In Service of Others – Connected Leadership in a Post-Secondary Context
Bibliographic record
Abstract
In this article, three associate deans, who each lead one of three Academic Support Offices in a School of Education at a Canadian research-intensive university, feature their reflections, leadership approaches, found synergies, and collaborations to cultivate and advance connected leadership and resilience. The Offices of Research, Teaching and Learning, and Internationalization are located in a common physical space. Each associate dean manages their own portfolio in addition to collaborating with one another on identified points of intersection and joint initiatives. These three Offices were formed to support faculty members and students in the two programs areas in the School—Undergraduate Programs in Education and Graduate Programs in Education. The work of the Academic Support Offices is supported by two administrative support individuals and two facilitators who work across all three Offices.
 Over the past 23 months, this team of seven transitioned to remote and virtual work in response to COVID-19. Opportunities and challenges pertaining to communications, collaborations and how leadership and resilience is lived amongst the three associate deans, in particular, are discussed. Authors apply the lenses of relationality and connectivism to make meaning of and reimagine their leadership through reflections on foundations of learning, such as autonomy, connectedness, diversity and openness, and how these essences contribute to collective and collaborative leadership and resilience. Authors assert that building on the relational and connectivity to support collaborative and generative work and learning communities that thrive is essential, moving forward.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.034 | 0.017 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 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".