A critical interpretive synthesis: Use of the occupational justice framework in research
Bibliographic record
Abstract
BACKGROUND: The occupational justice framework was established in the late 1990s with an agenda to spur occupational therapists to take action against injustices pertaining to occupation. METHODS: A critical interpretive synthesis of 23 texts was undertaken to examine how the occupational justice framework has been utilised in research, with a particular focus on how such research is located on a knowledge to action continuum and the extent to which it enacts the call to remediate occupational injustices. RESULTS: Within the texts reviewed, the occupational justice framework was predominantly used to interpret research findings, and only four studies explicitly used an action research approach. There was also a dominant tendency to individualise situations of occupational justice, but with some examples attending to the social and political production of injustices. Absences and silences related to the locations of the research in developed regions and a focus on conceptualisations of justice commensurate with a Western worldview were evident. CONCLUSIONS: Full realisation of the potential contributions of the occupational justice framework requires challenging traditional modes of research that focus primarily on knowledge generation, and expanding into modes of research that embrace a knowledge to action continuum. This expansion, which will enable occupational justice research to more fully embrace action-oriented work, requires practicing epistemological reflexivity, adopting a critical stance, incorporating a participatory action research approach and collaborating with scholars from different disciplines.
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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 | 0.164 | 0.292 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.031 | 0.025 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".