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Record W2018188943 · doi:10.5430/wje.v1n1p165

A Study of Teachers’ Perception of Schools' Organizational Health in Osun State

2011· article· en· W2018188943 on OpenAlexvenueno aff
Alaba Adeyemi Adediwura, Michael Adeniyi Omoyemiju

Bibliographic record

VenueWorld Journal of Education · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Leadership and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPerceptionMathematics educationApplied psychology

Abstract

fetched live from OpenAlex

This study examined the teachers’ perceptions of school organizational health (i.e. resource support, job satisfaction among staff, morale boosts, institutional integrity and initiating structure). Descriptive survey design was used for the study. The sample was composed of 330 secondary school teachers randomly selected from 283, 826 secondary school teachers in Osun State. Data collected was subjected to t-test analysis. It was found that that there is higher homogeneity within the group of male and female secondary school teachers and public secondary school teachers have a higher perception than their private counterpart. In conclusion, governments at various levels who are the proprietor of public schools have the best of teacher who are committed to having good organizational health in the schools. Thus, with little motivation and encouragement this commitment to good organizational health could be transformed into commitment to work and thus, leading to better academic performance of students in the public schools. 

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.097
GPT teacher head0.403
Teacher spread0.306 · 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 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

Citations20
Published2011
Admission routes1
Has abstractyes

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