We’re Building the Bridge While Walking on It: An Anti-Oppressive Social Work Response to Intimate Partner Violence among Immigrant Women in Canada
Bibliographic record
Abstract
Intimate partner violence (IPV) among immigrant women in Canada remains a deeply complex and often underreported issue, shaped by intersecting structural, cultural, and socio-economic factors. Barriers such as precarious immigration status, language limitations, cultural stigma, and economic dependency significantly constrain access to support and protection. Conventional social work responses, which tend to rely on standardized intervention models, frequently fail to account for these layered realities. This article adopts an anti-oppressive practice (AOP) perspective to critically examine how social workers respond to IPV within this context. Using a practice-oriented, three-phase analytical framework, the discussion explores (1) the identification of complex and intersectional client needs, (2) the development of adaptive practice strategies under institutional and resource constraints, and (3) the navigation of ethical dilemmas alongside stakeholder engagement. The phrase “we are building safety in pieces” is used to conceptualize the evolving and uncertain nature of practice in this field. The analysis suggests that effective responses require flexibility, cultural responsiveness, and a strong commitment to social justice. Ultimately, the article argues that anti-oppressive approaches enable more equitable and context-sensitive interventions, while highlighting the need for continuous reflexivity in social work practice. This article is derived from a Ph.D. thesis submitted to the University of South Africa, Department of Social Work, titled "Violence Against Immigrant Women in Canada: Experiences of Clients and Solutions Presented by Social Work" by Baffour Asamoah, supervised by Professor Paul Mbedzi.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.011 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".