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Record W3110136228 · doi:10.5267/j.msl.2020.11.023

The empowerments’ effect on teachers’ responsibility, self-efficacy, and organizational commitment

2020· article· en· W3110136228 on OpenAlexvenueno aff
Robertus M. B. Gunawan, W. Widodo

Bibliographic record

VenueManagement Science Letters · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEmployee Performance and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsOrganizational commitmentPath analysis (statistics)PsychologyNoveltyContext (archaeology)Structural equation modelingDescriptive statisticsSocial psychologyAccidental samplingEmpowermentKnowledge managementSociologyPolitical scienceComputer sciencePopulationStatisticsMathematics

Abstract

fetched live from OpenAlex

This study explores the empowerments’ effect on organizational commitment mediating by self-efficacy and responsibility. A questionnaire collected research data. The research participants include 375 teachers in Indonesia selected by accidental sampling. Data analysis uses path analysis supported by descriptive statistics and correlational. The results prove that empowerment positively and significantly affects organizational commitment, directly and indirectly, mediating by self-efficacy and responsibility. A fit research model regarding the empowerments’ effect on organizational commitment mediating by self-efficacy and responsibility was found as a novelty. This model can be discussed among researchers and practitioners in developing organizational commitment models in the future and various organizations’ context.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.020
GPT teacher head0.242
Teacher spread0.222 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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