Bibliographic record
Abstract
This issue called for papers and articles related to leadership innovations in schools. As I look back on my career, I recall many opportunities to provide leadership not only in schools but also in communities. In each case, there was always an expressed need either presented by existing conditions or through analysis of practices that were not working. Always it was about change and how to improve on what was already happening or not happening in my school environment. I recall that the key driving force behind every venture was what I could do to improve the learning experiences of the students I taught. With each project I learned that vision and creativity were necessary but if the project was to succeed collaboration and cooperation was essential. Over the years I have taken and taught various courses on leadership and the implementation of innovative change strategies. That said, in its simplest terms providing innovative leadership in schools comes down to controlling a variety of factors, far too many to write about in this column. However, I created a little equation for myself (6P's) that has guided every project. Be prepared. With careful Planning (vision and action strategies) a project unfolds as it emerges from infancy to implementation. Cultivate a Principal. Invest energy in an administrator who believes and supports the project (power and funding are important aspects of any project and they can help in this regard.). It is important to understand and accept that effective administrators have the authority and the power to influence decisions. Always collaborate and involve Parents. They are often your key to success and usually your best allies. Involve them in as many ways as possible. Ensure that other Partners (colleagues, students, consultants, media, etc.) are informed, involved and kept in the loop. Keep a high Profile (you need to get your project noticed and accepted). And finally, maintain a Principled approach (ethics, values and adherence to professional practice).
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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.323 | 0.231 |
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".