Violence and Healing: Exploring the Power of Collective Occupations
Bibliographic record
Abstract
The effects of violence on the person are extensive, more so, for persons disabled through violence. Research in occupational therapy has shown the effectiveness of occupations in helping displaced refugees to construct new identities and navigate new ways of belonging within asylum countries. No research thus far has focussed on the role of occupation for healing in contexts of sustained violence. Aim: To explore the role of occupations in the healing journeys of people physically impaired by violence. Study Design: Qualitative; Narrative Inquiry. Methodology: Photovoice and Narrative Interviews. Data Analysis: Narrative-analytic methods were used to produce explanatory stories. Findings: These are presented with a specific focus on the impact/influence of violence on personal and societal occupational engagement and the restorative role of collective occupations within the participants’ healing journeys. The findings suggest a need to reframe violence as a collective occupation that dehumanizes, and healing as a collective process that (re)humanizes within a broader framework of Ubuntu as an interactive ethic. These findings call for a shift in focus for rehabilitation practices involving individuals disabled through violence, in contexts of sustained direct and structural violence such as South Africa.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.037 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".