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Record W2466769108 · doi:10.17722/ijme.v7i1.846

The Mediating effect of Conflict Management styles of School Heads on the relationship between Ethical Climate and Organizational Commitment among Public Elementary Schools in region XI

2016· article· en· W2466769108 on OpenAlexvenueno aff
ElizabethA Bernaldez, Gloria P. Gempes

Bibliographic record

VenueInternational Journal of Management Excellence · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsConflict managementPsychologyOrganizational commitmentSobel testOrganisation climateDescriptive statisticsSocial psychologyTest (biology)SociologySocial scienceMathematicsStatisticsEcology

Abstract

fetched live from OpenAlex

This study aimed to investigate the mediating effect of conflict management styles of school heads on the relationship between ethical climate and organizational commitment of teachers among 520 teachers in Davao Region, Philippines. This study employed non-experimental design utilizing descriptive correlation technique. The statistical tools used were mean, pearson-r and regression technique. Research instruments on conflict management styles, ethical climate and organizational commitment which were pilot tested and content validated were used as sources of data. Using pearson-r, the results revealed significant relationships between ethical climate, organizational commitment of teachers, and conflict management styles of school heads. Utilizing medgraph Sobel z-test, the results of the study revealed partial mediating effect of conflict management styles of school heads on the relationship between ethical climate and organizational commitment of teachers. This implies that the mediating role played by conflict management styles of school heads partially assisted in clarifying the process that was responsible for the relationship between ethical climate and organizational commitment of teachers.

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)0.003
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 score0.186
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 science0.0010.000
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 head0.028
GPT teacher head0.270
Teacher spread0.242 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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