Building Global Skills: Broader Concepts of Internationalization in an Ontario College
Bibliographic record
Abstract
The Canadian federal government, national associations, and internationalization scholars have identified the need and demand for Canadian students to acquire global skills and competencies during their post-secondary education. Opportunities to acquire global skills can be offered through a wide variety of global engagement programs, such as study-abroad exchange programs, faculty-led excursions abroad, and other programs that allow students to interact with the global world. However, these programs are costly and do not consider the significant financial resources students require to participate in such activities. Most at-home students are left out of global engagement programming and therefore do not have the opportunity to acquire global skills during their time in college.\nThis organizational improvement plan (OIP) addresses the need for broader concepts of internationalization that include global engagement opportunities for at-home students. Using distributed and transformative leadership approaches and the change path model, this OIP provides an equitable solution to the problem of practice (PoP) by implementing virtual exchange initiatives, known as Collaborative Online International Learning (COIL), at a large college in southern Ontario. These initiatives provide a wider audience of at-home students with opportunities to work with students from around the world and acquire skills that are much needed and in demand in a global economy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.023 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".