Internationalizing Ourselves: Realities, Opportunities, and Challenges
Bibliographic record
Abstract
Internationalization is a very relevant topic on university campuses and most universities include a commitment to it in their mission statement or strategic plans. Over the years, universities have realized the importance of providing students with an international perspective that will prepare them to succeed in an increasingly globalized world. The globalization of the sport industry makes our field an ideal medium for addressing the concept of internationalization. As leaders in the field of sport management, we must ensure that we teach, research, and advocate from an international perspective. This paper discusses how we as sport management academicians and students might prepare ourselves to become global citizens by internationalizing ourselves through our teaching, research, and service. A commentary on the status of internationalization in our field as well as suggestions for change is provided.
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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 | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.041 |
| Scholarly communication | 0.027 | 0.029 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 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".