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Record W2059111779 · doi:10.1086/384944

The Visual Theology of Victorian Popularizers of Science: From Reverent Eye to Chemical Retina

2000· article· en· W2059111779 on OpenAlexaff
Bernard Lightman

Bibliographic record

VenueIsis · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Natural History
Canadian institutionsYork University
Fundersnot available
KeywordsWonderVisual cultureTeleological argumentCredibilityTrustworthinessArgument (complex analysis)Visual mediaNatural (archaeology)Embodied cognitionPhilosophyOrder (exchange)Natural theologyAestheticsSociologyVisual artsArtReligious studiesHistoryEpistemologyPsychologyBiology

Abstract

fetched live from OpenAlex

This essay examines the use of visual images during the latter half of the nineteenth century in the work of three important popularizers of science. J. G. Wood, Richard Proctor, and Agnes Clerke skillfully used illustrations and photographs to establish their credibility as trustworthy guides to scientific, moral, and religious truths. All three worked within the natural theology tradition, despite the powerful critique of William Paley's argument from design set forth in Charles Darwin's Origin of Species (1859). Wood, Proctor, and Clerke recognized that in order to reach a popular audience with their message of divine wonder in nature, they would have to take advantage of the developing mass visual culture embodied in the new pictorial magazines, spectacles, and entertaining toys based on scientific gadgets emblematic of the reorganization of vision. But in drawing on different facets of the emerging visual culture and in looking to the images produced by the new visual technologies to find the hand of God in nature, these popularizers subtly transformed the natural theology tradition.

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)0.003
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.986
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0140.042
Scholarly communication0.0110.006
Open science0.0010.005
Research integrity0.0030.006
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 head0.009
GPT teacher head0.241
Teacher spread0.232 · 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

Citations48
Published2000
Admission routes1
Has abstractyes

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