New Insights on Workplace Mistreatment: Bystander, Target, Perpetrator, and Group Perspectives
Notice bibliographique
Résumé
Despite substantial insights from prior research, many critical questions about workplace mistreatment remain unanswered. For instance, while both researchers and practitioners emphasize the importance of bystander intervention, little is known about how engaging in such actions affect the bystanders themselves. Similarly, although the harmful effects of leaders’ aggressive behavior on target employees’ work outcomes are well-documented, it is unclear how employees perceive and respond to aggression when it is expressed through humor—a form of communication typically associated with building rapport and fostering positivity. Additionally, questions remain regarding whether employees may misinterpret well-intentioned and constructive actions, such as providing feedback, as abusive or aggressive. Furthermore, while the adage “power corrupts” is well- established, some studies suggest that power can also enhance one’s sense of responsibility. The conflicting evidence and perspectives highlight a gap in understanding the nuanced relationship between power and engagement in mistreatment behaviors. Finally, although research on workplace aggression has grown significantly, there remains a notable scarcity of research on interventions aimed at reducing it—an area that holds considerable promise for practical applications in managing workplace mistreatment. Accordingly, our understanding of workplace mistreatment is still incomplete, necessitating further investigation to uncover new insights. This symposium presents five papers that explore these questions. It considers workplace mistreatment not only from the traditional perspectives of the bystander, target, and perpetrator but also from the broader group perspective. From Bystander to Upstander: The Ripple Effects of Intervening on Bystanders Themselves Author: Rui Zhong; The Pennsylvania State University Author: Yijue Liang; George Mason University Author: Zhanna Lyubykh; Simon Fraser University Author: Ivana Vranjes; Tilburg University The Implications of Leader Humor on Employee Image Management Author: Shubha Sharma; University of Tulsa Can Priming Hostility Lead to Perceiving Abuse in Supervisor Feedback? Author: Hyewon Ji; Author: Huiwen Lian; Texas A&M University Author: Sijun Kim; Texas A&M University Author: Srikanth Paruchuri; Texas A&M University The Deviant (and Beneficial) Effects of Power Sensitivity Author: Nicolais Chighizola; Air Force Academy Author: Trevor Foulk; University of Florida An Interdependence Theory-Based Network Intervention to Reduce Workplace Ostracism Author: Susan Zhu; University of Kentucky Author: Giuseppe Labianca; University of Massachusetts Amherst Author: Nicolina Leeann Taylor; University of Wyoming Author: Seong Won Yang; University of Mississippi Author: Robert Wilhelm Krause; University of Kentucky Author: Dale Watson; The Pennsylvania State University-Penn State Harrisburg Author: Noelle G Otto; University of Kentucky
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».