Roots of Collaborative Inquiry and Generative Dialogue for Educational Leadership
Bibliographic record
Abstract
The twin processes of collaborative inquiry and generative dialogue underpin two closely aligned and increasingly influential school leadership development programs, one in Alberta, Canada, and the other in New South Wales, Australia. This paper focuses primarily on the Australian program, the character of which has been strongly influenced by its Canadian predecessor. Of interest in the paper is the nature of the foundations of collaborative inquiry and generative dialogue, and the relationship of these processes to an expressed need for better leadership development in the Australian school sector. David Townsend and Pam Adams, who are principally responsible for generating a school leadership development model based on the use of both collaborative inquiry and generative dialogue, have sought to show how these two processes should function seamlessly, but there is more to be said about the nature of their relationship. This paper seeks to throw more light on the integral role played by generative dialogue in empowering collaborative inquiry in the context of school leadership development. Keywords: generative dialogue, collaborative inquiry, school leadership, leadership development, educational leadership programs Les processus jumeaux de l'enquête collaborative et du dialogue génératif sous-tendent deux programmes de développement du leadership scolaire étroitement alignés et de plus en plus influents, l'un en Alberta, au Canada, et l'autre en Nouvelle-Galles du Sud, en Australie. Cet article se concentre principalement sur le programme australien, dont le caractère a été fortement influencé par son prédécesseur canadien. Il s'intéresse à la nature des fondements de l'enquête collaborative et du dialogue génératif, ainsi qu'à la relation entre ces processus et le besoin exprimé d'un meilleur développement du leadership dans le secteur scolaire australien. David Townsend et Pam Adams, qui sont les principaux responsables de la création d'un modèle de développement du leadership scolaire basé sur l'utilisation de l'enquête collaborative et du dialogue génératif, ont cherché à montrer comment ces deux processus devraient fonctionner de manière transparente, mais il y a plus à dire sur la nature de leur relation. Cet article vise à mettre en lumière le rôle intégral joué par le dialogue génératif dans l'autonomisation de l'enquête collaborative dans le contexte du développement du leadership scolaire. Mots clés : dialogue génératif, enquête collaborative, leadership scolaire, développement du leadership, programmes de leadership scolaire
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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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.101 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".