From knowledge to action: defining effective and functional school division planning practices to maximize organizational improvement and change
Bibliographic record
Abstract
The practice of education planning across Canada is established for the manifest purpose of guiding school improvement. In Manitoba, the planning process is reportedly intended to improve linkages that will increase efficiency and enhance communication, thereby improving educational outcomes for all students (Manitoba Education, 2004, 2007). The problem arises in a practical sense, however, in determining whether the education planning process creates the necessary linkage between strategic intentions and activities, or whether the planning process exists simply as a bureaucratic requirement or condition (Meyer and Rowan, 1983). This research study was designed to determine whether there were systemic features of school division planning for Student Services, which would result in improved linkages between educational intentions and related actions, making the process more effective and functional. In order to respond to the questions posed in this study, I focused on a concrete aspect involved in planning for students with challenging learning behaviours. With the assistance of school divisions participating in the study, I collected data from structured interviews with key personnel, and from planning templates or other selected documentation. The information was compiled and examined through a conceptual framework, derived from the review of literature, which served to organize and analyze the school division data. A process of analytic abduction was used to define similarities and variances in planning practices, according to the conceptual framework. The information was summarized and a synthesis of effective planning practices was created as a result. The findings informed the development of a new framework detailing the archetypes of effective and functional planning practices for Student Services at the school division level, a process more likely to set the stage for organizational improvement and change.
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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 | 0.066 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.022 | 0.022 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.004 | 0.004 |
| 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 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".