Bibliographic record
Abstract
This article considers the development of identity within the True Crime Community (TCC) and examines the contagion theory of crime surrounding serial and mass murder within the United States. The TCC is an online Tumblr group that shares pictures, jokes, legends and other narratives surrounding such killers. TCC members are frequently blamed by outsiders for creating spaces where killers become celebrities which, in theory, creates more killers. Two issues arise out of contagion theory. The first is that modes of participation with crime representations and the production of texts around true crimes is shaped by contagion theory and vernacular debates about fandom. Second, contagion theory itself is open to critical cross disciplinary investigation for which folklorists, examining communities who participate in (re)producing true crime texts can offer valuable data, approaches and theory. Moreover, as folklorists working in rumour and contemporary legend have noted, we may have a role to play in interrupting crime cycles themselves.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".