Connectivity and Collectivity in a Doctoral Cohort Program: An Academic Memoir in Five Parts
Bibliographic record
Abstract
In this critical reflection, four doctoral graduates and one professor, all involved in a cohort-based educational leadership doctoral program, provide narratives about key processes and moments that contributed to building powerful connections and a collective orientation to the groups’ learning and success. Dialogic processes, conscious intention, and naming shared values were established early in the program by the cohort members enabling them to take ownership of their learning and to commit to the group’s collectivity and connectivity. We argue this cohort’s processes illustrate how shared and democratic leadership was not only a topic of discussion, it was also successfully enacted. Dans cette réflexion critique, quatre titulaires d’un doctorat et un professeur, tous impliqués dans un programme de troisième cycle sur le leadership éducationnel et reposant sur une cohorte, présentent des récits portant sur les procédés et les moments clés qui ont contribué à la création de liens puissants et une orientation collective visant l’apprentissage et la réussite du groupe. Les membres de la cohorte ont établi, dès le début du programme, des procédés dialogiques, une intention consciente et l’identification de valeurs partagées, ce qui leur a permis de s’approprier leur apprentissage et de s’engager dans la cohésion et la connectivité du groupe. Nous soutenons que les procédés de cette cohorte illustrent dans quelle mesure un leadership partagé et démocratique n’est pas resté seulement un sujet de discussion, mais a été en fait mis sur pied.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".