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Record W2602856067 · doi:10.3167/hrrh.2016.420306

“Such a Poor Finish”

2016· article· en· W2602856067 on OpenAlexvenueno aff
Ginger S. Frost

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsMasculinityWifePunishment (psychology)CriminologyPsychologySpanish Civil WarLawGender studiesPolitical scienceSociologySocial psychology

Abstract

fetched live from OpenAlex

Historians usually analyze changing gender constructions in the criminal courts after World War I through cases involving men and women. Using a different analytical lens this article explores two well-publicized murder trials involving war veterans and illegitimate children, one of a soldier who murdered his wife’s daughter from an adulterous affair and one who killed his own son. Although notions of masculinity had changed, the police, courts, and Home Office used traditional factors to assess punishments, including the degree of provocation, the behavior of the women involved, and the issue of deterrence. The press, however, was more sympathetic to the veterans, regarding them as victims of circumstances, much like women who committed infanticide. This new presentation did not succeed with the Home Office, especially as the war moved further into the past. By 1925, men’s war service had less influence on punishment than Victorian ideas of gender and criminal responsibility.

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)0.004
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.020
Scholarly communication0.0070.013
Open science0.0010.005
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0190.005

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 head0.048
GPT teacher head0.347
Teacher spread0.299 · 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
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

Citations1
Published2016
Admission routes1
Has abstractyes

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