The aim of the current research is to investigate the feasibility of identifying offensive language in Lithuanian by utilising the Simplified Offensive Language Taxonomy (SOLT). The key principle behind this taxonomy is its ability to complement existing offensive language ontologies and tagset systems, with the ultimate goal of integrating it into publicly accessible Linguistic Linked Open Data (LLOD) resources. The dataset used in the current study is a publicly available corpus of user-generated comments collected (...) from a Lithuanian portal (Amilevičius et al. 2016). The study identified that offensive language predominantly focuses on collective derogatory language rather than individuals. The most common category of offensive language is related to physical and mental disabilities, followed by ideological offenses, xenophobic and sexist remarks, and less frequent categories like ageism, classism, homophobia, and religious discrimination. These results highlight the diverse range of offensive language online and underscore the need to combat discrimination and promote respectful discourse, particularly concerning marginalised groups. (shrink)

This paper introduces a streamlined taxonomy for categorizing offensive language in Hebrew, addressing a gap in the literature that has, until now, largely focused on Indo-European languages. Our taxonomy divides offensive language into seven levels (six explicit and one implicit level). We based our work on the simplified offensive language (SOL) taxonomy introduced in (Lewandowska-Tomaszczyk et al. 2021a) hoping that our adjustment of SOL to the Hebrew language will be capable of reflecting the (...) unique linguistic and cultural nuances of Hebrew. The study involves both linguistic and cultural analysis beyond Natural Language Processing (NLP). We employed manual linguistic analysis to understand the nuances of offensive language in Hebrew. An accompanying dataset, gathered on Twitter and manually curated by human annotators, is described in detail. This dataset was constructed to both validate the taxonomy and serve as a foundation for future research on offensive language detection and analysis in Hebrew. Preliminary analysis of the dataset reveals intriguing patterns and distributions, underscoring the complexity and specificity of offensive expressions in the Hebrew language. The aim of our work is to capture the complexity and specificity of offensive expressions in Hebrew beyond what automated NLP methods alone can provide. Our findings highlight the significance of considering linguistic and cultural variations when researching and correcting abusive language online. We believe that our streamlined taxonomy and associated dataset will be crucial in improving research in Hebrew language sociocultural studies, natural language processing, and offensive language detection. Our study also makes a substantial contribution to the study of low-resource languages and can be used as a model for future research on other languages. (shrink)

This study intends to contribute to the delimitation of selected offensive language categories based on an analysis of a corpus of contributions to discussion forums in Czech online national newspapers and news platforms called Czech Corpus of Offensive Language (CCOL). It endeavours to study three problematic areas (1) delimitation between the speech acts performed, (ii) lexical realisation of specific properties of the target and (iii) identification and categorisation of implicit offence (e.g. figurative semantic shifts) by exploring (...) contextual cues for the speech act identification, the keywords indicating the properties of the target and the types of semantic shifts in implicit expressions of offence. The findings indicate that annotation systems that do not use context information for the detection of offensive language may face problems with adequate interpretation of the language means under investigation. (shrink)

The goal of the paper is to present a Simplified Offensive Language (SOL) Taxonomy, its application and testing in the Second Annotation Campaign conducted between March-May 2023 on four languages: English, Czech, Lithuanian, and Polish to be verified and located in LLOD. Making reference to the previous Offensive Language taxonomic models proposed mostly by the same COST Action Nexus Linguarum WG 4.1.1 team, the number and variety of the categories underwent the definitional revision, and the present (...) typology was tested in the annotation on the publicly available offensive language datasets of each of the four languages. The results of the annotation are presented and as they are contained within the accepted statistical values on the inter-annotator agreement in the SOL categories and their aspects, we propose this taxonomy as a core ontology which represents the encoding of the supported offensive languages and justify its use on new data in terms of a more universal Linguistic Linked Open Data (LLOD) schema. (shrink)

