“I just love it”: Avid knitters describe health and well-being through occupation
Bibliographic record
Abstract
BACKGROUND.: Examining craft-based occupations is necessary to explicate the relationship between occupation and well-being. PURPOSE.: This study aimed to understand the role of knitting in the lives of passionate knitters and their experience of how knitting contributes to health, well-being, and occupational identity. METHOD.: Principles of phenomenology guided interviews with 21 knitting-guild members (with and without health conditions) and observations at seven guild meetings as well as guided the data analysis. Eight interviewees and 24 additional guild members confirmed key findings in writing. FINDINGS.: Five main themes capture how knitting (a) "makes me happy," (b) is "the mental challenge I need," (c) is "a hobby that joins" through social connections and skill development, (d) sustains identity such that "I can't imagine life without knitting," and (e) is a creative outlet "reflecting my personality." IMPLICATIONS.: This in-depth description of how knitters experience their craft in daily life bolsters the philosophical assumption that favoured occupations have the power to promote health and well-being.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".