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Record W2526450326 · doi:10.1093/shm/hkv082

Sandra Opdycke,<i>The Flu Epidemic of 1918: America's Experience in the Global Health Crisis</i>

2015· article· en· W2526450326 on OpenAlexaboutno aff
Nancy K. Bristow

Bibliographic record

VenueSocial History of Medicine · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsGlobeHistoriographyPandemicHistoryQuarter (Canadian coin)PopulationSubject (documents)Coronavirus disease 2019 (COVID-19)Economic historyDemographyPolitical scienceSociologyMedicineLawLibrary scienceDisease

Abstract

fetched live from OpenAlex

In 1976, the distinguished historian Alfred W. Crosby, already credited with writing the path-breaking Columbian Exchange: Biological and Cultural Consequences of 1492, published another influential work, Epidemic and Peace, 1918.1 When the book was re-released years later, Crosby appropriately retitled the text America's Forgotten Pandemic, foregrounding one of the mysteries surrounding his subject, the 1918–19 outbreak of influenza that had raced around the globe, claiming perhaps 50 to 100 million lives. In the United States, over one-quarter of the population had been infected and some 675,000 had died, more than ten times the number of Americans killed in the First World War, with roughly half of those deaths occurring in just a six-week period. Yet for decades, as Crosby hailed with his new title, the outbreak had received little scholarly or popular attention. In recent years, though, study of the pandemic has flourished, attracting scholars from fields reaching from epidemiology and pathology to geography and anthropology. Historians, too, have explored the pandemic from a range of methodological and geographical perspectives, including a flurry of new work on the United States during the scourge. Combining an effective synthesis of this recent historiography with her own perceptive insights, Sandra Opdycke's The Flu Epidemic of 1918 is a welcome addition to this growing literature.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.007
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.128
GPT teacher head0.350
Teacher spread0.222 · 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
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
Published2015
Admission routes1
Has abstractyes

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