A Shift in Role: The Perspectives of Ontario Secondary Principals Working in Data-Driven Environments
Bibliographic record
Abstract
This study occurred in 2009 and questioned how Ontario secondary school principals perceived their role had changed, over a 7 year period, in response to the increased demands of data-driven school environments. Specifically, it sought to identify \nprincipals' perceptions on how high-stakes testing and data-driven environments had \naffected their role, tasks, and accountability responsibilities. This study contextualized \nthe emergence of the Education Quality and Accountability Offices (EQAO) as a central \ninfluence in the creation of data-driven school environments, and conceptualized the role \nof the principal as using data to inform and persuade a shift in thinking about the use of \ndata to improve instruction and student achievement. The findings of the study suggest \nthat data-driven environments had helped principals reclaim their positional power as \ninstructional leaders, using data as an avenue back into the classroom. The use of data \nshifted the responsibilities of the principal to persuade teachers to work collaboratively to \nimprove classroom instruction in order to demonstrate accountability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".