Bibliographic record
Abstract
More than at any other time, the importance of internationalization and of establishing global partnerships in education is acknowledged by governments and higher education institutions. As a result, collaboration between institutions resulting in increased study abroad opportunities, now viewed as signifiers of internationalization, have multiplied. In joining the search for the improvement of study abroad programs, this study follows a cohort of 14 Chinese graduate students enrolled in a 2-year Master in Education program offered in a partnership between Northeast Normal University (NENU), China, and the University of British Columbia (UBC), Canada. The study was guided by the following research question: What is the nature and substance of the students’ study abroad experience within the context of the NENU/UBC Collaborative Master’s Program? Student interviews, questionnaires, and final program evaluations show that there is a fine line between success and failure of such experiences. The outcomes of this study point to the need for greater attention to at least four tensions in our program: the system of schooling versus the educative agenda, a teaching qualification versus a degree in Education, being tied to a desk versus being free to explore, and reporting on versus inquiring into practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.028 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".