Developing a Global Mindset for Leaders: The Case of the Canadian Context
Bibliographic record
Abstract
The construct of global mindset is one that has gained greater attention recently. This chapter focuses on contextual factors that impact the development of a global mindset. Specifically, the focus is on the cultural context of Canada and the factors in the Canadian context that bridge the gap between the theoretical and the practical, and provide both opportunities and challenges related to developing a global mindset in this context. Developing a global mindset on the part of leaders takes place in particular contexts. In this chapter, the distinguishing aspects of the Canadian cultural context are reviewed. Specifically, the Canadian values of (1) individualism/collectivism balance; (2) egalitarianism; (3) caution, diffidence, dependence and non-violence; (4) consensus building; (5) regionalism; (6) multiculturalism; (7) particularism and tolerance; and (8) deference to authority are shown to be important in this cultural context to the development of a global mindset on the part of leaders. While these factors provide many benefits to supporting such development, they also represent unique cultural challenges for leaders.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.036 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".