The current study represents an integrated model of explicit and implicit offensive language taxonomy. First, it focuses on a definitional revision and enrichment of the explicit offensive language taxonomy by reviewing the collection of available corpora and comparing tagging schemas applied there. The study relies mainly on the categories originally proposed by Zampieri et al. (2019) in terms of offensive language categorization schemata. After the explanation of semantic differences between particular concepts used in the (...) tagging systems and the analysis of theoretical frameworks, a finite set of classes is presented, which cover aspects of offensive language representation along with linguistically sound explanations (Lewandowska-Tomaszczyk et al. 2021). In the analytic procedure, offensive from non-offensive discourse is first distinguished, with the question of offence Target and the following categorization levels and sublevels. Based on the relevant data generated from Sketch Engine (https://www.sketchengine.eu/ententen-english-corpus/), we propose the concept of offensive language as a superordinate category in our system with a number of hierarchically arranged 17 subcategories. The categories are taxonomically structured into 4 levels and verified with the use of neural-based (lexical) embeddings. Together with a taxonomy of implicit offensive language and its subcategorization levels which has received little scholarly attention until now, the categorization is exemplified in samples of offensive discourses in selected English social media materials, i.e., publicly available 25 web-based hate speech datasets (consult Appendix 1 for a complete list). The offensive category levels (types of offence, targets, etc.) and aspects (offensive language property clusters) as well as the categories of explicitness and implicitness are discussed in the study and the computationally verified integrated explicit and implicit offensive language taxonomy proposed in the study. (shrink)

The automatic detection of implicitly offensive language is a challenge for NLP, as such language is subtle, contextual, and plausibly deniable, but it is becoming increasingly important with the wider use of large language models to generate human-quality texts. This study argues that current difficulties in detecting implicit offence are exacerbated by multiple factors: (a) inadequate definitions of implicit and explicit offense; (b) an insufficient typology of implicit offence; and (c) a dearth of detailed analysis of (...) implicitly offensive linguistic data. In this study, based on a qualitative analysis of an implicitly offensive dataset, a new typology of implicitly offensive language is proposed along with a detailed, example-led account of the new typology, an operational definition of implicitly offensive language, and a thorough analysis of the role of figurative language and humour in each type. Our analyses identify three main issues with previous datasets and typologies used in NLP approaches: (a) conflating content and form in the annotation; (b) treating figurativeness, particularly metaphor, as the main device of implicitness, while ignoring its equally important role in the explicit offence; and (c) an over-focus on form-specific datasets (e.g. focusing only on offensive comparisons), which fails to reflect the full complexity of offensive language use. (shrink)

We provide a new text corpus from the social medium Telegram, which is rich in indirect forms of divisive speech. We scraped all messages from one channel of supporters of Donald Trump, covering a large part of his presidency from late 2016 until January 2021. The discussion among the group members over this long time period includes the spread of disinformation, disparaging of out-group members, and other forms of offensive speech. To encourage research into such practices of poisoning public (...) political discourse, we added automatic annotations of offensive language to all messages. We further added manual annotations of harmful language to a portion of the posts in order to enable the analysis of more implicit forms of online harm. (shrink)

The aim of this paper is to shed some light on the linguistic concept of implicit offensiveness. On the one hand, implicitness will be juxtaposed with indirectness as the two concepts are not conceived of here as synonymous. On the other hand, a typology of offensiveness (vs offensive language and vs offendedness) will be proposed, as well as the overarching term ‘covert meaning’ that will span figurative implicitness and non-figurative implicitness. The gradability of various forms of covert meaning (...) and its overlap with overt meaning (subsuming explicit literal meaning and implicit literal meaning) will also be discussed. In the analysis, two sample implicit concepts will be examined (irony vs sarcasm) based on corpus data (of general English and dedicated offensiveness corpus) and using non-contextual embeddings. Theory-wise, the paper demonstrates that implicitness is a complex term which is fuzzy and gradable; methodology-wise, it shows how computational tools can be used to attest theoretical assumptions related to offensive covert terms. (shrink)

One can attack a philosophical claim by identifying a misuse of the language used to state it. I distinguish between two varieties of this strategy: one belonging to Norman Malcolm and the other to Ludwig Wittgenstein. The former is flawed and easily dismissible as misled linguistic conservatism. It muddies the name of ordinary language philosophy. I argue that the latter avoids this flaw. To make perspicuous the kind of criticism of philosophical claims that the second variety makes available, (...) I draw a comparison between Wittgenstein’s recommendation that philosophers study ordinary language and Alfred Schütz’s recommendation that social scientists study the methods of the agents they study. Both do so in an attempt to sensitise philosophers and social scientists respectively to particular artefacts of method which can be easily mistaken for features of that which is studied. (shrink)

. Usually the ethics of humor revolves around the content of humor. After giving a synopsis and exposing some shortcomings of the recent controversies, this paper takes into account additional aspects and proposes a change of perspective from token to type level and deploys tools of the philosophy of language to tackle the question whether a joke as a type can be considered morally flawed irrespective of its tokens. After exploring possible ways one can think of to furnish evidence (...) for the opposite position, two novel lines of argumentation based on counterfactual conditionals and speech act theory are provided to show that these ways aren’t viable and that joke as types are ethically neutral. Moreover, the presented approach increases the resolution of the debate and provides a framework to capture other hitherto neglected questions of the philosophy of humor as well. (shrink)

