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Record W1989898745 · doi:10.1002/acp.702

Commonsense beliefs and the identification of familiar voices

2001· article· en· W1989898745 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

VenueApplied Cognitive Psychology · 2001
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsUniversity of GuelphYork UniversityUniversity of Toronto
Fundersnot available
KeywordsPsychologyTone (literature)AudiologyIdentification (biology)Social psychologyCognitive psychologyLinguistics

Abstract

fetched live from OpenAlex

Abstract Two experiments are reported in which participants attempted to reject the tape‐recorded voice of a stranger and identify by name the voices of three personal associates who differed in their level of familiarity. In Experiment 1 listeners were asked to identify speakers as soon as possible, but were not allowed to change their responses once made. In Experiment 2 listeners were permitted to change their responses over successive presentations of increasing durations of voice segments. Also, in Experiment 2 half of the listeners attempted to identify speakers who spoke in normal‐tone voices, and the remainder attempted to identify the same speakers who spoke in whispers. Separate groups of undergraduate students attempted to predict the performance of the listeners in both experiments. Accuracy of performance depended on the familiarity of speakers and tone of speech. A between‐subjects analysis of rated confidence was diagnostic of accuracy for high familiar and low familiar speakers (Experiment 1), and for moderate familiar and unfamiliar normal‐tone speakers (Experiment 2). A modified between‐subjects analysis assessed across the four levels of familiarity yielded reliable accuracy‐confidence correlations in both experiments. Beliefs about the accuracy of voice identification were inflated relative to the significantly lower actual performance for most of the normal‐tone and whispered‐speech conditions. Forensic significance and generalizations are addressed. Copyright © 2001 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.024
GPT teacher head0.342
Teacher spread0.318 · 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