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Record W1591988541 · doi:10.3390/soc5030566

Leadership Effects on Student Learning Mediated by Teacher Emotions

2015· article· en· W1591988541 on OpenAlexaff
Jingping Sun, Kenneth Leithwood

Bibliographic record

VenueSocieties · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransformational leadershipPsychologyTeacher leadershipStudent achievementOrganizational citizenship behaviorPedagogyEducational leadershipShared leadershipMathematics educationSocial psychologyTransactional leadershipAcademic achievementOrganizational commitment

Abstract

fetched live from OpenAlex

School leaders’ influence on student achievement is largely indirect. Using systematic review techniques, this paper assesses the impact that leaders have on their students when they focus their improvement efforts on those teacher emotions or dispositions known to have direct effects on teaching and learning in the classroom. Building on an earlier conceptions of how leadership influences student learning and based on a review of research over the last 25 years, this study identifies four distinct teacher emotions which have significant effects on student learning—collective teacher efficacy, teacher commitment, teacher trust in others, and Organizational Citizenship Behavior. This review also describes leadership practices likely to foster productive teacher emotions, most such practices reflecting a transformational approach to leadership.

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)0.014
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.051
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.210
GPT teacher head0.405
Teacher spread0.195 · 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 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

Citations69
Published2015
Admission routes1
Has abstractyes

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