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Record W3096190302

Recipe for an epidemic: Environmental perspectives on the 1885 smallpox epidemic and historical anti-vaccination

2020· article· en· W3096190302 on OpenAlexaboutno aff
Gabrielle McLaren

Bibliographic record

VenueSFU Undergraduate Research Symposium Journal · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsnot available
Fundersnot available
KeywordsSmallpoxNationalityEthnic groupVaccinationAppealPopulationIdentity (music)GenealogySociologyPolitical scienceGender studiesGeographyHistoryImmigrationMedicineLawDemographyVirology
DOInot available

Abstract

fetched live from OpenAlex

When smallpox swept through Montreal in 1885, many refused the vaccine that may have spared 3,000 lives and prevented at least 19,905 other cases. Thus far, the epidemic’s literature has linked anti-vaccination sentiment to the linguistic and ethnic identity of Montreal’s French-Canadian Catholic population. This project seeks to deconstruct how class and its impact on the urban environment of Montreal affected anti-vaccination protest. In a rapidly industrializing and urbanizing city, working-class Montrealers living in abject conditions during the epidemic met the smallpox pathogen on their own terms and dealt with it traditionally. Failures of municipal health authorities to appeal and cooperate with this vulnerable demographic and address their concerns led to anti-vaccination sentiment, and even riots. By viewing class, language, and ethnicity-nationality as separate though intersecting aspects of French-Canadian identity, this project seeks to deconstruct culturally deterministic justifications for vaccine rejection and reintegrate environmental concerns in the epidemic’s narrative.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.861
Threshold uncertainty score0.379

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.019
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.119
GPT teacher head0.309
Teacher spread0.190 · 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
Published2020
Admission routes1
Has abstractyes

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