MétaCan
Menu
Back to cohort
Record W2626226107 · doi:10.1017/mdh.2017.36

Medical Experts and Agnotology in the Fumes Controversy of the Huelva Copper Mines (1888–1890)

2017· article· en· W2626226107 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMedical History · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsnot available
FundersRio TintoMinisterio de Ciencia e InnovaciónUniversity of Exeter
KeywordsIgnoranceLawEnvironmental protectionEnvironmental planningPolitical scienceEnvironmental science

Abstract

fetched live from OpenAlex

Huelva's copper mines (Spain) have been active for centuries but in the second half of the nineteenth century extractive activities in Riotinto, Tharsis, and other mines in the region were intensified in order to reach world leadership. The method used in these mines for copper extraction from low grade ores generated continuous emissions of fumes that were extremely controversial. The inhabitants had complained about the fumes for decades but as activity intensified so did complaints. The killing of anti-fumes demonstrators in 1888 led to the passing of a Royal Decree banning the open-air roasting of ore and to the drafting of numerous reports on the hazards of the fumes. Major state and provincial medical institutions, as well as renowned hygienists and engineers, took part in the assessment, contributing to a scientific controversy especially rich in content. In my paper I will analyse the production and circulation of knowledge and ignorance about the impact of fumes on public health, as well as the role of medical experts and expertise in the controversy. The analysis will focus on the reports drafted between the 1888 ban and its 1890 repeal, and will show the changing nature of the expert assessment and the numerous paths followed by experts in producing ignorance. The paper will conclude by considering other stakeholders, who may shed some light on the reasons behind the performance of the medical experts.

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.

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)0.008
metaresearch head score (Gemma)0.054
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.054
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.486
GPT teacher head0.537
Teacher spread0.051 · 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