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Record W4412543870 · doi:10.5539/jel.v15n1p38

How to Enhance the Managerial Staff Capacity in Southeast Vietnam’s Primary Schools for Educational Reform?

2025· article· en· W4412543870 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Education and Learning · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Reforms and Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsPedagogyPsychologyPrimary educationProfessional developmentMathematics educationSociologyPolitical science

Abstract

fetched live from OpenAlex

This study investigates enhancing managerial staff capacity in Southeast Vietnam’s primary schools to support the 2018 General Education Program. Using a mixed-methods approach with surveys and interviews (n=262), it assesses Cultural Competency (CC), School Administrative Competency (SAC), Pedagogical Management Competency (PMC), Social Competency (SC), and Change Management Competency (CMC) via structural equation modeling (SEM). Results confirm these competencies drive educational innovation (EI), with CMC having a strong effect (β=0.482, p=0.000), though SC’s negative direct effect on EI (β=-0.214, p=0.001) suggests resource challenges. Five Plan-Do-Check-Act (PDCA)-based solutions—strategic planning, recruitment, training, evaluation, and cultural environment—are proposed to address gaps, offering a roadmap for policymakers to align managerial staff capacity with reform goals.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.788
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.341
Teacher spread0.319 · 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