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Record W4398226626 · doi:10.1353/vpr.2023.a927878

Two Hundred Years of the Lancet : From Quack to Anti-Vax, or How the Lancet Took a Stand

2023· article· en· W4398226626 on OpenAlexvenueno aff
Marysa Demoor

Bibliographic record

VenueVictorian periodicals review · 2023
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryMedicine

Abstract

fetched live from OpenAlex

Abstract: This essay traces the rise of the Lancet from its humble nineteenth-century beginnings to its current status as one of the most prestigious medical journals. By examining the Lancet 's early years and the hopes of founding editor Thomas Wakely and his successors, I aim to reveal what distinguished this journal from others circulating at the time and guaranteed its longevity. Despite fierce competition with several early medical journals, including the British Medical Journal and a quack publication that called itself the Anti - Lancet , the Lancet continued to publish research-based information to instruct the medical community far and wide. Indeed, while fake news and anti-vaxers might seem like twenty-first-century problems, this paper shows how the Lancet has been addressing misinformation for two hundred years.

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)0.015
metaresearch head score (Gemma)0.039
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.012
Scholarly communication0.0130.012
Open science0.0010.003
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0060.002

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 head0.229
GPT teacher head0.456
Teacher spread0.227 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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