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Record W3132384259 · doi:10.5267/j.ac.2021.1.011

The role of religiosity in moderating the influence of servant leadership on job satisfaction

2021· article· en· W3132384259 on OpenAlexvenueno aff
Abdul Jamal, Budiyanto Budiyanto, Agustedi Agustedi

Bibliographic record

VenueAccounting · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior and Marketing Influence
Canadian institutionsnot available
Fundersnot available
KeywordsReligiosityPsychologyJob satisfactionServant leadershipModerationSocial psychologySimple random sampleSample (material)Intervening variableApplied psychologyLeadership styleSociology

Abstract

fetched live from OpenAlex

This research aims to analyze the role of religiosity in moderating the influence of servant leadership and job satisfaction on the education office employees’ performances of Pekanbaru City. The sample of the research includes 121 employees and the sampling used a simple random sampling method. This research used closed questionnaires and the results of data are processed using SmartPLS 3.0. The result of the research is: (1) Variable of servant leadership has a significant effect on the employees’ performances, (2) Variable of job satisfaction has a significant effect on the employees’ performances, (3) Variable of religiosity moderating the influences of servant leadership (has a negative significant effect) on the employees’ performance, and (4) Variable of religiosity does not play any moderating role between job satisfaction and employees’ performances.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.022
GPT teacher head0.231
Teacher spread0.209 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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