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Record W1940529535 · doi:10.1017/s0025727300068721

Edwin Chadwick and the poverty of statistics

2002· article· en· W1940529535 on OpenAlexaff
James Hanley

Bibliographic record

VenueMedical History · 2002
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsComputer sciencePovertyAction (physics)Data scienceLibrary scienceWorld Wide WebPolitical scienceLaw

Abstract

fetched live from OpenAlex

In his 1842 Report on the sanitary condition of the labouring population of Great Britain, Edwin Chadwick demonstrated the existence of a mass of preventable illness and premature death in the community caused, he argued, by insanitary physical circumstances.'Although much of the evidence for the existence of this preventable mortality was anecdotal, Chadwick included a chapter of differential class-based death data which dramatically illustrated the extent to which insanitary physical circumstances shortened life.Chadwick's chosen statistical measure-the average age at which a given class of people died showed that what he called the "average period of life" or "chance of life" was as low as 17 for labourers in Manchester but as high as 52 for gentry in Rutlandshire.2Although his statistics were widely quoted at the time,3 professional statisticians dismissed the data and historians ever since have paid little serious attention to it.4In this paper I will argue that Chadwick's class-based average-age-at-death data were a central feature of the Sanitary report and that we cannot fully appreciate the argument or even the organization of the report without them.

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)0.021
metaresearch head score (Gemma)0.111
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 score0.021
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.111
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.007
Science and technology studies0.0050.014
Scholarly communication0.0100.017
Open science0.0010.005
Research integrity0.0060.013
Insufficient payload (model declined to judge)0.0090.003

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 head0.079
GPT teacher head0.363
Teacher spread0.283 · 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

Citations11
Published2002
Admission routes1
Has abstractyes

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