching to become a respected profession worthy of deep and intelligent thought, it is vital that coaches carefully consider the effects produced by the way they solve problems.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it