Intercultural Experiences Prior to the Educational Program: Occupational Therapy and Social Work Students
Bibliographic record
Abstract
In the health and social professions, including occupational therapy and social work, interactions and exchanges with people are essential. Populations encountered by professionals in these fields are becoming increasingly diverse in terms of age, origin, language, health status, and socio-economic background. Sometimes, professionals can have potential misinterpretations regarding intentions and actions, health beliefs and practices, or verbal and non-verbal communication. To overcome obstacles related to practice in a context of diversity, universities must develop students’ intercultural competence. Scientific literature stresses the importance of encountering diversity to improve awareness and sensitivity and to bring attention to biases and prejudices. Considering students’ intercultural experiences before their formation could be a basis to achieve this educational goal. The present study aims to document this topic. Semi-structured interviews with 51 first-year students from two educational institutions in French-speaking Switzerland were conducted to capture the participants’ descriptions of these experiences in private or professional contexts. The interviews were transcribed and submitted to a thematic analysis approach. A thematic map was generated and three main themes emerged: (1) perception of diversity; (2) communication challenges; and (3) transformation of attitudes toward the “Other.” They are described and discussed in terms of developing intercultural competence. Recommendations regarding intercultural education emerge from these findings.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.010 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".