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Record W4408945310 · doi:10.1177/00961442251325201

Neurasthenia and the Modern City: Genealogical Speculations on Capitalism-Urged Anxiety, Stress, and Suicide in North America, 1890–1920

2025· article· en· W4408945310 on OpenAlexaff
Phillip Gordon Mackintosh

Bibliographic record

VenueJournal of Urban History · 2025
Typearticle
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsBrock University
Fundersnot available
KeywordsNeurastheniaAnxietyCapitalismCriminologyHistoryPsychiatryEconomic historySociologyPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

The mental health of turn-of-the-twentieth-century urban North Americans declined under the predations and indifference of laissez-faire capitalism—so much so that physician George Beard associated the emergence of a new and modern “nervousness” with a novel “American” disease: neurasthenia. Neither new nor particularly American neurasthenia did, however, give psychiatric and cultural geographic shape to the pyroclastic eruption of stress in modern urban circumstances. Neurasthenic anxiety had fatal consequences: for many this meant suicide—which reached pandemic proportions by 1900. Here, we encounter an agony we know little about: the suicide club, which affected not just North America but the Western world from Russia west to Hawaii. Does this earlier neurasthenia resonate genealogically in our own late-capitalist, neoliberal, and neo-Victorian anxieties?

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.020
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.286
Teacher spread0.264 · 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 designTheoretical or conceptual
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 routes1
Has abstractyes

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