“It’s always going to be a part of who you are”: exploring the identities of competitive male ice hockey players
Bibliographic record
Abstract
In this thesis I explore how competitive male ice hockey players living in Northeastern Ontario \nconstruct their identities through sport participation with an emphasis on masculinity. The \npurpose of the thesis is to provide insight into the way identities are formed and the examination \nof myself in relation to my biases and the participants. The study was guided by narrative theory \nusing a social constructionism paradigm. Participants consisted of five current players (age 19- \n22) from hockey teams in Northeastern Ontario and one retired professional hockey player who \nacted as a key informant. I used thematic analysis to identify common themes from a total of six \nsemi-structured, conversational interviews. The thesis is a paper-based document consisting of \ntwo stand-alone manuscripts and complementing bookend chapters. The first manuscript \npresents the results from the analysis of the interviews while the second manuscript presents a \ndiscussion around reflexive materials written throughout the research process.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".