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Record W2905490537 · doi:10.5430/wje.v8n6p45

Investigation of the Relationship between the Organizational Cynicism Levels and Intent of Revenge of Sports Science Faculty Students Who Work

2018· article· en· W2905490537 on OpenAlexvenueno aff
Sevim Güllü

Bibliographic record

VenueWorld Journal of Education · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsCynicismPsychologySocial psychologyLikert scaleScale (ratio)Descriptive statisticsTest (biology)Data collectionApplied psychologyDevelopmental psychologySocial scienceSociologyPolitical science

Abstract

fetched live from OpenAlex

The research aims to determine the level of relationship between the organizational cynicism and the tendency ofrevenge of sports science students. In this study, descriptive and relational screening technique was used as theresearch technique. The working group consists of 105 students (36 female, 69 male). The participants are studentwho study at Istanbul University Faculty of Sports Science in the academic year of 2017-2018. All of the studentshave been working at an organization/ a workplace for at least 6 months. As the data collection tool, two scales wereutilized with the personal information form prepared by the researchers. Organizational Cynicism Scale and RevengeScale were used. The percentage (%), frequency, skewness, kurtosis, t-test, ANOVA, Pearson Correlation analysiswere used. As a result there is a positive relationship between the level of organizational cynicism and intention ofrevenge. It was revealed that gender and type of employment variables did not make a significant difference inorganizational cynicism and sub-dimensions and will for revenge. However, significant differences have beenidentified in favor of the participants with a low salary in the behavioral sub-dimension of organizational cynicism.On the other hand, the scores of organizational cynicism and will for revenge of the participants are moderate andeven low.

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)0.001
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 score0.003
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.061
GPT teacher head0.315
Teacher spread0.254 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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