A comparison of male and female sport officials' developmental histories
Bibliographic record
Abstract
Most research on sport officials (e.g., referees) has been comprised of male participants, with some indications that approximately only 13% of studies have included female officials (Pina et al., 2018). The purpose of this study was to explore the differences in male and female developmental milestones related to sport official's participation. The developmental history of athletes questionnaire (Hopwood, 2013) was modified to collect information from 511 Canadian sport officials (19% female) on factors such as officiating age of debut, and highest tier of officiating achieved (recreational, provincial, national/international). Overall, female officials had younger mean start ages (years) than male officials (21.5 vs. 26.7: t(509) = 3,59, p = .001). This trend was particularly evident among soccer officials (19.8 vs 26.3, t(201) = 2.58, p = .01). Although not statistically significant, females officiated on average more games per year prior to the age of 25, and thereafter, male officials averaged increasingly more games per year. There were also no statistically significant differences in the distribution of female and male officials across the tiers of officiating, although there was a 7% over-representation of male officials at the national/international level. These results provide some preliminary information on the developmental histories and activities of male and female officials. While most findings were inconclusive, they provide some indications that female and male officials may have unique developmental histories and experiences. Going forward it may be useful to explore female officials' prior athlete participation histories, as well as their accumulated training experience related to officiating.Acknowledgments: This research was supported by funding from the Social Sciences and Humanities Research Council (SSHRC) of Canada (Insight Grant# 435-2018-1496)
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".