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Record W2607364162 · doi:10.5539/ass.v13n5p144

Effect of Competence, Satisfaction and Discipline on Performance of Employees in the Office of Women Empowerment and Family Planning of West Papua

2017· article· en· W2607364162 on OpenAlexvenueno aff
Suyitno Suyitno

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEmployee Performance and Management
Canadian institutionsnot available
Fundersnot available
KeywordsCompetence (human resources)Job satisfactionEmpowermentPsychologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

This study investigates the effect of competence, satisfaction, and discipline on performance of employees in the Office of Women Empowerment and Family Planning of Fak-fak West Papua. Assigning 18 respondents, this study collected data using questionnaire, interview and document and used SPSS 17.0 for analysis on multiple regression and t-test. The findings showed the significant effects existed between (1) the competence of work (X1) on the performance of employee (Y) r=0.682; p=.011; (2) the job satisfaction (X2) with the performance of employee (Y) r=0.241; p=.025; (3) the discipline of work (X3) with the performance of employee (Y) r=0.230; p=.034; and (4) the competence (X1), the job satisfaction (X2), and the discipline (X3) to the performance employee partially or simultaneously at r=0.135. A weak effect of competence, job satisfaction and discipline of work existed on the performance of employee.

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)0.004
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0020.000

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 head0.015
GPT teacher head0.324
Teacher spread0.310 · 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

Citations23
Published2017
Admission routes1
Has abstractyes

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