Leading school improvement: using Popper’s theory of learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Leadership is a highly complex activity, as leaders respond to increasing diversity and external accountability. Additionally, there is increased recognition that leadership is deeply contextual, sensitive to macro-politics of systems and micro-politics of individual schools. In Ontario, Canada, the school improvement effort is focused on raising student achievement and ensuring equitable outcomes. The current provincial education policies across Canada require that principals focus on (1) increasing the proportion of students who meet educational expectations and (2) reducing the ‘achievement gaps’ amongst sub-groups of students within the public school system. Despite these efforts, in Ontario, schools continue to encounter difficulty in meeting the needs of all their students. A full pursuit of factors related to differences to students’ backgrounds and abilities is beyond the scope of this article. Rather, this article is concerned with how school can adopt Karl Popper’s theory of learning for school improvement efforts.
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.
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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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 it