Bibliographic record
Abstract
Identity development has been conceptualized through Marcia's (1966, 1967, 1980) identity status model, whereby an individual can adopt an identity status (i.e., achievement, moratorium, foreclosure, or diffusion) that varies along a continuum between commitment and crisis (Marcia, 1980). With Canada's top athletes spending close to 40 hours per week training and rating sport as the most important aspect of their lives (Ekos Research Associates, 2005), the question arises whether such devotion impacts identity development. Accordingly, the present study aimed to examine identity status in Canadian national team athletes. As part of a larger study, questionnaires were completed by Sport Canada carded athletes and by students from a Canadian university. Identity status was assessed using the Extended Objective Measure of Ego-Identity Status (EOMEIS-2) (Bennion & Adams, 1986). Results indicated likeness and variation, with athletes scoring similarly to university students in measures of identity diffusion, moratorium, and achievement, but scoring higher than university students in identity foreclosure. With this latter finding supporting the view that that the task of identity formation can be challenging given sport's push for commitment and conformity (Pearson & Petitpas, 1990) , the discussion will focus on how transitioning to adulthood may be a unique process for Canadian high performance athletes. Acknowledgments: This study received funding from the Social Sciences and Humanities Research Council of Canada.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".