The Notorious Woman: Tracing the Production of Alleged Female Killers through Discourse, Image, and Speculation
Bibliographic record
Abstract
This dissertation examines the visual and discursive production of female notoriety through the multi-mediated circulation of five images of Amanda Knox and Jodi Arias, who were both convicted of murder; Knox was eventually acquitted.This project employs visual discourse analysis to trace the movement and cultural use of widely shared and debated photographic images by consulting a broad visual corpus of mainstream American media content produced from 2007 to 2016.I argue notoriety is produced out of a necessary general relation of speculation that is (re)produced in processes of mass mediation.I illustrate the visual formation of notoriety by following the cultural use and spread of the selected digital images.Here I claim contemporary notoriety is fueled by repeated calls to speculate and judge images that seemingly resist full understanding while they are also used as evidence of perceived legal and sexual transgressions.This continual play to investigate, interpret, and define ambiguous imagery are key cultural practices that generate notoriety, for these relations compel further judgment and scrutiny.The dissertation draws critical attention to the cultural and visual practices tied to the creation of notoriety in contexts of digital mass media circulation, and questions the types of knowledge and spectatorship that are encouraged as images circulate over time and medium.Through the visual discourse analysis, I conclude these five images are continually used to define and assess Knox and Arias relative to shifting norms of acceptable white femininity.Treating the images as performative sites, I outline their compositional and thematic patterns within the visual corpus (e.g.within news broadcasts, newsmagazine episodes, made-for-TV true crime dramas and documentaries, and literary exposés) that constitute discourses of sexual deviancy, inappropriateness, obsession, vanity, and image management.Through these discursive lenses, Knox and Arias are positioned as sexually transgressive, desirable, and excessive -yet remain debatable and highly scrutinized women because they seemingly iii transgress middle-class white heteronormativity.Taking an intersectional approach, I explore how this constellation of visual discourses works to uphold sexist, classist, and racist logics while also encouraging viewers to see, judge, and consult the familiarly ambiguous images for meaning.I am incredibly fortunate to have had the opportunity to be a part of the Carleton Communication community, and there are a number of people I wish to thank for their support, guidance, and encouragement.Thank you to my supervisor, Dr. Miranda Brady, for your assistance, patience, and reassurance every step of the way through this project.No question was ever too big or too small, and words cannot express how thankful I am for your mentorship throughout this process
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".