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Record W4378650649 · doi:10.7202/1099981ar

Learning Leadership: Leading Growth in a Transactional System

2023· article· en· W4378650649 on OpenAlexafffundvenueabout
Kevin R. Wood

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2023
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsUniversity of Lethbridge
FundersUniversity of Lethbridge
KeywordsTransactional leadershipPsychologyEducational leadershipInstructional leadershipPedagogySociologySocial psychology

Abstract

fetched live from OpenAlex

Learning Leadership is a framework that addresses the complex actions and decisions made by principals. Harris and Jones (2021) declared the need to deepen an understanding of how educational leaders support conditions inherent to learning organizations. This study sought to better understand how principals learn and support growth as a strategy for leading. Findings are presented from seven Alberta, Canada high schools where principals were asked to reflect on learning leadership. Open interviews generated data about learning as both an outcome and a method of leading. Interview data was analyzed through van Manen’s (2016) three step interpretive scheme and yielded themes describing how high school principals mediated in-school realities with external expectations. Study findings indicate that principals who lead for learning and achievement were able to identify growth-minded solutions characterized by ethical and wise approaches.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.096
GPT teacher head0.399
Teacher spread0.302 · 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 teacher head, not a consensus.

Study designObservational
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

Citations3
Published2023
Admission routes4
Has abstractyes

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