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Enregistrement W7117722802 · doi:10.3390/soc16010012

Incivility, Ostracism, and Social Climate Surveys Through the Lens of Disabled People: A Scoping Review

2025· article· en· W7117722802 sur OpenAlex
Gregor Wolbring, Esha Dhaliwal, Mahakprit Kaur

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueSocieties · 2025
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueDisability Rights and Representation
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésIncivilityCivilityOstracismHarassmentNeglectDisabled peopleSet (abstract data type)Empirical research

Résumé

récupéré en direct d'OpenAlex

Incivility and civility have been studied for more than a century across disciplines and in many areas ranging from workplaces to communication, the digital world, and everyday life. They are often used to the detriment of marginalized groups. Their negative use is seen to set the groundwork for other negative treatments, such as bullying and harassment, impacting the social climate in a negative way. Ostracism is seen to be linked to incivility. Disabled people disproportionally face negative treatments, such as bullying and harassment, and experience a negative social climate, as highlighted by the UN Convention on the Rights of People with Disabilities, suggesting that they also disproportionately experience incivility and ostracism. Climate surveys aim to expose toxic social climate in workplaces, schools, and communities caused by incivility, ostracism, bullying, and harassment. As such, how incivility, civility, ostracism, and the design of climate surveys are discussed in the literature is of importance to disabled people. We could find no review that analyzed the use of climate surveys beyond individual surveys and the concepts of incivility and ostracism in relation to disabled people. The objective of our study was to contribute to filling this gap by analyzing the academic literature present in SCOPUS, EBSCO HOST (70 databases), and Web of Science, performing keyword frequency and content analysis of abstracts and full texts. Our findings provide empirical evidence for a systemic neglect of disabled people in the topics covered: from 21,215 abstracts mentioning “civilit*” or “incivilit*”, only 14 were relevant, and of the 8358 abstracts mentioning ostracism, only 26 were relevant. Of the 3643 abstracts mentioning “climate surveys,” 12 sources covered disabled people by focusing on a given survey, but not one study performed an evaluation of the utility of climate surveys for disabled people in general. Racism is seen as a structural problem facilitating civility/incivility. Ableism, the negative judgments of a given set of abilities someone has, and disablism, the systemic discrimination based on such judgments, are structural problems experienced by disabled people, facilitating civility/incivility. However, ableism generated only 2 hits, and disablism/disableism had no hits. Most of our sources focused on workplace incivility, and authors were mostly from the USA. We found no linkage to social and policy discourses that aim to make the social environment better, such as equity, diversity, and inclusion, well-being, and science and technology governance. This is the first paper of its kind to look in depth at how the academic literature engages with the concepts of civility, incivility, and ostracism and with the instrument of social climate surveys in relation to disabled people. Our findings can be used by many different disciplines and fields to strengthen the theoretical and practical discussions on the topics in relation to disabled people and beyond.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,681
Score d'incertitude au seuil0,749

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,050
Tête enseignante GPT0,398
Écart entre enseignants0,348 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle