Bibliographic record
Abstract
This chapter explores individual intercultural competence as an enacted capability developed through social interaction and experience with dominant local cultures and minority cultures. The authors employ a knowing-as-practice perspective, following Nicolini et al. (2003), and notions of tacit knowledge within particular domains (Sternberg et al., 1995), to suggest that the study of intercultural experts has potential to inform this area of knowledge. From this perspective, examining practice repertoires used by expert actors can provide a useful complement to cultural intelligence frameworks (Thomas & Inkson, 2004, Earley, 2002) for understanding individual intercultural competence. Drawing on emerging literature on biculturalism, this chapter introduces an approach to researching intercultural knowing-in-practice through a focus on one type of experts, in this case, a group of young, bicultural Canadians. The authors found emotion- and behavioral-based themes that informed these experts’ responses to intercultural scenarios, their responses to proposed in-situ practice. From the findings, the chapter suggests that management can learn about intercultural competence from such experts’ approaches to navigating intercultural conflicts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.063 | 0.028 |
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".