Understanding the staff cancer through the perceived experiences of varsity male soccer players
Bibliographic record
Abstract
Informal roles can be beneficial or detrimental to sport performance. Researchers have identified negative informal roles within sports and organisational contexts; however, exploration of these roles has been limited to athletes within sports research or staff members within organisational research. To our knowledge, negative informal roles occupied by a staff member on a sports team have not been studied. The purpose of the current research was to develop an introductory understanding of a negative informal staff role on a sports team, henceforth referred to as the staff cancer. Working within a critical realist framework, we utilised photo elicitations and arts-based conversational interviews to augment comfort and interview seven former varsity male soccer players concerning their perceived experiences of the staff cancer. Two overarching themes representing the characteristics and consequences of the staff cancer were developed using an interpretive/inductive thematic analysis. Four subthemes represent the characteristics theme, including passionate, insecure, controlling, and poor communicator, while five subthemes represent the consequences theme, including poor mental health, team divide, team unification, diminished performance, and increased attrition. The results are presented through a composite vignette to safeguard participant confidentially. This manuscript makes a valuable contribution towards understanding some of the characteristics and consequences of the staff cancer, showcases clarity regarding the application of critical realism, and highlights how combining methods can be used to augment participant comfort when discussing sensitive topics, such as coaches’ and athletes’ power hierarchies.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".