What Do We Expect? An Examination of Perceived Committee Norms in Non-profit Sport Organisations
Bibliographic record
Abstract
Group norms are agreed standards describing behaviours that should and should not be performed in a prescribed context. The purpose of this study was to examine, in the context of volunteer sport executive committees, the types and relative strength of perceived committee norms. A further purpose was to explore the influence of individual and group factors on those norms, and the relationship between perceived norms and individual behaviour. Volunteer sport executive committee members (N = 121) completed a questionnaire that measured perceptions of committee norms, various individual (position, tenure) and group (size, gender and tenure composition) variables, and individual behaviour (attendance, effort, intention to stay with the committee). Committee norms that reflect members′ expectations about how to treat each other (social norms) and how to work together (task norms) were perceived to be very strong. Only committee size explained any variation in perceived committee norms, where three norms were perceived to be stronger by members of large versus medium-size committees. Committee norms were mildly associated with member attendance and effort. The findings suggest there are strong expectations, with very little variation, for member behaviour in volunteer sport executive committees. However, those group expectations have only a modest influence on the individual behaviours examined here.
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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 | 0.023 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".