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Record W4408614581 · doi:10.5539/ies.v18n2p69

A Digital Leadership Development Model of Administrators in Large-Sized Secondary Schools under the Basic Education Commission Offices in the Northeast of Thailand

2025· article· en· W4408614581 on OpenAlexvenueno aff
Phornma Juntrakot, Wannika Chalakbang, Wanpen Nantasri

Bibliographic record

VenueInternational Education Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Leadership and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionInstructional leadershipEducational leadershipPolitical sciencePedagogyMathematics educationSociologyPublic relationsPublic administrationPsychology

Abstract

fetched live from OpenAlex

The objective of this study was to develop and validate a digital leadership development model of administrators in large-sized secondary schools under the Basic Education Commission offices in the northeast of Thailand. The findings showed that 1) the developed model comprised four key elements, namely factors of success development support, components of digital leadership, development process and strategies and digital leadership outcomes, 2) all elements of the developed model obtained suitability and feasibility at the highest levels, and 3) the guide book of digital leadership development model of administrators in large-sized schools under the Basic Education commission offices in the northeast of Thailand composed of Instructions, Principles, Objectives, Rationale and Background, Contents and References. All components of the guide book, in overall, received the highest level of feasibility.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.134
GPT teacher head0.411
Teacher spread0.276 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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