Professional Misfits: “You’re Having to Perform . . . All Week Long”
Bibliographic record
Abstract
Background: Occupational therapy professes commitment to equity and justice, and research is growing concerning the experiences of clients from marginalized groups. To date, almost no research explores the professional experiences of therapists from marginalized groups. This qualitative study explores how exclusion operates in the profession among colleagues. Method: Grounded in critical phenomenology, semi-structured in-depth interviews were conducted with 20 occupational therapists who self-identified as racialized, disabled, ethnic minority, minority sexual/gender identity (LGBTQ+), and/or from working-class backgrounds. Iterative analysis was conducted using constant comparison and employing ATLAS.ti for team coding. Results: Across identity groups, four processes of exclusion were identified: isolation, abrasion, presumptions of incompetence, and coerced assimilation. Garland-Thompson’s (2011) concept of “misfit” is employed to analyze how therapists are constructed as not-quite-fitting the professional space delimited by occupational therapy’s white, able-body-minded, Western, heterosexual, middle-class, cisgender norms. Conclusions: Misfits are constructed by contexts, by expectations and material arrangements that assume particular bodies. Misfits make visible the inequities built into business-as-usual, an illumination that comes at often-painful cost. Yet there is possibility for change toward equity and justice for therapist colleagues: we can all choose to do differently, enacting change at micro and macro levels.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".