Social work education and disability: a multicase study of approaches to disability in core and specialized curricula in three Bachelor of Social Work programs
Bibliographic record
Abstract
The purpose of this study was to examine ideas about disability within social work education within three Bachelor of Social Work programs in Canada, and to identify and describe major perspectives and themes of disability. One important aspect of the study was to determine the extent to which critical disability studies perspectives were presented, explained, and discussed in the classroom within core social work theory courses, and specialized courses addressing disability. Three Bachelor of Social Work programs; St. Thomas University School of Social Work in New Brunswick, the Dalhousie School of Social Work in Nova Scotia, and the University of Manitoba Faculty of Social Work, Fort Garry Campus, were purposefully chosen for this multicase study based on a theoretical replication logic that predicted that social work education on disability within each of the schools would represent different points on a range of disability perspectives, as developed from the disability studies literature. Data collection and analysis included multiple methods, including a manifest content analysis of texts, a modified inductive analysis of transcriptions from interviews with key informants, and a critical discourse analysis of transcriptions from an audio-taped session of classes addressing disability in each case. Findings from the multicase study indicate that the original research suppositions were not supported. Based on the analysis of texts and interviews, the approach to disability followed by each Bachelor of Social Work program was found to incorporate a broad range of disability theory, particularly social pathology and critical disability perspectives. However, there was little evidence of classroom discussion and use of social work practice approaches supporting these perspectives. It was argued in the literature review to the study that anti-oppressive social work approaches, such as structural social work, were congruent with critical disability perspectives, but that there is also a need for an “infused” approach to integrating disability content into core curriculum. In conclusion, I also suggest that the Canadian Association for Social Work Education has an important leadership role to play in providing specific recommendations for disability inclusion in social work education.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".