Perceptions of Faculty With Respect to Change at a Western Canadian College: An Exploratory Study
Bibliographic record
Abstract
Publicly funded postsecondary education institutions are experiencing significant forces of change which have been acerbated by the global pandemic. The results of this project indicate that leaders of those institutions in North America should engage their faculty to help their respective colleges or universities survive, and perhaps even thrive in these evolving circumstances. In this exploratory case study, the research participants (faculty in a small central Alberta institution) contributed interesting insights with respect to their perceptions of change and the need and urgency for change in the sector. In addition, they shared interesting perspectives with respect to several topic areas, in particular provincial governance and technology. They especially identified that the influence of technology, with respect to curriculum, teaching and learning and other aspects of institutional operation, was pervasive. Furthermore, I discovered that faculty in general may not be naturally inclined to contribute to their institution’s change efforts, given their primary job responsibilities. However, it appeared that some members, generally those who had taken on leadership roles and/or additional education, demonstrated awareness of larger and far reaching aspects of the change forces impacting the sector. Thus, faculty members, when adequately prepared for discussions related to change, can enhance the welfare of their home institutions in these challenging environments. Thus, it may take some preparation by committed leaders to get larger portions of that constituency group to contribute to the larger organizational effort, but early indications are that the investment in those efforts are worthwhile.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.029 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".