Extending Beyond Qualitative Interviewing to Illuminate the Tacit Nature of Everyday Occupation
Bibliographic record
Abstract
The study of human occupation requires a variety of methods to fully elucidate its complex, multifaceted nature. Although qualitative approaches have commonly been used within occupational therapy and occupational science, we contend that such qualitative research must extend beyond the sole use of interviews. Drawing on qualitative methodological literature, we discuss the limits of interview methods and outline other methods, particularly visual methods, as productive means to enhance qualitative research. We then provide an overview of our critical ethnographic study that used narrative, visual, and observational methods to explore the occupational transitions experienced by immigrants to Canada. We describe our use of occupational mapping and participatory occupation methods and the contributions of these combined methods. We conclude that adopting a variety of methods can enable a deeper understanding of the tacit nature of everyday occupation, and is key to advancing knowledge regarding occupation and to informing occupational therapy practice.
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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 | 0.069 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 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".