Canadian Global Leadership Students Engaged in Strategic Partnerships in Ecuador
Bibliographic record
Abstract
Abstract Recognizing the need to build global-minded citizens, higher education institutions are increasingly trying to find ways to leverage their international programs to develop students’ intercultural competence. The MA in global leadership at Royal Roads University, Canada, created an international partnership in Ecuador that serves to go beyond the traditional student study abroad or service learning focus and instead focuses on developing competencies of global mindedness and strategic relationships. In this chapter, we present an analysis of how an international student group engaged in building dynamic partnerships within a Global South country to create change for sustainable development initiatives of mutual concern. Through a case example, we describe how these partnerships evolved and adapted in ways that enhanced the learning needs of the students while simultaneously supporting the development of new educational opportunities for Ecuadorians. To illustrate, this chapter delineates the activities that members of the program undertook to connect and develop a mutuality of relationship across diverse stakeholders in Ecuador. The authors analyze this network-building process from the perspective of cultural context, building trust and influence, and responding to social development needs of host communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 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".