LEADERSHIP AS HOSTING: EXPLORATION OF CONCEPT AND PRACTICES
Bibliographic record
Abstract
The purpose of this qualitative study was to develop a grounded conceptualization of leadership as hosting in educational contexts and to explore perceived features of the effectiveness of hosting practices in educational organizations. The underpinning methodological design for the study was grounded theory. The population of educators for the study was identified through purposive sampling and consisted of graduate students and experienced educational leaders all of whom were affiliated with the University of Saskatchewan in Canada. Research-pertinent data were collected using an electronic Delphi, semi-structured, and expert interviews. The NVivo data analysis software was used to fortify the analytical process in order to produce insights and greater understandings associated with the construct and practices of leadership as hosting. This study was premised on the need for educators to provide high quality leadership and make educational settings more caring, inclusive, and welcoming. Findings revealed that among other things, educators who host well are competent at building positive relationships, managing vulnerabilities, and creating a culture of support and care for constituents. The practice of leadership as hosting holds promise for consciously creating educational environments where all stakeholders are valued and have a sense of belonging. Socially constructed understandings of this construct and its associated effective practices are likely to have significant implications for current leaders, policy makers, leader recruitment and preparatory programs for aspiring educational leaders.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".