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Record W7011278650

Medical Cartography in Southern Ontario, 1880–1920: A Records Perspective

2020· article· en· W7011278650 on OpenAlexaboutno aff

Bibliographic record

VenueArchivaria (Association of Canadian Archivists) · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Historical recordInterpretation (philosophy)Object (grammar)
DOInot available

Abstract

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This article examines the context of the creation and use of medical cartographic records in late-19th- and early-20th-century Ontario and suggests that disease maps be recognized not just as records of medical practice or public health administration but additionally as records of data management practices and technologies of liberal government. Disease mapping occurred primarily in the context of municipal and provincial public health departments, which used wall-mounted cloth pin maps as data management tools. In contrast, printed disease maps were used in educational outreach work to encourage individual self-regulation and self-surveillance. Public health authorities sought to use disease maps as tools of governmentality to re-orient individuals and to encourage them to view themselves as members of a larger population that could be improved through changed individual conduct. By examining the origins and functions of disease maps in Ontario, this article contributes to our foundational knowledge of the history of records and record-making, particularly the longer history of data management practices and techniques. As a contribution to archival literature, it offers a deeper understanding of the public role of cartographic records in the recent past, specifically, of the role of such records in the development of liberal government in a settler colonial state. RÉSUMÉ Cet article explore le contexte de création et l’utilisation de documents cartographiques médicaux à la fin du XIXe et début du XXe siècle en Ontario et avance que les cartes des maladies pourraient être reconnues non seulement comme des documents liés à la pratique médicale ou à l’administration de la santé publique, mais également comme des documents sur la gestion des données et les technologies d’un gouvernement libéral. Les cartes des maladies étaient produites principalement dans les organismes de santé publique muni-cipaux ou provinciaux, lesquels utilisaient des cartes apposées à un mur et des punaises comme outil de gestion des données. À l’opposé, les cartes des maladies imprimées étaient utilisées comme outils de sensibilisation pour encourager l’autorégulation et l’autosurveillance des individus. Les autorités de santé publique ont cherché à utiliser les cartes comme instrument de gouvernementalité afin de réorienter les individus et les encourager à se percevoir eux-mêmes comme membre d’une population plus large pouvant être réformée grâce à des changements de comportement individuels. En explorant les origines et les fonctions des cartes des maladies en Ontario, cet article contribue à la connaissance fondamentale de l’histoire des documents et de la production documentaire, particulièrement la longue histoire des pratiques et techniques de gestion des données. En guise de contribution à la littérature archivistique, il offre une compréhension approfondie du rôle des documents cartographiques dans l’histoire récente, particulièrement du rôle de ce type de document dans le développement d’un gouvernement libéral comme état colonisateur et colonial.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.496

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.017
Science and technology studies0.0060.005
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.033
GPT teacher head0.226
Teacher spread0.194 · 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.

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

Citations1
Published2020
Admission routes1
Has abstractno

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