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Record W3046842922 · doi:10.5267/j.msl.2020.7.037

Organizational climate, organizational citizenship behaviour and turnover intention: Evidence from Jordan

2020· article· en· W3046842922 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueManagement Science Letters · 2020
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsTurnover intentionOrganizational citizenship behaviorOrganizational commitmentOrganisation climateCitizenshipPsychologyTurnoverBusinessSocial psychologyPolitical scienceEconomicsManagementPolitics

Abstract

fetched live from OpenAlex

The present paper attempts to analyse the effect of organizational climate on organizational citizenship behaviour (OCB), as well as the effect of OCB on turnover intention. Data on organizational climate, OCB and turnover intention were obtained from a sample of 78 internal auditors of Jordanian private universities. Hypotheses were proposed and were tested using PLS-SEM, and the outcomes demonstrate the positive linkage between organizational climate and OCB. Meanwhile, OCB and turnover intention were found to have inverse linkage. Strong organizational climate should be created in Jordanian private universities since it improves and predicts OCB. OCB will in turn cause turnover intention to decrease among internal auditors. With the use of PLS-SEM method, this study adds to the extant literature.

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.

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)0.000
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 score0.202
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.020
GPT teacher head0.218
Teacher spread0.198 · 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