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Record W2025664900 · doi:10.2466/pms.106.2.387-394

Frances McGehee (1912–2004): The First Earwitness Researcher

2008· article· en· W2025664900 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerceptual and Motor Skills · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSketchIdentification (biology)ConvictionPsychologyHistoryLawComputer sciencePolitical science

Abstract

fetched live from OpenAlex

The conviction of Bruno Richard Hauptmann (State v. Hauptmann, 1935) for the kidnap and murder of baby Charles Lindbergh, Jr. in 1932, which attracted world-wide attention and still remains controversial today, was based in part on voice identification evidence. This trial was the stimulus for the development of the first scientific experiments on voice identification. However, the historical contributions of Frances McGehee (1937, 1944), who can legitimately be called the First Earwitness Researcher, have generally been overlooked. An outline of the voice identification evidence presented by the State in the Hauptmann trial is described. A description of McGehee's research methodology, major findings, and scientific criticisms are presented, and a brief sketch of McGehee's life (1912-2004) is offered.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.111
GPT teacher head0.251
Teacher spread0.139 · 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