Bibliographic record
Abstract
Schein (2010) proposed that any group's culture can be analyzed at three levels: artifacts, espoused beliefs and values, and basic assumptions. Given the exponential growth, popularity, and success of CrossFit (Helm, 2013), it is beneficial to explore and better understand its culture. The purpose of this study was to investigate the organizational culture of CrossFit using Schein's (1985) conceptual framework. Focus groups were conducted with 17 participants from a CrossFit gym in northern Ontario including five new members (under 6 months), six veteran members (over 1 year), four coaches, and the two owners. The interview questions were structured around Schein's three levels of organizational culture. Support for all three levels of Schein's model of organizational culture was found within the CrossFit gym. Perceptions of culture were not dependant on status within the gym as all groups of participants (new members, veteran members, coaches and owners) perceived a similar culture. Artifacts reported included the rugged, industrial appearance of the gym (visual structures and processes) and the social nature of members' prior to/following each workout (observable behaviour). Espoused beliefs and values identified by the participants included pride in the gym and their workouts, inclusion of all abilities, and a strong sense of community that extended beyond the gym. A shared underlying assumption by all members, coaches and owners was the common goal of improving their health and well-being. This research has helped us better understand CrossFit's organizational culture and the values that have made it a successful organization.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".