Internationalization of location-bound resources: cases from Canada
Bibliographic record
Abstract
This chapter addresses a gap in the internationalization theory. It compares the internationalization of location-bound events and resources with the traditional theories of internationalization and points to their few similarities and mainly differences. Two in depth and longitudinal case-studies of highly popular and growing events in Montreal, Canada, prior to the emergence of COVID-19 crisis document significant differences between the traditional and location-bound internationalization, where international customers travel to Montreal to benefit from such events. These cases also point to the important impact of influential factors and evolving processes. They also uncover that communication and information technologies play critical roles in the internationalization outcomes over time. The longitudinal aspects of these case-studies also point to the indirect internationalization of complementary events and services over time due to their interactions with the other firms, and international customers at home during the internationalized local events. The chapter also discusses the managerial lessons, theoretical implications, and public policy recommendations, followed by a brief epilogue updating the status of the two cases at the end.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.013 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".