Bibliographic record
Abstract
In this article, the relationships between the nature of the professional leadership culture and student learning are examined according to the professionals’ perceptions. The qualitative case study examined the perceptions of school-level professionals in one elementary school with a reputation for strong results in student learning, regarding the nature of the professional leadership culture and its relationship to student learning. Professional leadership culture is defined by this author as shared assumptions, practices, beliefs and values concerning leadership activities that are understood and practiced among school professionals. E. H. Schein’s (2010) organizational culture and leadership model provided the conceptual framework for the study. The three most common representations of the professional leadership culture included pervasive collaboration among professionals, a culture of trust, and a supportive environment. This study prompts some reflection for theory-building on the connection between the concept of leadership and its role in improving school culture. Policy implications of the study are discussed as they relate to human resources issues and their connection to culture and leadership, priorities regarding personnel supervision and evaluation, standards for a respectful workplace, the institutionalization of trust, open communication, supportive relationships, collaboration, and the anticipation and management of workplace conflict.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".