An objection frequently brought against critical or satirical expressions, especially when these target religions, is that they are ‘offensive’. In this article, I indicate why the existence of diverse and conflicting beliefs gives people an incentive to formulate their complaints in the language of offence. But I also cast doubt on whether people, in saying they are offended really mean to present that as the foundation of their complaint and, if they do, whether their complaint should weigh with (...) us. These doubts do not apply to everything we might find offensive; in particular, they do not apply to simple cases of ‘sensory offence’; but they do apply to ‘belief-based offence’. Relying on offence also implies, inequitably, that different faiths should be differently protected depending on their susceptibility to offence; and the faithful themselves should worry about the flimsiness of claims based on ‘bare knowledge’ offence. I propose a principle of respect for beliefs as a differently grounded and more plausible reason for curbing our treatment of others’ beliefs. However, that principle has a limited compass and is hemmed in by the claims of free expression. It is also less suited to dictating the content of law than to influencing our conduct within the law. (shrink)

Pejorative Language Some words can hurt. Slurs, insults, and swears can be highly offensive and derogatory. Some theorists hold that the derogatory capacity of a pejorative word or phrase is best explained by the content it expresses. In opposition to content theories, deflationism denies that there is any specifically derogatory content expressed by pejoratives. As … Continue reading Pejorative Language →.

Taboo terms offer a playground for linguistic creativity in language after language, and sign languages form no exception. The present paper offers the first investigation of taboo terms in sign languages from a cognitive linguistic perspective. We analyze the linguistic mechanisms that introduce offense, focusing on the combined effects of cognitive metonymy and iconicity. Using the Think Aloud Protocol, we elicited offensive or crass signs and dysphemisms from nine signers. We find that German Sign Language uses (...) a variety of linguistic means to introduce and enhance offense, many of which rely on iconic properties of the taboo sign. In conjunction with cross-linguistically common metonymic word-formation strategies, the degree of visual explicitness of a sign increases its potential to offend. Semantically similar taboo signs based on the same metonymic anchor but differing in their degree of iconicity also differ in offensiveness. This allows for creating dysphemisms and euphemisms via phonological changes to a sign. We further show that embodiment creates modality-enhanced ‘vicarious embarrassment’ in the viewer that results in the respective signs being judged obscene or offensive. Further, lexical blending and non-manual enhancement play a role in the creation of dysphemisms in DGS. Lastly, we propose that iconicity as a cognitive structuring principle of linguistic expressions constrains the possible semantic extensions of iconic taboo terms. (shrink)

Recent artificial intelligence advances, especially those of large language models (LLMs), have increasingly shown glimpses of human-like intelligence. This has led to bold claims that these systems are no longer a mere “it” but now a “who,” a kind of person deserving respect. In this paper, I argue that this view depends on a Cartesian account of personhood, on which identifying someone as a person is based on their cognitive sophistication and ability to address common-sense reasoning problems. I contrast (...) this with a different account of personhood, one where an agent is a person if they are autonomous, responsive to norms, and culpable for their actions. On this latter account, I show that LLMs are not person-like, as evidenced by their propensity for dishonesty, inconsistency, and offensiveness. Moreover, I argue current LLMs, given the way they are designed and trained, cannot be persons—either social or Cartesian. The upshot is that contemporary LLMs are not, and never will be, persons. (shrink)

The rhetoric of Amos includes a wonderful mixture of humour and threat, sarcasm and irony, hyperbole and prediction. Holding the fabric of this conversation together is Amos's place within the prophetic minority - the Yahweh-only party. Making use of sociolinguistics, and particularly the idea of anti-language, I take a closer look at Amos, including his use of overlexicalisation, insider-humour and all the shades of irony one might expect. Typically of a member of an anti-society, Amos exaggerates the differences between (...) insider and outsider, in this case, speaking of 'ivory houses', 'the cattle of Bashan' while appealing to his successful attempts to save the rich from the wrath of God. The offenses of the outsiders are sometimes crystal clear and at other times shrouded in metaphor, and so too is the fate of these people. In reading Amos, we are constantly in danger of falling victim to the persuasive power of his rhetoric. We are drawn into the world of Amos, quickly accepting his boundaries and the ideology of his anti-society, his depiction of reality and his stark caricature of the rich. The rhetoric is persuasive and the irony is divisive forcing a choice of black and white, believer and unbeliever, rich and poor, oppressors and oppressed. We struggle to swim against the current and instead long to respond to Amos's invitation to live - perhaps even to discover that elusive hope at which the book hints: Most of history has been the forging of structures of security and appropriate loyalty symbols, to announce and defend one's personal identity, one's group, and one's gender issues and identity. (shrink)

