Reimagining Social Work from an Islamic Worldview
Bibliographic record
Abstract
With Islamophobia on the rise in Canada, it may reasonably be expected that social work, a seemingly care-oriented profession, would have effective support readily available for the Muslim community. However, rather than the Muslim community experiencing social services as a place where such support can be accessed, their interactions with these services demonstrate the ways that Islamophobia seeps into social work settings amidst discriminatory assumptions about Muslims and a lack of religiously informed care. In response, informed by an Islamic worldview and drawing upon decolonial thought and community-based participatory research principles, this study aims to centre Islamic ways of knowing, being, and doing in considering how mainstream social services and social work practice can most effectively support the Muslim community. Emerging from interviews with five Muslim community leaders and scholars were four key themes: the role of Islam in the lives and well-being of Muslims; anti-Muslim sentiment and the devaluing of Islamic identity in mainstream social work education and practice; the need for Islamically informed care; and reimagining social work from an Islamic worldview. The findings reveal significant challenges for the Muslim community in accessing and receiving effective support from mainstream social services, while also underscoring important considerations for enhanced social work practice with Muslims. Implications and recommendations for the social work profession, social work education, and the Muslim community are discussed, alongside suggestions for future research and action, with an emphasis on the importance of contributions from Islam and Muslims to elicit meaningful change.
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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 | 0.018 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.029 | 0.089 |
| Scholarly communication | 0.020 | 0.010 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.008 |
| 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".