Bleeding Panels, Leaking Forms: Reading the Abject in Emily Carroll’s Through the Woods (2014)
Bibliographic record
Abstract
Seeking to move beyond Scott McCloud’s spatio-temporal reading of the bleed (1993: 103), this article explores how Canadian writer/artist Emily Carroll’s graphic narrative Through the Woods (2014) employs the bleed as a means to give form to a mode of horror known as the ‘abject’. Employing theories of embodiment that excavate historical conflations of femininity and nature, in addition to socio-cultural discourses that figure the female body as more uncontrollable than the male, this article explores the anxieties experienced by Carroll’s adolescent protagonists as they traverse the boundary separating girlhood from womanhood. By paying particular attention to Carroll’s excessive use of bleeds, this article argues that the stylistic convention of the bleed is utilised to adumbrate and illustrate the abject horror of such boundary crossings.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.035 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| 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".