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Record W2623180463 · doi:10.5539/jel.v6n3p312

Relationship between Job Statisfaction Levels and Work-Family Conflicts of Physical Education Teachers

2017· article· en· W2623180463 on OpenAlexvenueno aff
Hakki Ulucan

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsTurkishJob satisfactionPsychologyScale (ratio)Physical educationVariance (accounting)Social psychologyWork (physics)InstitutionMathematics educationSociologySocial scienceGeography

Abstract

fetched live from OpenAlex

Study aims to examine the relationship between perceived job satisfaction levels and work-family conflicts of the physical education teachers. Research group consists of 154 volunteer physical education teachers that work full time in governmental institutions in Kirşehir city and its counties. To acquire the job satisfaction datum; the Minnesota job satisfaction Scale, developed by Weiss, Dawis, England and Lofquist (1967) and adapted to Turkish version by Baycan (1985), was used. For acquiring the work-family conflict datum the Work-Family Conflict Scale, developed by Netemeyer et al. (1996) and adapted to Turkish by Efeoglu (2006), was used. While there was no meaningful difference determined between groups in the job satisfaction levels of physical education teachers according to gender and working year in the institution variance there was a meaningful difference determined between groups according to age and working year variance. When work-family conflict levels of teachers are considered while there was no meaningful difference found between groups according to gender variance there was a meaningful difference determined between groups according to age and working year in that institution variances. As a result, there was no meaningful relationship found between job satisfaction levels and work-family conflict levels of physical education teachers.

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)0.002
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 score0.065
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.088
GPT teacher head0.394
Teacher spread0.306 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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