A Blueprint for Promoting Innovation, Interdisciplinary Teamwork, and Collaboration
Bibliographic record
Abstract
In response to the myriad of pressures we are experiencing across the higher education landscape, many colleges and universities are exploring different ways to manage and drive change within their institutions. Centres for Teaching and Learning (CTLs) are well-positioned to be high-impact drivers of change in this evolving educational arena. With this comes the expectation that they will emulate and promote innovative practices and creative approaches when addressing many of our most complex academic challenges. Increased agility, cooperation, and strategic foresight within these centres are necessary to detect, respond, and adapt to anticipated future changes and disruptions. However, coordinating such a broad array of resources among CTL departments coupled with interpersonal implications often associated with organizational change and transformation can pose ongoing challenges for leadership. This Organizational Improvement Plan (OIP) will address these issues within the context of a teaching and learning centre at a mid-sized college in Southern Alberta. It will focus specifically on the fluctuating demands and functionality of the centre and the need for increased agility, cooperation, and collaboration among CTL departments to respond more effectively to our continuously shifting circumstances. This is accomplished by exploring the relational and systemic nature of the problem through the lens of complexity leadership theory and its three entangled leadership models: adaptive leadership, enabling leadership, and administrative leadership. The outcome is a strategy theoretically grounded in social cognition theory and a leadership model for cultivating adaptive capacity and leadership competence in strategic foresight.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".