Moving towards the social construction of leadership around sport coaching succession
Bibliographic record
Abstract
The ritual scapegoat theory advocates that team results do not justify within-season coaching turnovers. Head coaches are nevertheless constantly portrayed as scapegoats in the face of adversity during competitive seasons. To improve the comprehension of sport coaching succession (e.g. within-season coaching changes), this study adopts the social construction of leadership as a broader theoretical perspective which values the relational nature of sport leaders who interact for collective outcomes. Two research questions are addressed: (1) Why are head coaches continuously framed as scapegoats?; (2) How can sport leaders collectively manage within-season adversities? Through a phenomenological research design, qualitative data were generated from 59 semi-structured interviews with football practitioners from Brazil, an empirical setting where within-season coaching changes are repeatedly high. A reflexive thematic analysis captured five higher-order themes: excessive media pressure, dominant politics in club administration, lack of strategic planning, illogical expectations, and disengagement among players. Accordingly, the shared experiences of high-performance practitioners are discussed with respect to the collective interactions and social relations that construct leadership, hence stepping away from the conventional leader-centric approach that focuses on the head coach as a singular leader.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.025 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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 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".