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Record W2895787936 · doi:10.3889/oamjms.2018.389

Falsification of Type at Work: Assessment of Prevalence and Investigation of Predictors

2018· article· en· W2895787936 on OpenAlexaff
Nagat M. Amer, Zeinab M. Monir, Salwa Farouk Hafez, Sally Mostafa, Heba Mahdy-Abdallah, Mai Sabry Saleh

Bibliographic record

VenueOpen Access Macedonian Journal of Medical Sciences · 2018
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsDouglas Mental Health University Institute
Fundersnot available
KeywordsMedicineWork (physics)

Abstract

fetched live from OpenAlex

BACKGROUND: Occupational-stress, job-satisfaction and poor health outcomes are closely related and strongly pertain to individuals' mental health and physiological well-being. Falsification of Type is a growing term in the field of organisational psychology that measures occupational stress when working in a job that does not match one's, natural leader. AIM: The present work aims at determining the prevalence of falsification of type and associated socio-demographic and work-related factors. METHODS: The study sample consists of 150 researchers working at the National Research Centre of Egypt. Participants were asked to complete a self-report Falsification of Type Questionnaire, Andrews and Withey scale for Job Satisfaction, in addition to socio-demographic and work-related variables. Statistics included descriptive and comparative analyses. A regression model was built with falsification of the type as the dependent variable. RESULTS: Facilities showed the highest rate of dissatisfaction in the Job Satisfaction Questionnaire. The most prominent manifestations of falsification were fatigue and irritability, and its predictors were the position, interpersonal relationships, facilities and sex according to the regression model. Falsification of type could seriously contribute to occupational stress. Job satisfaction is highly about falsification. CONCLUSION: More research on the Falsification of Type at work is recommended with the greater attention of employers to the importance of the concept of person-job fit.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptMetaresearchResearch integrity
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.220
GPT teacher head0.519
Teacher spread0.299 · 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

Labeled directly by 2 models reading the full record.

MetaresearchResearch integrity

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational
DomainMethods
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
Published2018
Admission routes1
Has abstractyes

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