Representing the Reprehensible: Fairy Tales, News Stories & the Monstrous Karla Homolka
Bibliographic record
Abstract
Fairy tales and news stories are not often linked; however, in many news stories, Canadian media depicted Karla Homolka as both passive princess and evil witch. This paper argues journalists used aspects of popularized fairy tales to shape and give meaning to Homolka's life, personality and crimes, and these constructs created a discourse that limited, liberated and ultimately problematised the public's conception of Homolka. Résumé Les contes de fées et les nouvelles histoires ne sont pas souvent reliés, cependant, les media canadiens ont peint Karla Homolka comme étant à la fois une princesse passive et une mauvaise sorcière. Cet article discute de la façon dont les journalistes se sont servis des aspects des contes de fées popularisés pour façonner et donner une signification à la vie, à la personnalité et aux crimes d'Homolka, et ces constructions mentales ont crée une dissertation qui limita, libéra, et ultimement problématisa la conception que le public a d'Homolka.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.029 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".