We encounter offense through various media: an intended facetious remark, a protester’s photographic image of an aborted fetus, an epithet, a stereotypical joke of a minority racial group. People say things that cause offense all of the time. And causing offense can have serious consequences, both personal and professional; the offending party is subject to termination, suspension, or social isolation and public opprobrium. Since the stakes are so high we should have a better understanding of the mechanisms of offense involved (...) in these media and how they work. In this dissertation I focus on two mechanisms for communicating offense—i.e. racial and ethnic slurs and racial humor. First, I lay out a few distinctions concerning the particular kind of offense being targeted, objective versus subjective offense, and when state involvement might be appropriate for penalizing offensive behavior. Next, I discuss racial slurs and the conditions of their offensiveness. I offer a non-content based view of slurs’ offense, which contradicts the consensus view held by most philosophers of language and linguists working on this issue. Also, I look more closely at a purportedly non-offensive use of slurring language, so-called linguistic appropriation, and determine that appropriated uses are permissible in certain settings only under certain conditions. And finally, I propose a tri-partite analysis of racial jokes that provides conditions for when they are merely racial, racially insensitive, or racist. (shrink)

This contribution takes a look at video-sharing platforms to highlight a popular entertainment format which consists in re-framing political discourse for the purposes of entertaining the audience and, at the same time, providing an evaluation of that discourse. Evaluations of political discourse uncover the role and importance imputed to it by those who are outside of the political system, but who are directly impacted by it, that is, the people. A sample of French-language data, collected from YouTube, is examined (...) for the categories of evaluation which are used by the authors, which are conjectured to represent the ideas ordinary citizens have about political discourse. Reframing political discourse carries these evaluations through offensive language and humor. Teasing out the relevant parameters of evaluation can provide a basis for understanding how regular citizens gauge political discourse. Appropriateness appears to be an important evaluation criterion pertaining to the characteristics of political discourse, occurring in a particular context. (shrink)

Harmful and dangerous language is frequent in social media, in particular in spaces which are considered anonymous and/or allow free participation. In this paper, we analyse the language in a Telegram channel populated by followers of Donald Trump, in order to identify the ways in which harmful language is used to create a specific narrative in a group of mostly like-minded discussants. Our research has several aims. First, we create an extended taxonomy of potentially harmful language (...) that includes not only hate speech and direct insults, but also more indirect ways of poisoning online discourse, such as divisive speech and the glorification of violence. We apply this taxonomy to a large portion of the corpus. Our data gives empirical evidence for harmful speech such as in/out-group divisive language and the use of codes within certain communities which have not often been investigated before. Second, we compare our manual annotations to several automatic methods of classifying hate speech and offensive language, namely list based and machine learning based approaches. We find that the Telegram data set still poses particular challenges for these automatic methods. Finally, we argue for the value of studying such naturally occurring, coherent data sets for research on online harm and how to address it in linguistics and philosophy. (shrink)

First published in 1982. Routledge is an imprint of Taylor & Francis, an informa company.

1. Anderson and Lepore (2013) argue that the offensiveness of slur terms can’t consist (merely?) in their having derogatory meanings because even quotation marks fail to prevent offence being cause...

This chapter focuses on one of the common fallacies in Western philosophy, etymological fallacy (EF). To understand the EF fully, it is important to break down the word etymology, which is a practice that in itself informs the conversation surrounding the fallacy. EF is a willful use of a former definition of a word that has changed meaning and/or developed new connotations because the change does not benefit the one committing the fallacy. To avoid committing the EF, individuals should approach (...) language as they would a scientific process: they may hypothesize the word means X, but after further research and consideration, realize that indeed a word now means Y. Either way, the changing nature of language must be considered and individuals should be learned enough and flexible enough to communicate within the time and culture they inhabit. Clinging to etymons while ignoring the evolution and everyday use of language is neither logical nor truthful. (shrink)

The papers collected in this volume exemplify some of the trends in current approaches to logic, language and computation. Written by authors with varied academic backgrounds, the contributions are intended for an interdisciplinary audience. The first part of this volume addresses issues relevant for multi-agent systems: reasoning with incomplete information, reasoning about knowledge and beliefs, and reasoning about games. Proofs as formal objects form the subject of Part II. Topics covered include: contributions on logical frameworks, linear logic, and different (...) approaches to formalized reasoning. Part III focuses on representations and formal methods in linguistic theory, addressing the areas of comparative and temporal expressions, modal subordination, and compositionality. (shrink)

