Uplifting School Leadership—Enabling Structures and Processes: The Seven Powers of the Townsend/Adams Approach
Bibliographic record
Abstract
This article reviews the work of two Albertan educators, David Townsend and Pam Adams, in their application of collaborative inquiry to improving school leadership. Collaborative inquiry is essentially a professional practice that has yet not been comprehensively theorized. This article seeks to lay some foundations for a theorization of the practice by identifying structures and processes that appear to underlie the remarkable success of applications of the practice in several school districts in Alberta, Canada. The emerging mode is one that envisages seven powers: the power of teams, the power of relationship, the power of the process, the power of inquiry and reflection, the power of collaboration, the power of modelling, and the power of narrative. These powers appear to underpin much of what has been written about the ways in which collaborative inquiry has become a powerful force for leadership development in Alberta, and more recently in the State of New South Wales in Australia. Keywords: Collaborative inquiry, school leadership, enabling structures Cet article examine le travail de deux éducateurs albertains, David Townsend et Pam Adams, dans leur application de l'enquête collaborative pour améliorer le leadership scolaire. L'enquête collaborative est essentiellement une pratique professionnelle qui n'a pas encore été théorisée de manière exhaustive. Cet article cherche à jeter les bases d'une théorisation de la pratique en identifiant les structures et les processus qui semblent sous-tendre le succès remarquable des applications de la pratique dans plusieurs districts scolaires de l'Alberta, au Canada. Le mode émergent est celui qui envisage sept pouvoirs : le pouvoir des équipes, le pouvoir des relations, le pouvoir du processus, le pouvoir de l'enquête et de la réflexion, le pouvoir de la collaboration, le pouvoir de la modélisation et le pouvoir du récit. Ces pouvoirs semblent sous-tendre une grande partie de ce qui a été écrit sur la manière dont l'enquête collaborative est devenue une force puissante pour le développement du leadership en Alberta, et plus récemment dans l'État de Nouvelle-Galles du Sud en Australie. Mots clés : enquête collaborative, leadership scolaire, structures habilitantes
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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 | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.014 | 0.068 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".