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Record W3160440050 · doi:10.22230/ijepl.2018v13n10a743

Assistant Principals’ Perceptions of the Principalship

2018· article· en· W3160440050 on OpenAlexvenueno aff
Thomas Lee Morgan

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionEducational leadershipInstructional leadershipPsychologyPedagogySet (abstract data type)Teacher leadershipLearning environmentShared leadershipMedical educationLeadership styleSocial psychologyMedicineComputer science

Abstract

fetched live from OpenAlex

Education research has established a significant relationship between school leadership and students’ achievement. This study considered the leadership self-efficacy and practice of public school assistant principals (AP) in the domains of facilitating a supportive collaborative learning environment, instructional leadership, school improvement, management, and family and community relations, as perceived by APs' self-report. Findings of this study suggest that, in addition to the strengths in the domain of facilitating a collaborative learning environment and efficacy around family and community engagement, there were explicit gaps in the instructional leadership and school improvement practices of APs that need to be addressed. The study also confirmed that there continues to be a proliferation of duties and a lack of consistent set of practices.

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)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.117
GPT teacher head0.426
Teacher spread0.309 · 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 designQualitative
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

Citations24
Published2018
Admission routes1
Has abstractyes

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