Understanding and mitigating cynicism in the workplace
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.
Bibliographic record
Abstract
Purpose – Organizational cynicism is on the increase. The purpose of this paper is to explore how dispositions promote cynical attitudes and how to mitigate the negative impact of organizational cynicism for employees. Design/methodology/approach – The data consisted of two samples ( n =312 and n =529) of employed adults. All participants completed online surveys containing the variables of interest. The hypothesized model was tested using structural equation modeling. Findings – Low levels of core self-evaluation (CSE) predict organizational cynicism which, in turn, mediates the relations between CSE and job attitudes. Importantly, the authors find that supervisory support moderates both the relations between CSE and organizational cynicism and organizational cynicism and job satisfaction. Originality/value – Little research has directly assessed the role of dispositions in the development of organizational cynicism. The authors suggest that CSE contributes to the development of cynical attitudes. Further, the authors demonstrate that a supportive supervisor can serve as a buffer to mitigate the expression and effects of organizational cynicism on workplace outcomes.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it