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Irish Crime Fiction

2021· reference-entry· en· W4230132092 on OpenAlexaff

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldArts and Humanities
TopicCrime and Detective Fiction Studies
Canadian institutionsTrinity College
Fundersnot available
KeywordsIrishCeltic TigerScholarshipNarrativeHistoryLanguage changeLiteratureCriminologySociologyPolitical scienceLawArt

Abstract

fetched live from OpenAlex

Irish crime fiction is still an emerging field of study. Much of the scholarship concerns Northern Ireland, though that often pays little attention to popular fiction, as is true of Irish Studies more generally. Among the studies most directly concerned with genre fiction, two further focal points are clear. The first is the work of Tana French, among the most prominent Irish crime writers. The second is more general: crime novels read as reflecting on the Celtic Tiger (Ireland’s economic boom in the late 20th and early 21st centuries), on the crash that ensued, and on the cultural complexes arising from and contributing to that boom. Across these focal points, several thematic patterns are clear but not yet fully addressed by scholars: corruption on all sides of the law; a narrative resistance to closure and resolution; Gothic influences; adaptations of domestic noir; and the systemic abuse of women and children by the church, the state, and institutions like the Magdalen Laundries. Indeed, if one category of crime is a defining marker of Irish crime fiction, it is likely to be corruption in all its forms, literal and figurative alike, from Gothic allegories to ripped-from-the-headlines realist narratives. Little attention, however, has been paid to most crime writers predating this contemporary proliferation: even writers who were just barely ahead of the curve—such as Julie Parsons, Vincent Banville, Eugene McEldowney, and Gemma O’Connor—are not regularly addressed at length in scholarly accounts. While Irish contexts and settings distinguish Irish crime fiction from its international counterparts—including the English, Scottish, and American work to which it is most often compared—its particularity is further signaled by several patterns. One is an insistent avoidance of the closure popularly associated with the genre, as in Alan Glynn’s conspiracy thrillers, where uncertainty is an inescapable baseline. Elsewhere, this avoidance reflects Irish literary inheritances like the supernatural, pronounced in the novels of French and John Connolly, and less overt but still clear across their contemporaries’ writings. A third pattern is discernible in the varied means by which Irish writers have adapted familiar subgenres—the police procedural, the private eye, the serial killer—to Irish contexts, which have proven inhospitable to some of these subgenres, a challenge some writers have addressed by setting their work abroad. A final hallmark of Irish crime fiction is a generic instability, a promiscuous mingling of genre elements, including folklore, the supernatural, and romance.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.067
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0090.007
Scholarly communication0.0080.003
Open science0.0020.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0670.021

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 head0.100
GPT teacher head0.292
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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