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Enregistrement W3088437292 · doi:10.15353/jirr.v3.419

How Restorative Justice Practices Create Safer More Caring School Communities

2020· article· en· W3088437292 sur OpenAlexaffvenue
Sage Streight

Notice bibliographique

RevueJournal of integrative research & reflection · 2020
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueEducation and Teacher Training
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésHarmSAFERInjusticeRestorative justicePublic relationsAccountabilityContext (archaeology)Retributive justiceSociologyEmpathyEconomic JusticeCriminologyPolitical sciencePsychologySocial psychologyLawComputer security

Résumé

récupéré en direct d'OpenAlex

This paper looks at the traditionally retributive paradigm that is used in Western educational systems to control misbehaviour, issues of injustice, and violence in schools. The paper first talks about the ineffectiveness of this paradigm in creating communities of care and safer schools. The paper then offers that restorative justice (RJ) practices are more effective at creating communities of care and making schools safer. In fact, many schools in North America have been recognizing this and thus implementing RJ practices. The paper looks in depth as to what RJ is and how it is relevant to and works within the school context. This is done to show that RJ changes how individuals view harm. The traditional retributive paradigm views harm as an act of injustice against the state/law, whereas RJ views harm as harm against human beings. This means that RJ fosters understanding, accountability, empathy, connection, and learning positive reconciliation skills that can both be reactive and preventive ways to address harm in schools. Through all these things RJ looks to address the root causes of harm and attend to unmet needs that result from a specific harmful action.
 These findings are important in the paper as they provide an understanding as to why RJ is then relevant in schools. The paper goes on to argue that RJ is relevant in schools because schools are tasked with socializing children, provide behaviour management, and are currently places where violence frequently occurs. These three factors are extremely important in shaping how individuals and communities operate. Because of this, RJ is argued to be necessary and relevant in order to ensure positive and constructive measures. Next, the paper looks at what circles are and how using circles as an RJ practice in schools can create constructive dialogue that leads to understanding that can reduce incidents of harm and injustice and help to develop communities of care. A study by Ortega, Lyubansky, Nettles, & Espelage (2016) is presented to support these findings.
 Furthermore, the paper presents how circles could realistically and effectively be implemented in schools according to Braithwaite (2001). Circles need to be implemented on a school wide level, accessible to everyone, and with the hope that they become an everyday practice for individuals to use to resolve issues of harm and injustice. The paper concludes by reiterating that using circles as an RJ practice creates broader participation in schools and fosters a collective value and stake in what happens within a school. This is done through the intentional dialogue of circles, which is proven to foster community, understanding, and needs being met. Ultimately, this makes schools operate in a more responsible way where individuals look out for how their actions are affecting those around them, ultimately making them more conscious citizens and the school a safer place.

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 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)0,004
score de la tête « metaresearch » (Gemma)0,021
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Études des sciences et des technologies, Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,488
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,021
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,002
Science ouverte0,0000,000
Intégrité de la recherche0,0000,002
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 Opus0,428
Tête enseignante GPT0,551
Écart entre enseignants0,123 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission2
Résumé présentoui

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