Redefining Borders between Communities and the Classroom: How Community-based Social Activists can Transform Social Work Education
Bibliographic record
Abstract
In the context of service restructuring that has gravely impacted quality of life for social workers and the people with whom they work, this paper considers the ways that social work education can better support social justice-based social work practices in urban communities in Canada. The paper’s authors attended a fall 2013 Ryerson University forum that brought together critical social work educators and community-based activist social workers struggling to bring social justice-based practices to their work within restructured social services. Examples of social service restructuring include cuts to services, labour intensification, and increased managerialism, processes known as neoliberalism that have shifted discourses away from quality of life toward a focus on economic markers and efficiencies. The purpose of our forum was to explore ways in which social work curricula and pedagogical practices can be challenged and redefined in order to better support those efforts by social workers to resist such processes and to enhance social worker and client quality of life. Our paper presents the findings of this forum, including the presentation and discussion of a series of recommendations to reconfigure social work education so that it is more congruent with the needs of social justice-based practice in social work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.043 | 0.064 |
| Scholarly communication | 0.025 | 0.015 |
| Open science | 0.004 | 0.033 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 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".