The use of slang, abusive, and offensive language has become common practice on social media. Even though social media companies have censorship polices for slang, abusive, vulgar, and offensive language, due to limited resources and research in the automatic detection of abusive language mechanisms other than English, this condemnable act is still practiced. This study proposes USAD, a lexicon-based intelligent framework to detect abusive and slang words in Perso-Arabic-scripted Urdu Tweets. Furthermore, due to the nonavailability (...) of the standard dataset, we also design and annotate a dataset of abusive, offensive, and slang word Perso-Arabic-scripted Urdu as our second significant contribution for future research. The results show that our proposed USAD model can identify 72.6% correctly as abusive or nonabusive Tweet. Additionally, we have also identified some key factors that can help the researchers improve their abusive language detection models. (shrink)

In her analysis of pejoratives, Eva Picardi rejects a too sharp separation between descriptive and expressive content. I reconstruct some of her arguments, endorsing Eva’s criticism of Williamson’s analysis of Dummett and developing a suggestion by Manuel Garcia Carpintero on a speech act analysis of pejoratives. Eva’s main concern is accounting for our instinctive refusal to endorse an assertion containing pejoratives because it suggests a picture of reality we do not share. Her stance might be further developed claiming that uses (...) of pejoratives not only suggest, but also promote a wrong picture of reality. Our refusal to endorse implies rejecting not only a wrong picture of reality but also a call for participation to what that picture promotes. (shrink)

Orosius is generally considered Augustine’s companion in the debate with Pelagius; however, a careful analysis of his Liber Apologeticus shows that Orosius shares the main features of Jerome’s polemic against Pelagius, thus moving away from Augustine’s approach. Orosius and Jerome used the same source, unknown to Augustine. They depicted Pelagius as the heir of Christian heretics, such as Origen, Priscillian and Jovinian; they both employed offensive language; and, finally, they agreed on the main theological problems involved in the (...) controversy. All of these issues are at odds with what Augustine believed was the right approach against Pelagius. At the end of his Palestinian experience, Orosius was no longer Augustine’s disciple, but rather Jerome’s companion in the struggle against Pelagius. (shrink)

In this paper, I highlight some important implications of a non-individualistic account of derogatory words. I do so by critically examining an intriguing claim of Jennifer Hornsby‘s: that derogatory words – words that, as she puts it, ―apply to people, and that are commonly understood to convey hatred and contempt‖ – are useless for us. In their stead, she maintains, we employ neutral counterparts: words ―that apply to the same people, but whose uses do not convey these things. I argue (...) that Hornsby‘s distinctions – between derogatory words and neutral counterparts, and them (speakers who have use for the former) and us (who do not) – is not sustainable. I begin by considering examples that suggest that some of the words that some of us have use for are indeed derogatory. I then offer reasons for thinking that words that would presumably be identified as acceptable counterparts to derogatory words are not, in general, neutral. (shrink)

Slurs are derogatory words; they seem to express contempt and hatred toward marginalized groups. They are used to insult and derogate their victims. Moreover, slurs give rise to philosophical questions. In virtue of what is the word “chink,” unlike “Chinese,” a derogatory word? Does “chink” refer to the same group as “Chinese”? If “chink” is a derogatory word, how is it possible to use it in a non-derogatory way (e.g., by Chinese comedians or between Chinese friends)? Many theories of slurs (...) answer these questions by assuming that slurs communicate derogatory messages. However, little attention has been paid to the speech acts slurs are used to perform. In this dissertation, I argue that slurs are illocutionary force indicators: words to perform the speech acts of derogation. “Chink” is a derogatory word because its use is to derogate the Chinese, just like the phrase “I promise” has the use to make a promise. To derogate the Chinese is to enforce a norm which assigns to them an inferior normative status. Slurs are also propositional indicators: words that contribute to the truth-conditions. “Chink” has the same referent as “Chinese,” its neutral counterpart. Appealing to speech act theory enables my theory to answer questions about slurs, e.g., slurs can be used in non-derogatory ways because the felicity conditions of derogation are not met. To illustrate the advantage of my theory, I will explain how other theories of slurs fall short because they take positions opposite to mine on certain issues. For instance, Mark Richard’s theory, unlike mine, takes utterances of slurs to have no truth values. It follows from his theory, I will argue, that lying with “Chang is a chink” is impossible. Finally, I will defend the force indicator theory from common objections. My force indicator theory provides a case study of the use theory of meaning and a framework for political philosophers to study the harm of slurs. (shrink)

