Career Decision-Making Processes and Cultural Perspectives from East-Asian Counselling Psychologists in Canada
Bibliographic record
Abstract
This study explores the career decision-making processes of East Asian psychologists in Canada, documents their perspective on cultural competency education at the graduate level, and discuss implications for recruiting and training future counselling psychologists to better meet the mental health needs of East Asian communities and individuals. This study is a qualitative research based on semi-structured interviews with 10 participants in Canada: five practicing counselling psychologists and five counselling psychology graduate students, all from East Asian backgrounds. Through a qualitative thematic analysis, salient themes revolving around participants’ career decision-making experiences, their experiences in graduate training programs, as well as their professional experiences were identified. These themes point to gaps between existing mental health practices in counselling psychology and the cultural experiences of East Asian individuals. They highlight the need for promoting diverse representation in the field of professional psychology, as well as addressing deficits in cultural competency training in counselling psychology programs in Canada. This research provides a unique perspective from a group of minority psychologists regarding ways to enhance the recruiting and training psychologists from more diverse cultural backgrounds to promote equity, diversity, and inclusiveness in the field of counselling psychology.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.033 | 0.010 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| 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".