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Record W2334502844 · doi:10.1093/ahr/119.2.612a

Paul O'Leary. Claiming the Streets: Processions and Urban Culture in South Wales, c. 1830–1880.

2014· article· en· W2334502844 on OpenAlexaboutno aff
Andy Croll

Bibliographic record

VenueThe American Historical Review · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsProcessionNewspaperUrban culturePeriod (music)HistoryMonsterCrowdsMedia studiesConsciousnessHappeningSociologyArt historyArtPerformance artAestheticsLawArchaeologyPolitical science

Abstract

fetched live from OpenAlex

This is a study of the rich processional culture that flourished in the towns of early and mid-Victorian South Wales. The period saw an almost endless series of crowds winding their way through their towns' main streets. While not a novel cultural practice, the Victorian procession was more democratic than it had ever been, and as a result of the burgeoning newspaper industry, its impact on the consciousness of urbanites was greater than ever. Even if some town-dwellers happened to miss a particular “monster demonstration,” they could read about it, often at great length, in their local papers. In Paul O'Leary's hands, the procession is shown to be something that is richly suggestive of the multiple ways in which different groups reacted with each other and with the wider urban public. As others have argued, processions and parades can be read as texts, charged with meanings that can be teased out by the perceptive analyst. The book's opening sections demonstrate the author's impressive command of the scholarly literature, with references to an array of anthropologists, historians, and sociologists of street culture. Moreover, there are references throughout to parades in many different urban contexts—from Toronto to Barcelona and various points in between—that serve to contextualize the South Wales experience.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.583
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.237
Teacher spread0.212 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2014
Admission routes1
Has abstractyes

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