The Art of Working Together: A Phenomenological Study of Interdepartmental Collaboration Within Ontario Universities
Bibliographic record
Abstract
The role of higher education professional staff in enacting strategies for institutional survival is critical, as an emergent subset of staff collaborate in inter-disciplinary space between traditional academic and administrative boundaries to solve complex problems. However, collaboration is not straightforward, as it is not an automatic phenomenon, only sometimes happening. Using qualitative research design, this thesis explores how collaboration occurs within Ontario universities from the perspective of professional staff within equity diversity and inclusion (EDI) and community engagement roles tasked with collaboration. Ten professional staff from seven Ontario universities, working on inter-disciplinary projects indicated in institutional strategic plans, participated in this study. The findings emphasize that Ontario university professional staff experience collaboration as a subset of co-constructed activities, while continuously making sense of their roles and objectives. This thesis explores and advances our fundamental understanding of a system's capacity for collaboration in hopes of increasing innovation and problem-solving capacity within higher education institutions.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.044 | 0.041 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".