Leading from the middle: its nature, origins and importance
Bibliographic record
Abstract
Purpose The purpose of this paper is to cover a 10-year period in ten of Ontario’s 72 school districts on the nature, origins and importance of “leading from the middle” (LfM) within and across the districts. Design/methodology/approach The research uses a self-selected but also representative sample of ten Ontario school districts. It undertook three-day site visits in each of the districts, transcribed all the interviews and compiled an analysis into detailed case studies. Findings LfM is defined by a philosophy, structure and culture that promotes collaboration, initiative and responsiveness to the needs of each district along with collective responsibility for all students’ success. Research limitations/implications To be sustainable in Ontario, LfM needs support and resourcing from the top. The current environment of economic austerity therefore threatens sustainability. Globally, examples of LfM are emerging in at least three other systems. The analysis does not have identical questions or respondents in phases 1 and 2. Ontario’s version of LfM may differ from others. The collaborative design may downplay criticisms of LfM. Practical implications LfM provides a clear design for leading in complex times. Compared to top-down leadership the whole system can address the whole of students’ learning and well-being. LfM is suited to systems and cultures that support local democracy, community responsiveness and professional empowerment and engagement. Originality/value LfM is an inclusive, democratic and professionally empowering and responsive process that differs from other middle level strategies which treat the middle merely as a way of connecting the top and bottom to get government policies implemented more efficiently and coherently.
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 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.022 | 0.021 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".