International Cooperation through Academic Projects: Are There Any Future Prospects?
Bibliographic record
Abstract
Today, international academic cooperation of universities is going through a tough period due to political and economic challenges. The authors consider the main causes of this and show how the situation could be improved through the development of local academic programs, such as LEADER Project. This joint educational project, focused on entrepreneurship and management skills, is arranged by Richard Ivey School of Business, University of Western Ontario (Canada). The program has 11 years of positive experience at Baikal State University in Irkutsk and it has proved to be successful and viable. The article provides analysis of the projects strengths and the main components of its success. Attention is also drawn to the specific features and potential advantages of using the case method as a modern teaching procedure, as well as to the innovative format of the project and its mutually beneficial character. The authors analyze the results of a feedback survey of the participants and instructors in order to find out their takeaways from the project, its possible drawbacks and future development prospects. The key conclusions refer to the importance of retaining international academic contacts.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".