The use of language in hate speech is understandably offensive. Though words do not kill, they convey an alarming message that can harm the victim. To understand how words can harm, it is necessary to understand the nature of the meaning of pejoratives or slurs that are used in hate speech. Pejoratives are undeniably offensive. However, they are puzzling as they can be used in two directions, namely, the offensive power preservation and the offensive power (...) destruction. This paper proposes that the direct reference theory of pejoratives can solve the puzzle. A characterization of pejoratives is that it has the property of immediacy. They refer directly to the object of speech. Grounding on a shared context, any descriptions are unnecessary for understanding the offensive message of pejoratives. In this sense, pejoratives have indexical content as it is context-sensitive. The kind of indexical content that pertains to pejoratives is action-oriented. However, its object of reference is empty. In discussing pejoratives that are used in hate speech, some examples of Thai slurs are shown. (shrink)

Fictional terms are terms that have null extensions, and in this regard pejorative terms are a species of fictional terms: although there are Jews, there are no kikes. That pejoratives are fictions is the central consequence of the Moral and Semantic Innocence (MSI) view of Hom et al. (2013). There it is shown that for pejoratives, null extensionality is the semantic realization of the moral fact that no one ought to be the target of negative moral evaluation solely in virtue (...) of their group membership. In having null extensions, pejorative terms are much like mythological terms like ‘unicorn horn’ that express concepts with empty extensions, even though it was thought otherwise: people who falsely believed the mythology were mislead into thinking that ordinary objects (i.e. whale tusks) were magical objects, and pejoratives terms work likewise. For example, the term ‘kike’ is supported by the ideology of anti-Semitism, and speakers who fall prey to its influence (perniciously or not) are mislead into thinking that ordinary people (i.e. Jews) are inherently worthy of contempt. In this paper, we explore the consequences of this parallelism, with an eye to criticisms of MSI. In particular, we will re-visit identity expressivist views - those that hold that there are kikes and that they are Jews, and hence deny null extensionality - arguing that this embeds a mistake of fiction for fact. Among the issues to be discussed are the role of fictional truth in understanding pejorative sentences and the relation of the semantics of pejoratives to offensive use of language. We conclude with meta-semantic reflections on the origins of word meanings. (shrink)

This book aims to rehabilitate taking offence. In an era of public criticism of those deemed too easily offended, it is easy to overlook the significance and social value of this emotion. Offence, the book argues, is better understood as a way to defend one’s standing than as a mere expression of hurt feelings. The book defends the significance of offence as one way to resist everyday social inequalities: those details of interactions that, together, pattern social hierarchies. As a result, (...) the defence of offence is of that taken at apparently trivial and small-scale details of social interactions, and so the very form that its opponents find most objectionable. Within societies marred by hierarchies of unequal social standing, and when taken by those who face systematic attributions of lower social standing, an inclination to take offence is a civic virtue. First, this book offers an analysis of offence that depicts a distinctive emotion ripe for moral reappraisal. To take offence resists an affront to one’s social standing and is one way to negotiate the social norms and practices that structure social interactions, often in socially unequal ways. Second, the book defends the significance of our social standing, the cumulative importance of apparently small details of interactions, and offence as an act of insubordination against a social hierarchy. Third, it turns to the limits on when taking offence is justified, addressing jokes, unintentional affronts, disagreement over what counts as offensive, and what we should think of offence that is taken online. (shrink)

Pejorative Language Some words can hurt. Slurs, insults, and swears can be highly offensive and derogatory. Some theorists hold that the derogatory capacity of a pejorative word or phrase is best explained by the content it expresses. In opposition to content theories, deflationism denies that there is any specifically derogatory content expressed by pejoratives. As […].

