Examining the Process of the Development of Multicultural Counselling Competencies in Therapist-Trainees
Bibliographic record
Abstract
Canada admits between 22,000 - 24,000 refugees each year (Beiser, 2005). Immigrants and visible minorities tend to underutilize mental health services. However, ensuring new settlers' physical and mental health is not only humane, but also crucial to enable them to achieve their social and economic potential in the host country. Fundamentally, the need for Multicultural Counselling Competencies (MCC) is due to diverging notions of mental health and healing between clients and therapists who are culturally different from each other. There is ample literature on Multicultural Counselling Competencies. However most of this body of research has been conducted using quantitative approaches. The present study is a qualitative analysis which aimed to answer the research question: "What are therapist-trainees' experiences regarding their Multicultural Counselling Competencies (MCC) while providing therapy to firstgeneration, government assisted, refugee clients?". The sample for this study consisted of fourteen therapist-trainees who were doctoral level students in the Clinical Psychology program, Adult Track, at the University of Windsor. These therapist-trainees completed Critical Incident Journal (CIJ) entries after each session with their refugee clients. The therapist-trainees completed a total of 165 CIJ entries. These entries were analyzed using an adaptation of the Grounded Theory Method (GTM) as a guiding framework (Rennie, 2006). Three main themes emerged from the therapists CIJs: "Feeling the Need to Adapt", "Feeling a Sense of Increasing Cultural Self-Awareness" and "Building the Therapeutic Relationship is Important". In addition, developmental aspects of the therapists' experiences were identified. Implications for future training, practice and research are discussed.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".