Towards a Critical Occupational Approach to Research
Bibliographic record
Abstract
Critical approaches to research are becoming increasingly more prevalent but occupational science and critical approaches have not been explicitly combined into one approach despite the potential to enrich the understanding of the assumptions and ideologies underlying human activity. In this article we outline an approach to research that is mutually informed by occupational and critical social science perspectives. The critical occupational approach we describe can be used to explore the ways in which knowledge is produced through engagement in occupation, who controls knowledge production, the mechanisms of how occupations are taken up, and who stands to gain or lose. We discuss the implications and considerations for generating research purposes and methods and conducting analyses. We then illustrate the use of the approach through a case study. We conclude this article with consideration of the wider uses and implications of a critical occupational approach within health and social research.
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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 | 0.269 | 0.117 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.019 | 0.008 |
| Science and technology studies | 0.024 | 0.158 |
| Scholarly communication | 0.048 | 0.043 |
| Open science | 0.008 | 0.028 |
| Research integrity | 0.014 | 0.022 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".