Counselling Muslims: A culture-infused antidiscriminatory approach.
Bibliographic record
Abstract
There are approximately 1.57 billion Muslims in the world, with approximately 940,000 living in Canada. Furthermore, the population of Muslims living in Canada is expected to grow to about 2.7 million by 2030. Despite the high numbers and anticipated growth of this population, there still exists a dearth of research on the worldviews and intracultural differences of Muslims. Understanding the worldviews and intracultural differences of Muslims is essential if counsellors and psychologists intend to practice in an antidiscriminatory and culturally competent manner, especially given the increased awareness of the psychosocial needs of Muslims in the decade or so that followed the 9/11 attacks. However, if counsellors and psychologists are unwilling to challenge existing biases and stereotypes in their own minds, or are unaware of how to do it, then they may unintentionally engage in unethical prejudicial and discriminatory practices. The authors aim to encourage counsellors and psychologists to apply an aspirational level of ethical practice when working with nondominant populations in general and Muslims in particular. In the article, ethical obligations are mentioned first, followed by an in-depth exploration of the major sources of discrimination. The authors then discuss several theoretical models of the development of bias. Subsequently an exploration into the use of Arthur and Collins’ culture-infused counselling framework for working with Muslims in Canada is put forth. The example of Muslim women wearing the religious veil known as hijab is used to highlight these points and allows readers to explore their own level of cultural competency in working with Muslim clients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".