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Record W4412702166 · doi:10.5539/jel.v14n6p396

Priority Needs for Participative Administration Focusing on Safety in Schools Under Primary Educational Service Area Office in North-Eastern Region

2025· article· en· W4412702166 on OpenAlexvenueno aff
Nonglagk Choobsuwan, Pacharawit Chansirisira

Bibliographic record

VenueJournal of Education and Learning · 2025
Typearticle
Languageen
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsReliability (semiconductor)Sample (material)Service (business)PsychologyMedical educationSample size determinationAdministration (probate law)Operations managementApplied psychologyStatisticsMedicineBusinessMathematicsEngineeringPolitical scienceMarketing

Abstract

fetched live from OpenAlex

This research aimed to 1. study compositions and indicators of participative administration focusing on primary school safety 2. study current condition, desirable condition and priority needs of primary school safety; and 3. study guidelines of participative administration focusing on primary school safety. The research was divided into 3 phrases, which were 1) synthesizing composition and indicator towards school safety, 2) doing survey about current condition, desirable condition, and synthesis of primary school safety, and 3) seeking guidelines for participative administration focusing on primary school safety. The sample consisted of 370 school administrators and teachers, selected based on the sample size table by Krejcie and Morgan, using a multi-stage sampling method. The research tool was a questionnaire, with a reliability coefficient of 0.97 for the current condition and 0.98 for the desirable condition. Data were analyzed using percentage, mean, and standard deviation.The sample group was a group of 370 administrators and teachers with the size that follows Krejcie & Morgan’s table pattern. The group members were selected by multi-stage sampling method. The tool was questionnaire which had reliability on current condition at 0.97 and 0.98 for desirable condition. The data was analyzed using percentage, average, and standard deviation. Priority Needs Index (PNI) was also applied in the analysis, it was found that, 1. There are 5 compositions of primary school safety with 15 indicators. They are 1) student-assistant system 2) prevention and solution methods for accidents within schools 3) prevention and solution methods for accidents related to natural disasters 4) prevention and solution methods for social issues, and 5) student’s well-being control. For participative administration, it has 5 compositions which are 1) participation in planning process 2) participation in work operation 3) participation in decision-making method 4) participation in supervision, and 5) participation in monitoring and evaluation. 2. The overall current condition of participative administration focusing on primary school safety was at a fair level, while the overall desirable condition was at a high level. The most critical need identified was the prevention and resolution of accidents in educational institutions. 3. Participatory management guidelines for primary school safety should emphasize the involvement of all stakeholders in the planning process-from policy formulation and collaborative planning to joint decision-making. Additionally, support should be provided for private organizations to participate in management efforts, including organizing study visits to learn effective strategies for collaborative problem-solving.

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)0.010
metaresearch head score (Gemma)0.018
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 score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.098
GPT teacher head0.478
Teacher spread0.380 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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