Occupational Burnout among Employees in Serbian Banking Sector: Evidence during Covid-19 Pandemic
Bibliographic record
Abstract
This paper examines occupational burnout among employees in the banking sector in Serbia, with an emphasis on the Covid-19 pandemic. Workload, short deadlines, role ambiguity, role conflict, lack of autonomy, job insecurity, new technologies, overly demanding clients, constant pressure for high performance, and fierce and increasing competition make the banking sector one of the most stressful. Banking institutions have undergone various changes in their strategies, organization, and structure in the past due to new technologies, processes, and working conditions caused by the Covid-19 pandemic. The research results of conducted empirical study based on the Maslach Burnout Inventory, in which 165 employees from Serbian banks participated in the first quarter of 2022, revealed a higher level of emotional exhaustion among employees who had daily direct contact with clients and those who worked from office, a higher level of depersonalization among male respondents, and a lower personal accomplishment among employees with less working experience.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".