Film, Fear and the Female: An Empirical Study of the Female Horror Spectator
Bibliographic record
Abstract
This thesis combines feminist theoretical frameworks of analysis with original, empirical research to examine the under-representation of the female horror spectator in critical, academic discourse.The merging of theory and empirical data allows for an in-depth study of the psychological motivations of the female spectator and her relative absence from theoretical study.Drawing heavily upon the work of Brigid Cherry, Justin Nolan and Gery Ryan, this project comparatively assesses fandom as exemplified by the female spectator, as contrasted to the male spectator; the subject of myriad critical investigations of the horror spectator.Utilizing a sample of twenty-two, self-identified female horror fans, this study offers an original glimpse into the preferences, responses and motivations of the female horror fan.The findings of this project support the hypothesis that female horror fans prefer intellectually stimulating films and narratives, regardless of the inclusion of graphic violence.Challenging a variety of misconceptions about horror spectatorship, the present project opens a new line inquiry into a field of investigation previously considered unworthy of study.Finally, this thesis invites further exploration of a new subgenre of horror deemed the cerebral slasher and its unique appeal to the female spectator.Film, Fear and the Female 3 Acknowledgements Many people assisted in the creation and execution of this project.Firstly, I would like to thank my thesis supervisor, Dr. André Loiselle for his support, patience and encouragement.I embarked on this project with enthusiasm and fervour-brimming with ideas and ambition.Dr. Loiselle helped reign in my broad and complex ideas, forming something tangible and fit for study.Some professors would have discouraged empirical research for a thesis in the Humanities, but Dr. Loiselle stood by my decisions and offered the support and guidance to get this project off the ground.Similarly, I'd like to thank Dr. Aalya
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".