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Record W2140910283 · doi:10.5267/j.msl.2013.10.023

Investigating the effect of work stress, general health quality, organizational intelligence and job satisfaction on employee performance

2013· article· en· W2140910283 on OpenAlexvenueno aff
Masoud Samadzadeh

Bibliographic record

VenueManagement Science Letters · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
FundersIslamic Azad University
KeywordsJob satisfactionPsychologyJob performanceQuality (philosophy)Applied psychologyJob stressWork (physics)Employee researchOrganizational commitmentBusinessSocial psychology

Abstract

fetched live from OpenAlex

During the past few years, there have been tremendous efforts on measuring the effects of different factors such as work stress, general heath quality, etc. on performance of employees. In this paper, we present an empirical investigation to study the effects of work stress, general health, organizational intelligence and job satisfaction on employee performance. The proposed study of this paper uses two questionnaires where one is associated with general health quality (GHQ) with 20 questions and the other one consists of 12 questions, which is associated with work stress. The study chooses a sample of 144 employees from 222 people who worked for one of Islamic Azad University in Iran. Cronbach alphas for work stress, general health, organizational intelligence, job satisfaction and organizational performance are 0.911, 0.895, 0.795, 0.863 and, 0.864, respectively. The results indicate that job satisfaction has the highest influence on organizational performance followed by other factors.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.019
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.017
GPT teacher head0.257
Teacher spread0.240 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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