Bibliographic record
Abstract
Abstract In early 2014, several articles appeared proclaiming the rise to prominence of a new subgenre of the crime novel: “chick noir,” which included popular books like Gone Girl, The Silent Wife, and Before We Met. However, there was also resistance to the new genre label from critics who viewed it as belittling to women’s writing and to female-focused narratives. Indeed, the separation of female-centred books - whether “chick lit” or “chick noir” - from mainstream fiction remains highly problematic and reflects the persistence of a gendered literary hierarchy. However, as this paper suggests, the label “chick noir” also reflects the fact that in these novels the crime thriller has been revitalized through cross-pollination with the so-called chick lit novel. I contend that chick lit and chick noir are two narrative forms addressing many of the same concerns relating to the modern woman, offering two different responses: humour and horror. Comparing the features of chick noir to those of chick lit and noir crime fiction, I suggest that chick noir may be read as a manifestation of feminist anger and anxiety - responses to the contemporary pressure to be “wonder women.”
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".