Shattering Silence, Inviting Dialogue: Anti-Oppressive Occupational Therapy During the Genocide of Palestinians
Bibliographic record
Abstract
Background. Occupational therapists are obligated to promote human rights and are required to advocate for the profession's statements concerning social justice to align with its actions. Purpose. This Commentary provides an anti-oppressive perspective, developed from the different positions and identities of authors currently living in Canada, contending that the practices of occupational therapists cannot be viewed as disconnected from global conflicts such as the genocide of Palestinians, and providing guidance for those seeking to align their actions with the profession's espoused values and obligations. Key issues. Identifying anti-oppression as an ethical, moral, and professional imperative, this commentary articulates a principled examination of a complexified issue; providing suggestions for how occupational therapists, as individuals and as a profession, can engage in anti-oppressive practices through: (a) commitment to learning, (b) reflexive and reflective personal work, (c) the use of guiding frameworks, (d) building community, and (e) compassionate actions. Implications. Noting that there is never a neutral or apolitical position in the face of injustice, the paper invites dialogue, and provides suggestions and guidance for occupational therapists seeking to align their actions with their professional obligations in supporting human and occupational rights locally and globally.
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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 | 0.025 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.055 | 0.069 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".