Realizing change in a Manitoba high school: a multi-lens perspective and integrative framework explaining the linkages among contexts, agents, and strategy
Bibliographic record
Abstract
In September 2009, the Seven Oaks School Division (SOSD) in Winnipeg, Manitoba, Canada operating in accordance with an agreement it had signed with Big Picture Learning Inc. of Providence, Rhode Island opened a Met (Metropolitan Regional Career and Technical Center) school and housed it in an existing division high school. The purpose of this thesis is to analyze the factors that supported the development of the design of this Met school. The analysis in this instrumental case study (Stake, 2006) used an adaptation of a multi-lens integrative framework (Rajagopalan & Spreitzer, 1997) to answer the following overarching research question – To what extent are the features of the SOSD Met school explained by factors in the environment of the collective leadership group that was assigned the task of developing the school, by factors in the secondary school where the Met school was hosted, and by the mindsets, interactions and actions of the four members of the collective leadership group? The study utilized elite interviewing methods (Dexter (1970) with nine individuals and an analysis (Neuendorf, 2002) of primary and secondary documents. The theoretical model as developed through the adapted Rajagopalan- Spreitzer Multiple-Lens Integrative Framework proved useful in identifying environmental and organizational factors that shaped cognitions, which lead to the actions of the principal and advisors of the collective leadership group. The study shows that the collective leadership group chose a design for the SOSD Met school that was rational in that it met the goals and constraints of major agents in the group’s environment, and that it reflected the cognitions and actions of the individual members of the group. More generally, the thesis adds to the literature of strategic organizational 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.017 | 0.028 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".