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Record W4255250620 · doi:10.32920/14643984.v1

Is Organizational Cynicism Positively Related To Attitude Towards Unethical Workplace Behavior?

2021· preprint· en· W4255250620 on OpenAlexaff
ShiChao Yuan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCynicismSocial psychologyPsychologyTraitPersonalityOrganizational behaviorSkepticismPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

Cynicism is conventionally thought of as a fixed attitude or personality trait characterized by skepticism and a general lack of trust in others. The concept of organizational cynicism was introduced in the early 1990s, when scholars argued that cynicism can be a fluid state and thus can be learned and unlearned based on beliefs, behaviors and affects. The purpose of this study is twofold: 1) to determine whether a positive relationship exists between organizational cynicism and self-reported attitudes towards unethical workplace behavior; and 2) to determine whether exposure to positive or negative organizational information in the form of short articles and sentences would moderate the effects of the aforementioned variables. Results from the study have demonstrated no relationships between the two variables, even taking into account the moderators, with results in p values reaching neither the .05 nor .01 levels. Both hypotheses are thus not supported.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.193
GPT teacher head0.459
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2021
Admission routes1
Has abstractyes

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