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Record W4407991644 · doi:10.1080/00947679.2025.2468166

Building Urban Community in Late Imperial Russia: Early Twentieth-Century Kopeck Newspapers as Local Institutions

2025· article· en· W4407991644 on OpenAlexafffund
Felix Cowan

Bibliographic record

VenueJournalism History · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Cultural and National Identity
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNewspaperHistoryEconomic historyPolitical scienceAncient historyLaw

Abstract

fetched live from OpenAlex

This paper explores the community functions of the penny press in the cities of the Russian Empire in the early twentieth century. Cheap tabloid newspapers facilitated the social needs of residents in the empire’s growing cities and towns, easing the ebb and flow of daily urban life by offering a forum for mass communication, fostering public dialogue, and acting as institutions of public assistance and small-scale charity, albeit always in ways mediated by the desires and preferences of journalists, editors, and publishers. In so doing, they helped readers and local community members bring order to the chaos of urban life in a time of rapid migration and urbanization. By exploring these community functions, this article furthers our understanding of both the potential social and institutional roles of urban newspapers and the specific role played by popular journalism in the cities of the autocratic Russian Empire.

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)0.002
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 score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.008
Scholarly communication0.0070.003
Open science0.0000.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.309
Teacher spread0.274 · 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
Published2025
Admission routes2
Has abstractyes

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