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Enregistrement W4387776273 · doi:10.5209/cjes.89255

Guillén-Nieto, Victoria. 2023. Hate speech: Linguistic perspectives. Berlin: De Gruyter. 211 pp. ISBN: 9783110672466

2023· article· en· W4387776273 sur OpenAlexaboutno aff
Alicja Paleta

Notice bibliographique

RevueComplutense Journal of English Studies · 2023
Typearticle
Langueen
DomaineComputer Science
ThématiqueHate Speech and Cyberbullying Detection
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSociologyLinguisticsHumanitiesArtPhilosophy

Résumé

récupéré en direct d'OpenAlex

The book by Victoria Guillén-Nieto focuses on hate speech seen through the lens of the combination of various legal and linguistic perspectives which result in several methodologies being called upon to support the analysis of the hate speech phenomenon.The author's starting point is the fact that so far very few significant studies on hate speech in the field of linguistics have been accessible.The general point of view adopted by Guillén-Nieto is that of legal practitioners and linguists who face major difficulties in dealing with language of hatred, particularly with the emergence and rapid evolution of new technologies and social networks.The author develops a linguistic perspective based on data, tools and solutions that linguists may provide to enable legal action to be taken.The macro-structure of the book consists of a preface and eight chapters.In the Preface the reader will find a detailed review of the bibliography on hate speech accompanied by some general considerations on the current status of research on hate speech in various areas of study.Then, the book is divided into two parts: Legal linguistics (Part I -Chapters 1-4) and Forensic linguistics (Part II -Chapters 5-8).Legal linguistics analyses the doctrinal content of the law and its linguistically-based structure, while forensic linguistics is concerned with helping to establish the facts on which a legal decision is based.In Chapter 1. Approaches to the meaning of hate speech, Guillén-Nieto considers various definitions of hate speech and adopts Wittgenstein's concept of family resemblance (2009 [1953]) with the aim of revealing to what extent it can be of use for the researchers in the area of linguistics and law who approach the phenomenon of hate speech.This perspective enables and supports the understanding that hate speech does not have a single meaning but rather several connotations that share certain affinities with each other.Thus it is not possible to identify features that would be shared by all scientific disciplines that deal with hate speech.The aforementioned thesis is proven by the author through Brown's ordinary language analysis (2017).In the following part of the chapter Guillén-Nieto gives an outline of legal scholarly attempts to define the concept of hate speech and she suggests its division into three categories, namely content-based hate speech, intent-based hate speech and harms-based hate speech.This section provides a diachronic overview of research on hate speech and shows very clearly that it might not be possible to create a single unified definition which could be used both in linguistics and legal studies.The author's main aim of this part of Chapter 1 is to show how heterogeneous hate speech is, regardless of the discipline that is chosen as the theoretical framework.The author cites a considerable number of studies that prove her thesis, but it shall be acknowledged that this has been a well-known assumption and a starting point for many studies on hate speech, especially in linguistics.The scholars seem to be aware of the complexity and indefiniteness of the phenomenon.At the same time, given the premise the author makes in the preface about combining legal and linguistic perspectives, it might have been useful to place a little more emphasis on aspects related to the latter, as the legal perspective is by far the dominant one here.The final section of Chapter 1 focuses on approaches to a technical legal definition of hate speech at three levels: international law, common law and civil law (European Union and Member State law).The analysis takes into consideration legal documents such as the Universal Declaration of Human Rights (1948), the International Convention on the Elimination of All Forms of Racial Discrimination (1965), International Covenant on Civil and Political Rights (1966) -for the international law.The common law is represented by Hate Crime Statistic Act, the First Amendment to the Constitution of the United States, Criminal Code of Canada, laws of the United Kingdom, Racial Discrimination Bill (1975) and Racial Vilification Act of Australia.Finally, the author devotes some space to hate speech legislation within the European Union, and particularly she refers to the European Convention on Human Rights, Recommendation No. R (97) 20 of the Committee of Ministers of the Council of Europe to the Member States (1997), the Council Framework Decision (2008) and to Member State law in Germany, France and Spain.What emerges from the considerations exposed in this chapter is the difference between the common law, on the one hand, and the civil/international law on the other.This concept will be furtherly elaborated in the next chapter.At this point, it is worth noting that this is a particularly insightful section of the book, as the author effectively and clearly shows that the differences in legal systems do have a very significant impact on how difficult it is to create a uniform definition of hate speech.Although the differences in European and American legislation are a matter of common knowledge, only a detailed analysis of the legal acts shows that, from the scholarly perspective, a coherent definition of the phenomenon under discussion will be difficult to reach.Indeed, an utterance which under one legal ARTÍCULOS

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)0,002
score de la tête « metaresearch » (Gemma)0,007
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,210
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,007
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
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 Opus0,030
Tête enseignante GPT0,285
Écart entre enseignants0,255 · 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'étudeSans objet
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
Publié2023
Routes d'admission1
Résumé présentoui

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