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Record W6902589798 · doi:10.6093/2035-8504/8605

Crime and Gender as Popularised Discourse in Maureen Jennings’ A Journeyman to Grief

2021· article· en· W6902589798 on OpenAlexaboutno aff

Bibliographic record

VenueUniversità degli Studi di Napoli Federico II · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicCrime and Detective Fiction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeEmbodied cognitionTerminologyGriefDiscourse analysisSet (abstract data type)

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.052
GPT teacher head0.286
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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