Not All Dead White Men: Classics and Misogyny in the Digital Age by Donna Zuckerberg
Notice bibliographique
Résumé
BOOK REVIEWS/COMPTES RENDUS 405 them. The sections on Australia and the United States also raise the issue of introduced species and the impact they have on native ecosystems, as well as the ethics surrounding their treatment as feral populations. The final chapter (“The Donkey’s Tale”) summarizes the main arguments that run throughout the book. Mitchell explains how we can use donkeys to study human history, as well as the potential risks of such study. One risk is anthropocentrism, which results in viewing the donkey as simply an agent that benefited humans. This does not allow researchers to fully study the human-donkey relationship, as it makes the donkey a human tool rather than a being capable of influencing actions through its own decisionmaking process. Finally, the author presents the reader with avenues for future research, indicating that this text is not meant to be the final word on donkeys in history, but rather the beginning of a dialogue on the topic. This book is a valuable addition to the fields of animal studies, zooarchaeology, history, and anthropology. Mitchell’s writing is clear and succinct, and the language used appealing to both specialists and newcomers to the topic. The text is lavishly illustrated with black-and-white images as well as colour plates. One puts this book down with a new perspective not just on the donkey in human history, but rather on how much of human history was possible because of the donkey. Mount Royal University Carolyn Willekes Not All Dead White Men: Classics and Misogyny in the Digital Age. By Donna Zuckerberg. Cambridge, MA: Harvard University Press. 2018. Pp. 270. In this book, Donna Zuckerberg tackles head-on the relationship between some contemporary forms of misogyny and the classical world. It is a short, readable work combining scholarly approaches, analyses, and citational habits with an accessible narrative, tone, and style. It explains both the ancient and the social media world where necessary, while giving a nuanced and thoughtful account of the intersections between them that will be enlightening to classical scholars and savvy social media users alike. Zuckerberg clearly lays out the various groups connected to the most virulent expressions of online misogyny, where they have come from, what their views are, and how they use classical texts as justification, support, and inspiration for those views and their dissemination. Her aim is to uncover the mechanisms by which antiquity is used and mythologized to perpetuate patriarchal and white supremacist ideology; she hopes both to combat that ideology and to point towards a “vibrant, radical, intersectional feminist classics—one that uses the ancient world to enrich conversations about race, gender, and social justice” (188). The book is divided into four chapters, with a brief Introduction and Conclusion. It has extensive endnotes, a glossary, and a detailed bibliography. The first chapter, “Arms and the Manosphere,” outlines the online world of toxic masculinity, with terms and definitions and a sketch of what she often refers to as the “Red Pill community,” a collective term for a number of online groups whose membership is primarily or exclusively male and mostly white, and whose views centre around misogyny and opposition to feminism. Even those readers with some familiarity with the terms “Red Pill,” “MGTOW” (“Men Going Their Own Way”), “pickup artists,” and so forth will find this section clarifying, as the aims, ideologies, and memberships of these groups intersect in complicated ways, 406 PHOENIX while for many readers this chapter will serve as an essential introduction to an important subset of the online world. Zuckerberg delineates how the actual misogyny of the ancient world provides resources for modern misogyny, bolstered by the social and cultural capital of classics. This chapter demonstrates how easily some ancient texts, and the traditional approach to studying them, can be used to support extreme positions today. Zuckerberg also points out some similarities between the manosphere’s use of antiquity and attitude toward classics and feminism and the views and attitudes of some classical scholars—not only in the past, but also in the present. In the second chapter, “The Angriest Stoics,” the main topic is the appeal of Stoic philosophy and ancient Stoic writers for the Red...
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».