MétaCan
Menu
Back to cohort
Record W4406726948 · doi:10.7202/1115683ar

The Impact of the 1918 Influenza Pandemic on the Demography of the Island of Newfoundland in the First Half of the Twentieth Century

2023· article· en· W4406726948 on OpenAlexvenueaboutno aff
Lisa Sattenspiel, Taylor P. van Doren, Jessica Dimka

Bibliographic record

VenueNewfoundland and Labrador Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsInfluenza pandemicPandemicGeographyDemographyGenealogyHistoryCoronavirus disease 2019 (COVID-19)MedicineSociologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The early twentieth century was a time of dramatic social, economic, political, demographic, and health-related change in Newfoundland and Labrador. One of the major upheavals at this time was the 1918 influenza pandemic, which led to the deaths of nearly 2,000 residents of the Dominion. In this paper we examine the short- and long-term demographic consequences of this catastrophic event. We focus on changes in the overall age and sex distribution, fertility levels, and cause-specific (for selected causes) and overall mortality before, during,and after the 1918 pandemic. Data on these demographic processes and the prevalent social conditions have been collected at The Rooms, the Digital Archives at Memorial University of Newfoundland, and other archives in the province and online. Results indicate that, although the 1918 pandemic had major impacts over the short term on fertility, mortality, and the age and sex structure, both on the island as a whole and in every region analyzed, these effects were of short duration. Long-term demographic changes occurring on the island duringthe first half of the twentieth century appear to be more related to the large-scale socio-economic changes that occurred through the long process of moving from an independent Dominion to Confederation with Canada.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
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 head0.027
GPT teacher head0.294
Teacher spread0.266 · 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; both teacher heads agree on what is shown here.

Study designObservational
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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueNewfoundland and Labrador StudiesSame topicCanadian Identity and HistoryFrench-language works237,207