Cross-cultural Experiences during a Visiting Scholar Program: “…A Start[ing] not a Finishing Point”
Bibliographic record
Abstract
Aim To describe the Visiting Scholar Program as a context for cross-cultural learning experiences and the development of intercultural competencies. Background In 2004, a Visiting Scholar Program (VSP) was developed between the Faculty of Nursing, University of Alberta (UA), Canada, and the University of São Paulo at Ribeirão Preto College of Nursing (USP-EERP), Brazil, with the goal to promote capacity building among nurse researchers. During a cross-cultural exchange program, participants are immersed in a foreign culture and language over an extended period of time, which offers them a potential opportunity to develop intercultural competence. Methods A qualitative design was utilized and data were collected in June 2011 through semi-structured in-depth interviews with scholars, supervisors and staff members from both institutions. Following data collection, an inductive process was used to analyze the data, following Morse’s (1994) taxonomy. Results At USP-EERP participants included 12 former scholars, two staff members from the International Office, one graduate student, and one former Dean. At the UA, 12 supervisors and 5 staff, affiliated with the VSP participated in an interview and two provided feedback by email. The central theme in the findings was the ‘Cross-Cultural Learning Process’, with three main sub-themes: challenges; benefits; and lessons learned. Conclusion Cross-cultural learning was a circular process that involved dealing with challenges, experiencing stress in a strange environment and building intercultural competencies. The VSP program enhanced scholars and supervisors’ awareness and sensitivity to cultural diversity and their openness to new cross-cultural experiences.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".