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Enregistrement W899766299

Christie Davies. Jokes and Targets

2012· article· en· W899766299 sur OpenAlexvenueno aff
Molly McBride

Notice bibliographique

RevueEthnologies · 2012
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueMisinformation and Its Impacts
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésJokeStupidityImmoralityMeaning (existential)Order (exchange)PoliticsSociologyPsychologyEpistemologyLiteratureLawArtPolitical scienceMoralityPhilosophy
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Christie Davies. Jokes and Targets. (Bloomington: 2011, Indiana University Press. 328 pp. ISBN: 978-0-253-22302-9) In Jokes and Targets, Davies explains how certain joke cycles that have targets move throughout time and place. Specifically, as his title suggests, he explores how certain groups of people have become the targets of certain scripts. In considering jokes as social facts, Davies focuses on the social and political contexts that give jokes meaning in order to understand the nature of targets. His objective for this text, which becomes clear only in the conclusion, is to build upon and refine his previous models of jokes and their targets. Working towards a grand theory of jokes and targets, Davies asserts that his center-periphery model (1990), monopoly-competition model (2009), and mind-over-matter model further elucidated in this text should be used together to fully grasp the place of jokes in society. The text is organized into six chapters that center on either a target or script that targets. The joke cycles, or themes, examined are: jokes about stupidity and canniness, libidinous blondes and people, Jewish people, men's sexuality, American lawyers, and the Soviet Union. Jokes about the French, lawyers, and Jewish men and women are explained in terms of their historical and political contexts, whereas jokes for which there is no set target (for example those about stupidity) are explained by drawing connections between targeted groups. These differences in analytical approaches can at times obfuscate the purpose of the text, but the contrasts raise further questions that others can build upon. Chapter One, Mind Over Matter, groups stupidity jokes and canny jokes into one cycle based on the dichotomy between mind and body (47), intelligence and the material (67). This chapter covers extensive ground, discussing eight target groups, ranging from the militia to blondes. Readers gain a more generalized view of stupidity and canny joke scripts rather than the specific contexts of each target group. It is mainly this chapter on the mind-over-matter model that Davies connects to his previous work. Chapter Two begins with a brief examination of sex jokes about blondes and then focuses for the majority of the chapter on sex jokes about people. The contextualization and analysis of jokes is the strongest section of the book; the chapter would have more coherence if the section on blonde women was omitted. Davies concludes that while blonde jokes are not actually about blondes (they are about specific values of beauty), jokes are about the French (112). This difference raises issues that scholars could pursue in the future: what types of meanings arise from contrasting jokes with set targets and joke scripts without set targets? The rest of the book presents similar issues with different targets and scripts. Chapter Three delves into various joke scripts about Jewish femininity and masculinity that have been created and told both by Jewish and non-Jewish people. In Chapter Four Davies examines two types of joke scripts about men: intimacy in homosocial situations and homosexual or feminine men. Chapter Five examines the American lawyer joke cycle and ties its movement and meaning to the American political system. The final cycle Davies examines is Soviet Union jokes created by citizens to criticize the former state. Because of the varying nature of scripts in each cycle, the organization of theoretical work can at times be confusing. Some chapters seem to he based on a target and the various scripts told about the target, such as the chapters on people and lawyers; other chapters appear to focus on open-ended cycles that contain various scripts and targets within, such as Chapter One. …

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)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,669
Score d'incertitude au seuil0,245

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
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 Opus0,049
Tête enseignante GPT0,348
Écart entre enseignants0,299 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations1
Publié2012
Routes d'admission1
Résumé présentoui

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