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Record W4386569918 · doi:10.5539/jel.v12n6p90

A Study of Education Administrators’ Exertion of Authority Phitsanulok Primary Educational Service Area Office 1

2023· article· en· W4386569918 on OpenAlexvenueno aff
Nirada Wechayaluck

Bibliographic record

VenueJournal of Education and Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Leadership and Teacher Performance
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPopulationTest (biology)Higher educationStratified samplingMedical educationSociologyPolitical scienceDemographyMedicineStatisticsMathematicsLaw

Abstract

fetched live from OpenAlex

The objectives of this study were 1) to study education administrators’ exertion of authority 2) to compare education administrators’ exertion of authority under Phitsanulok Primary Educational Service Area Office 1. The variables were divided by the administrators’ experiences and the sizes of the institutions. The population in this study was 1,161 education administrators and teachers. The number of the samples was 291 determined using Krejcie and Morgan Table, stratified random sample of the sizes of the institutions, and simple random sampling. The study used a 5-point rating scale questionnaire for item-objective congruence ranged between 0.80-1.00 and the reliability was at 0.962. Data analysis statistics were mean, standard deviation, t-test statistic, one-way ANOVA test, and pair difference test by Scheffe’s method. The results were found as follows. 1) In general, the level of education administrators’ exertion of authority was high. The aspect with the highest mean was the authority of information technology access (x  = 4.17), while that with the lowest mean was the authority of punishment (x  = 3.56). 2) There was no difference, in general, in the comparison of education administrators’ exertion of authority divided by work experience. However, when each aspect was considered, there were statistically significant differences in the authority of punishment and the sizes of the institutions at statistically significant level of .05.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.048
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.378
Teacher spread0.296 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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