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Record 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 on OpenAlexaboutno aff
Alicja Paleta

Bibliographic record

VenueComplutense Journal of English Studies · 2023
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyLinguisticsHumanitiesArtPhilosophy

Abstract

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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

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.030
GPT teacher head0.285
Teacher spread0.255 · 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.

Study designNot applicable
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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