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Record W2012896671 · doi:10.1017/s0952675707001273

Place assimilation and phonetic grounding: a cross-linguistic perceptual study

2007· article· en· W2012896671 on OpenAlexaffabout
Alexei Kochetov, Connie K. So

Bibliographic record

VenuePhonology · 2007
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSalience (neuroscience)MarkednessPerceptionLinguisticsPsychologyPlace of articulationMandarin ChineseAssimilation (phonology)Articulation (sociology)Cognitive psychologyConsonantVowel

Abstract

fetched live from OpenAlex

This paper investigates predictions made by the ‘phonetic knowledge hypothesis’ (Jun 1995, 2004, Hayes & Steriade 2004) about the relation between perceptibility of stops and common patterns of major place assimilation. In two perceptual experiments, stimuli with Russian released and unreleased voiceless stops in clusters were presented for identification of 56 listeners, native speakers of Russian, Canadian English, Korean and Taiwanese Mandarin. Percentages of correct responses and reaction time data were used to determine scales of perceptual salience. Results reveal considerable perceptual differences between places of articulation, consistent across four language groups. Perceptual salience of place of articulation was strongly affected by presence or absence of stop releases. While the salience scale for released stops closely corresponded to cross-linguistic patterns of assimilation, the scale for unreleased stops did not. The results provide partial support for the hypothesis, while suggesting a less direct relation between scales of phonetic difficulty and phonological markedness.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.057
GPT teacher head0.431
Teacher spread0.373 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations17
Published2007
Admission routes2
Has abstractyes

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