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Record W2088507329 · doi:10.1086/384721

Baring the Sole: The Rise and Fall of the Shoe-Fitting Fluoroscope

2000· article· en· W2088507329 on OpenAlexaffabout
Jacalyn Duffin, Charles Hayter

Bibliographic record

VenueIsis · 2000
Typearticle
Languageen
FieldMedicine
TopicHistory of Medical Practice
Canadian institutionsQueen's University
Fundersnot available
KeywordsPopularityEnthusiasmNewspaperTRACE (psycholinguistics)Government (linguistics)HistoryAdvertisingPolitical sciencePsychologyBusinessLawSocial psychology

Abstract

fetched live from OpenAlex

One of the most conspicuous nonmedical uses of the x-ray was the shoe-fitting fluoroscope. It allowed visualization of the bones and soft tissues of the foot inside a shoe, purportedly increasing the accuracy of shoe fitting and thereby enhancing sales. From the mid 1920s to the 1950s, shoe-fitting fluoroscopes were a prominent feature of shoe stores in North America and Europe. Despite the widespread distribution and popularity of these machines, few have studied their history. In this essay we trace the origin, technology, applications, and significance of the shoe-fitting fluoroscope in Britain, Canada, and the United States. Our sources include medical and industrial literature, oral and written testimony of shoe retailers, newspapers, magazines, and government reports on the uses and dangers of these machines. The public response to shoe-fitting fluoroscopes changed from initial enthusiasm and trust to suspicion and fear, in conjunction with shifting cultural attitudes to radiation technologies.

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)0.001
metaresearch head score (Gemma)0.003
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.011
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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 designNot applicable
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

Citations30
Published2000
Admission routes2
Has abstractyes

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