SUSTAINING A COMMUNITY OF SCHOLARS AT A TRANSNATIONAL UNIVERSITY: A SELF-STUDY
Bibliographic record
Abstract
In this article we report on a self-study at a transnational research-intensive university in Qatar. We trace the shared perceptions of four emerging scholars, from two disciplines, coming together to build a sustainable community of scholars as an interdisciplinary team. We explore our initial thoughts in developing our group and illustrate the themes of collegiality, mentorship and conflict in sustaining a successful community of scholars. We conclude with lessons learned illustrating how the concept of support played a significant factor in sustaining our community and adjusting to both a transnational education setting and expatriate life. The findings may serve useful to others working in such a setting, and most expressively, provide an opportunity to broaden the continued scholarly discourses of scholarship, community of scholars, and interdisciplinary teams within the context of transnational education.
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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 | 0.019 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.033 | 0.022 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".