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Health and Immigration in Argentina, 1870–1950

2025· reference-entry· en· W4409408194 on OpenAlexaff
Benjamin Bryce

Bibliographic record

VenueOxford Research Encyclopedia of Latin American History · 2025
Typereference-entry
Languageen
FieldArts and Humanities
TopicHistory of Medicine and Tropical Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImmigrationGeographyGenealogyPolitical scienceDemographic economicsEthnologySociologyHistoryEconomicsArchaeology

Abstract

fetched live from OpenAlex

Abstract The entangled nature of the histories of health and immigration in Argentina between 1870 and 1950 have often been overlooked. The centrality of immigrants in public health discussions, the place of health in border regulation, and the role of immigrants themselves in providing health care are examples of several ways that scholars of both health and immigration could think more about one another’s fields. Historical studies of health often look at a specific ailment (such as tuberculosis, trachoma, venereal disease, or mental illness), and immigrants play a small role in those stories, usually appearing as the objects of doctors and officials’ concerns. Yet the fact that foreigners were commonly discussed and disproportionately targeted could instead push scholars to reconceptualize these histories. Both hospitals and mutual aid societies run by immigrants made up an important part of the health care systems in many Argentine cities starting in the final third of the 19th century. Yet they are conspicuously absent in a field that looks overwhelmingly at the role of the state and the Catholic Church in the provision of health care. Hospitals and mutual aid societies’ focus on health care are also absent in Argentine immigration historiography, even though hospitals were the largest immigrant-run institutions in country in this entire period, and health was the main focus of mutual aid societies.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.333
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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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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