Spooking the System: Re-evaluating Belief Formation Through Psychological Disturbance and Supernatural Encounter in Early Modern English Drama
Notice bibliographique
Résumé
This dissertation explores the early modern English stage as a significant site for producing, exploring, and meditating on psychological uncertainty, specifically through encounters between human characters and representations of the supernatural.I argue that the psychological disturbance these encounters engender allows for a re-evaluation of the process and nature of belief formation.Rather than dismiss dramatic supernatural representations as theatrical spectacles void of critical significance, I argue that the supernatural can be productive conduits for exploring the psychological complexities of the human mind.I demonstrate that because ghosts, devils and witches are products of the same theological and philosophical systems which conceptualize the workings of the early modern mind, they are able to infiltrate and influence the aspects of human psychology which are particularly susceptible to doubt and desire.These encounters then result in the psychological unravelling of human characters, who must navigate conflicting ideals in order to move towards action.However, the experience of this internal struggle is significant not only for revealing the competing influences characters must reconcile in the process of forming beliefs and opinions, but also for emphasizing the importance of critical evaluation of the discourses of belief that surround them, regardless of external pressure to blindly accept them.As ghosts, devils and witches are supernatural figures rooted in the religious, social and political ideologies that shape early modern English belief, so are they imbued with a powerful potential to shake the foundations of those belief systems of which they themselves are part.I analyze supernatural representations of these figures in plays by Shakespeare, Middleton, Marston, Chapman, Goffe and Marlowe, and the psychological effects of their encounters with human characters, in order to examine how they can facilitate alternative perceptions of beliefs around gender and power in sixteenth and seventeenth-century England.I would like to start off by thanking the wonderful faculty, staff and students of the Department of English, who have all contributed to creating such a warm, communal and collegial environment.I feel very lucky to have been part of this department for the last five years, as it has taught me so much about what it means to be a colleague, a teacher, a mentor, and an involved member of an academic community.I would like to extend thanks particularly to Dr. Julie Murray and Dr. Brian Johnson, who, in their roles as graduate supervisor, provided invaluable guidance and advice, not only about the degree program and its requirements, but about life in academia beyond the PhD.Thank you for always having an open door, a welcoming demeanor, and the patience to reassure me through the various bumps along the way.Thank you also to Lana Keon and Priya Kumar, the superb graduate administrators who always have all the answers, whose tireless efforts make life so much easier for the rest of us, and who are always available for a hug or a pep talk.I would also like to thank the internal members of my dissertation committee, Dr. Micheline White
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,008 | 0,025 |
| Communication savante | 0,011 | 0,008 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,001 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».