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Record W2280383983 · doi:10.1177/105268461302300602

Learning and Leading for Growth: Preparing Leaders to Support Adult Development in Our Schools

2013· article· en· W2280383983 on OpenAlexaff
Eleanor Drago‐Severson, Jessica Blum‐DeStefano, Anila Asghar

Bibliographic record

VenueJournal of School Leadership · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsMcGill University
Fundersnot available
KeywordsCourseworkLeadership developmentEducational leadershipAdult LearningPedagogyMedical educationPsychologyAdult educationMathematics educationPolitical sciencePublic relationsMedicine

Abstract

fetched live from OpenAlex

Currently, scholars and practitioners seek to improve leadership programs so that educational leaders can more effectively support adult development—especially since it is connected to improved student achievement. Interview findings presented here stem from a larger mixed methods study. This research investigated how a university course on leadership for adult development influenced participating leaders’ thinking and on-the-ground practices years after course completion. Findings describe students’ reported course learnings, ways that they translated learnings to practice, and obstacles that they still encounter. This investigation offers insight into how leadership coursework can help leaders support adult development in schools and build systemic and school structures that would better enable them to build capacity.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.085
GPT teacher head0.358
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2013
Admission routes1
Has abstractyes

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