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Record W4405603054 · doi:10.1080/14780038.2024.2441295

Respectable Men Seeking Odious Work in the Late Nineteenth Century

2024· article· en· W4405603054 on OpenAlexaff
Stephen Heathorn, Greg T. Smith

Bibliographic record

VenueCultural and Social History · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of ManitobaMcMaster University
Fundersnot available
KeywordsWork (physics)HistoryEngineering

Abstract

fetched live from OpenAlex

Using the nearly 1000 unsolicited letters of application for the job of common hangman in 1883, this article examines how these mostly skilled or semi-skilled workmen presented their abilities and credentials for the job. Combining a statistical analysis of the applicant pool with qualitative analysis of the letters and testimonials provided by them, the authors seek to advance the debate about nineteenth-century working-class respectability and its connection to occupational status. They address the paucity of scholarship on how working men in the later nineteenth century presented their credentials and experience for new occupations, and how the hangman letters offer a unique source for understanding how some men did so. The authors conclude that the expected dictates of respectable status were invoked, instrumentally, by the applicants despite the social perception of the hangman role as one of extreme odium, using the kinds of information requested by other ‘adjacent’ occupations – like the military, police and railways – and found in newspaper advertisements.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.008
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.287
Teacher spread0.253 · 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 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
Published2024
Admission routes1
Has abstractyes

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