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Record W20590110

Instructional Leadership in Alberta: Research Insights from Five Highly Effective Schools.

2012· article· en· W20590110 on OpenAlexaboutno aff
Larry Beauchamp, Jim Parsons

Bibliographic record

VenueAASA journal of scholarship & practice · 2012
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsInstructional leadershipEducational leadershipSchool administrationPsychologyPedagogyTeacher leadershipLeadership styleParticipative decision-makingEducational administrationFaculty developmentMathematics educationSociologyProfessional developmentPublic relationsPolitical scienceHigher educationSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

En este artículo se revisa la investigación patrocinada por la Asociación de Profesores de Alberta (ATA), con el fin de aportar evidencias a partir del estudio de cinco casos de liderazgo en cinco escuelas ejemplares de Educación Primaria en Alberta, Canadá. Las escuelas fueron seleccionadas por la ATA en torno al criterio de ser escuelas en las que se llevaba a cabo un liderazgo eficaz. En este estudio se vincula el liderazgo eficaz con la mejora de los aprendizajes de los estudiantes. En el transcurso del año escolar 2009-2010, los investigadores pasaron un tiempo en casa escuela entrevistando al personal de cada escuela con dos preguntas: (1) ¿Qué hace que esta escuela sea un buen lugar para la enseñanza y el aprendizaje? y (2) ¿Qué función ejerce el liderazgo para hacer que esto sea así? Los datos obtenidos fueron categorizados en de ocho temas. El artículo revisa estos ocho elementos y teoriza sobre qué lecciones aprendidas a partir de estos resultados pueden enseñarse a los lideres escolares

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)0.003
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.264

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0090.002
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.001
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 head0.231
GPT teacher head0.467
Teacher spread0.236 · 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

Citations12
Published2012
Admission routes1
Has abstractno

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Same venueAASA journal of scholarship & practiceSame topicEducational and Psychological AssessmentsFrench-language works237,207