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Record W7118119171 · doi:10.17951/sil.2025.34.4.11-27

Mobbing in the Institutional Work Environment: The Example of Polish Prosecutors’ Offices

2025· article· en· W7118119171 on OpenAlexaboutno aff
Aleksandra Malinowska-Bizon, Wojciech Bizon

Bibliographic record

VenueStudia Iuridica Lublinensia · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsnot available
Fundersnot available
KeywordsMobbingHarassmentStatutory lawQuarter (Canadian coin)Work (physics)Phenomenon

Abstract

fetched live from OpenAlex

The survey is part of an identified research gap, which is the issue of mobbing behavior in the environment of common organizational units of the Polish prosecutor’s office. Data was collected by asking 1,891 people (which constituted 12.6% of all employees) in an anonymous survey, both prosecutors and assessors, as well as administrative staff, at all levels of the Polish prosecutor’s office. This is the first study of its kind in Poland and one of the few in general that addresses the institutional legal community. The findings confirm the fact that incidents of harassment at work are more frequent in organizations where duties are routine. The phenomenon of mobbing in the Polish prosecutor’s office is present and is not only of a marginal, incidental nature. Over a quarter of interviewees experienced at work behavior that falls under the statutory definition of mobbing. As expected, the predominant type of professional relationship in which mobbing occurs is a subordinate professional relationship (73% of cases), although in as many as 12% of cases mobbing occurred in equivalent relationships. The results also show the disturbing fact that this type of behavior is not reported (as many as 68% of the mobbed); the main reason being the lack of belief in the effectiveness of such actions and the lack of faith that formal disclosure will change anything. In the light of the facts learned, ways to overcome the identified negative phenomena are given as recommendations.

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 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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.291
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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