Is ethics all about rights and duties, or is it about living a happy, flourishing life? For millennia in the West, ethics was about the way to flourish as an individual and a community. The qualities that enable people to live that way are the virtues, and that style of ethics is called Virtue Ethics. In the early modern period, Virtue Ethics went out of fashion and ethics began to focus on right and duties, where rights and duties are demands (...) made against others. In this article I argue that the language of rights and duties has made it almost impossible for people on opposing sides of public policy issues to come to agreement. I defend the return of Virtue Ethics in philosophy, and propose that if it can be adopted by ordinary people, we will have a better chance at overcoming our deep divisions. (shrink)

I argue that the offense generation pattern of slurring terms parallels that of impoliteness behaviors, and is best explained by appeal to similar purely pragmatic mechanisms. In choosing to use a slurring term rather than its neutral counterpart, the speaker signals that she endorses the term. Such an endorsement warrants offense, and consequently slurs generate offense whenever a speaker's use demonstrates a contrastive preference for the slurring term. Since this explanation comes at low theoretical cost and imposes few constraints on (...) an account of the semantics of slurs, this suggests that we should not require semantic accounts to provide an independent explanation of the offense profile. (shrink)

Slurs such as spic, slut, wetback, and whore are linguistic expressions that are primarily understood to derogate certain group members on the basis of their descriptive attributes and expressions of this kind have been considered to pack some of the nastiest punches natural language affords. Although prior scholarship on slurs has uncovered several important facts concerning their meaning and use –including that slurs are potentially offensive, are felicitously applied towards some targets yet not others, and are often flexibly (...) used not only derogatorily to convey offense towards out-group members but also non-derogatorily to convey affiliation with in-group members– the literature remains largely focused on slurs that typically target African Americans, male homosexuals, and sexually active females. Since no account of slurs that typically target Hispanics or Mexican-Americans has so far been proposed, here I offer the first systematic and empirically informed analysis of these that accounts for both their derogatory and appropriative use. Importantly, this article reviews over a dozen Spanish stereotypes and slurs and explains how the descriptive attributes involved in a stereotype associated with a slur can contribute to the predication of certain content in the application of that slur toward its target in context. This article further explains how the psychological effects of stereotype threat and stereotype lift can be initiated through the application of a relevant slur towards its target in context as well. -/- ----- -/- Las expresiones peyorativas tales como spic (‘spic’), slut (‘zorra’), wetback (‘espalda mojada’) y whore (‘puta’) son expresiones lingüísticas que se entienden principalmente para minusvalorar ciertos miembros de un grupo sobre la base de sus atributos descriptivos (como la raza o el sexo). Se ha considerado que las expresiones de este tipo conllevan algunos de los puñetazos más desagradables que el lenguaje natural puede proporcionar. Aunque la literatura especializada sobre expresiones peyorativas ha descubierto varios hechos importantes en cuanto a significado y uso –entre los que se incluyen que tales expresiones son potencialmente ofensivas, apuntan efectivamente hacia unos objetivos pero no hacia otros, y con frecuencia se utilizan con flexibilidad no sólo despectivamente para ofender a miembros por fuera de un grupo, sino que también de forma no despectiva para afiliar con miembros dentro de un mismo grupo–, tal literatura sigue centrada en gran medida en las expresiones peyorativas que típicamente apuntan contra los afroamericanos (nigger ‘negro’), los homosexuales varones (fagot ‘maricón’), y las mujeres sexualmente activas (slut ‘zorra’). En tanto que no se ha propuesto al momento dar cuenta de expresiones peyorativas dirigidas contra hispanos o mexicano-americanos, en este trabajo se ofrece el primer análisis sistemático y empíricamente informado de tales expresiones, tanto en sus usos despectivos y de apropiación. Es importante destacar que en este artículo se revisan más de una docena de estereotipos y expresiones peyorativas en español, además de explicar cómo los atributos descriptivos que participan de un estereotipo asociado con una difamación pueden contribuir a la predicación de determinados contenidos en la aplicación de esa expresión hacia su objetivo en contexto. Asimismo, en este artículo se explica cómo comienzan los efectos psicológicos de la amenaza estereotipada y el realce estereotipado cuando se emplea una expresión peyorativa relevante contra un objetivo en contexto. (shrink)

The best grounds for accepting contextualism concerning knowledge attributions are to be found in how knowledge-attributing (and knowledge-denying) sentences are used in ordinary, nonphilosophical talk: What ordinary speakers will count as “knowledge” in some non-philosophical contexts they will deny is such in others. Contextualists typically appeal to pairs of cases that forcefully display the variability in the epistemic standards that govern ordinary usage: A “low standards” case (henceforth, “LOW”) in which a speaker seems quite appropriately and truthfully to ascribe knowledge (...) to a subject will be paired with a “high standards” case (“HIGH”) in which another speaker in a quite different and more demanding context seems with equal propriety and truth to say that the same subject (or a similarly positioned subject) does not know. The contextualist argument based on such cases is driven by the premises that the positive attribution of knowledge in LOW is true, and that the denial of knowledge in HIGH is true. And where the contextualist has constructed HIGH and LOW wisely, those premises are in turn powerfully supported by the two mutually reinforcing strands of evidence that both of the claims intuitively seem true, and that both claims are perfectly appropriate. The resulting argument for contextualism is very powerful indeed, but I am on the offensive making that case in another paper: “The Ordinary Language Basis for Contextualism and the New Invariantism.”. (shrink)

