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Record W2355442027 · doi:10.1080/13555502.2016.1167766

Portraits of the Poor in Early Nineteenth-Century Radical Journalism

2016· article· en· W2355442027 on OpenAlexaff
Rob Breton

Bibliographic record

VenueJournal of Victorian Culture · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsNipissing University
Fundersnot available
KeywordsPoliticsPovertyPortraitJournalismPolitical sciencePolitical economySociologyHistoryMedia studiesLawArt history

Abstract

fetched live from OpenAlex

This paper compares the social-exploration literature of radical, mostly Owenite and Chartist, and liberal journalism in the first half of the nineteenth century, though the focus is on the less known ‘portraits of the poor’ in radical papers. In the paper I argue that against the developing liberal practice of intricately mapping poverty and categorizing the poor, radical papers under-represented particular cases of poverty, using an obfuscating syntax to document the poor. In doing so, radicals differentiated themselves from their middle-class counterparts, primarily as a way to challenge the assumption that poverty was a function of individual error and to turn the public’s gaze onto the social causes of poverty. Highlighting the political dimensions of poverty and minimizing the language of ‘personal responsibility’, radicals demonstrated that the activist agenda concerned itself with the economic and social as much as with the political, even while offering political solutions to economic and social problems.

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)0.009
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.004
Science and technology studies0.0190.039
Scholarly communication0.0130.007
Open science0.0010.010
Research integrity0.0030.005
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 head0.009
GPT teacher head0.262
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

Citations30
Published2016
Admission routes1
Has abstractyes

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