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Record W2313229582 · doi:10.1177/0073275315580953

Anthropometric portraiture and Victorian anthropology: Situating Francis Galton’s photographic work in the late 1870s

2015· article· en· W2313229582 on OpenAlexaff
Efram Sera‐Shriar

Bibliographic record

VenueHistory of Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsYork University
Fundersnot available
KeywordsGalton's problemCredibilityPhotographySociologyDiversity (politics)Period (music)AnthropologyHistoryArt historyVisual artsArtEpistemologyAestheticsPhilosophyComputer science

Abstract

fetched live from OpenAlex

This paper examines the complex observational techniques of British anthropologists during the nineteenth century. In particular, using Galton’s initial work with anthropometric and composite photography in the late 1870s as a case study, it argues that nineteenth-century anthropological armchair studies were extremely sophisticated and that researchers were highly attuned to the problems associated with their methodologies. These nineteenth-century practitioners were not simply anthologising the materials of others; rather they were developing specialised methods for producing their own evidence and drawing conclusions. Moreover, Galton’s use of photographic processes is instructive because it highlights one of the ways in which researchers interested in human diversity attempted to add further scientific credibility to their arguments by utilising the most cutting-edge technologies available during the period.

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)0.005
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 score0.987
Threshold uncertainty score0.575

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0130.033
Scholarly communication0.0050.004
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.321
Teacher spread0.274 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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