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Record W2127120858 · doi:10.5267/j.msl.2013.07.016

A social work study on the effect of gender and marital status on job satisfaction

2013· article· en· W2127120858 on OpenAlexvenueno aff
Mohammad Reza Iravani, Seyyed Saeed Hosseini, Mostafa Rajabi, Akram Fakhri Fakhramini, Shirin Mirhaj, Mina Shirvani

Bibliographic record

VenueManagement Science Letters · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsJob satisfactionPsychologyMarital statusWork (physics)Social psychologySociologyDemographyEngineering

Abstract

fetched live from OpenAlex

Job satisfaction plays an essential role on having happy society since people may have better lives when they fully satisfied with their jobs. In this paper, we present an empirical study to investigate the effect of marital status as well as educational background on job satisfaction. The study performs the study among university employees of Khomeinishar branch located in province of Esfahan, Iran and all questions are designed in Likert scale of 1-5 based on Brayfield & Rothes Index of job satisfaction. Using a sample of 100 people, the study first uses Kolmogrov-Smirnov test and verifies that all data are normally distributed (α=5%). The survey also finds that there is no difference between female and male employees in terms of job satisfaction (α=5%). In addition, the study confirms that marital status has no significance on job satisfaction (α=5%).

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.024
GPT teacher head0.288
Teacher spread0.265 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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