Crime and Gender as Popularised Discourse in Maureen Jennings’ A Journeyman to Grief
Bibliographic record
Abstract
The article deals with the analysis of the novel A Journeyman to Grief (2007) by the contemporary Canadian writer Maureen Jennings with the aim to detect the occurrence of popularised samples of specialised knowledge and communication flanked by the evocative language of the Crime Fiction genre profiling literary womanhood. Handled by – or significantly referring to – female characters, the language is observed in order to comprehend the effectiveness and the compatibility of the different codes conveyed by the medium through a narrative perspective, which is linguistically entrusted to a gender-bound proficiency. Besides, being the plot set in a fictional but plausible historical reconstruction of late XIX century Toronto, the observation includes the examination of discourse events within different communicative situations and the related criteria of perceptibility, familiarity and acceptability of the detechnified terminology transmitted. The linguistic study also considers the social roles embodied by the characters – most of them being male – in contrast with the profiles of the female heroes and villains on the scene and, in accordance with narrative stylistic praxes, with the stereotypes associated with femininity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.027 | 0.032 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".