In Read My Desire, Joan Copjec stages a confrontation between the theories of Jacques Lacan and Michel Foucault, protagonists of two powerful modern discourses - psychoanalysis and historicism. Ordinarily, these discourses only cross paths long enough for historicists to charge psychoanalysis with an indifference to history, but here psychoanalysis, via Lacan, goes on the offensive. Refusing to cede historicity to the historicists, Copjec makes a case for the superiority of Lacan's explanation of historical process, its generative principles, and its (...) complex functionings. Her goal is to inspire a new kind of cultural critique, one that would be "literate in desire," that would be able to read what is inarticulable in cultural statements. Choosing a variety of battlegrounds, from historical phenomena - the 40,000 unsettling photographs of Moroccan drapery taken by Lacan's mentor, G. G. de ClA©rambault; the coincidence between vampire literature and the eighteenth-century imperative to breast-feed; the recurrent emptiness of urban spaces in film noir; the rise of democracy and questions of human rights - to theoretical concepts such as the gaze, cause, and sexual difference, Copjec imagines the blows that each contender might strike. Although Lacan emerges the victor, one has a sense that for Copjec the contest is close, that she is interested not in simply dismissing Foucault but in seizing his theory at those moments when its concerns and strategies are similar to Lacan's. She is intent on understanding how two compelling theories come to diverge, how small differences distort common assumptions. Establishing the links between psychoanalysis and critical philosophy, Copjec treats psychoanalysis not as a private language but as the mother tongue of modernity. She thus makes Lacan's famous "return to Freud" a return, as well, to the best principles of the Enlightenment. By this maneuver she forces us to question the historicist dialect that we have been taught to speak and that we all but take for granted and to regret the loss in it of psychoanalysis's more rousing accents. (shrink)

Allegorical interpretation of the ancient Greek myths began not with the grammarians, but with the philosophers. As speculative thought developed, there grew up also the belief that in mystical and symbolic terms the ancient poets had expressed profound truths which were difficult to define in scientifically exact language. Assuming that the myth-makers were concerned to edify and to instruct, the philosophers found in apparent immoralities and impieties a warning that both in offensive and in inoffensive passages one must (...) look beneath the surface for the true significance of the tales. Thus allegory was originally positive, not negative, in its aim; its purpose was not so much to defend the poetic traditions against charges of immorality as to make fully explicit the wealth of doctrine which ex hypothesi the myths contained. Those who wrote to defend the poets could, if they chose, make some use of the results of the allegorical method; passages to which exception had been taken could be shown by allegorical treatment to be quite consistent with the view that the poets were wise and divinely inspired. But the first dim beginnings of allegory can be traced to another and a weightier motive—namely, the desire of speculative thinkers to appropriate for their own use some at least of the mythical traditions. Nor is there any reason to doubt that the same motive was the main driving force in the later history of allegorical interpretation. Objectionable passages were, indeed, regarded as among the richest in deeper meaning; but the leading allegorists applied their method to offensive and inoffensive passages alike. (shrink)

Millions of memes are created and shared every day on social media platforms. Memes are a great tool to spread humour. However, some people use it to target an individual or a group generating offensive content in a polite and sarcastic way. Lack of moderation of such memes spreads hatred and can lead to depression like psychological conditions. Many successful studies related to analysis of language such as sentiment analysis and analysis of images such as image classification have (...) been performed. However, most of these studies rely only upon either one of these components. As classifying meme is one problem which cannot be solved by relying upon only any one of these aspects, the present work identifies, addresses, and ensembles both the aspects for analyzing such data. In this research, we propose a solution to the problems in which the classification depends on more than one model. This paper proposes two different approaches to solve the problem of identifying hate memes. The first approach uses sentiment analysis based on image captioning and text written on the meme. The second approach is to combine features from different modalities. These approaches utilize a combination of glove, encoder-decoder, and OCR with Adamax optimizer deep learning algorithms. Facebook Challenge Hateful Meme Dataset is utilized which contains approximately 8500 meme images. Both the approaches are implemented on the live challenge competition by Facebook and predicted quite acceptable results. Both approaches are tested on the validation dataset, and results are found to be promising for both models. (shrink)