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Record W2909665089 · doi:10.1017/s0305000918000557

Learning speech-internal cues to pronoun interpretation from co-speech gesture: a training study

2019· article· en· W2909665089 on OpenAlexaff
Whitney Goodrich Smith, Alexis K. Black, Carla L. Hudson Kam

Bibliographic record

VenueJournal of Child Language · 2019
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of British Columbia
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsReferentPronounGesturePsychologyInterpretation (philosophy)AmbiguityLinguisticsSentenceSubject pronounNarrativeCognitive psychology

Abstract

fetched live from OpenAlex

This study explores whether children can learn a structural processing bias relevant to pronoun interpretation from brief training. Over three days, 42 five-year-olds were exposed to narratives exhibiting a first-mentioned tendency. Two characters were introduced, and the first-mentioned was later described engaging in a solo activity. In our primary condition of interest, the Gesture Training condition, the solo-activity sentence contained an ambiguous pronoun, but co-speech gesture clarified the referent. There were two comparison conditions. In the Gender Training condition the characters were different genders, thereby avoiding ambiguity. In the Name Training condition, the first-mentioned name was simply repeated. Ambiguous pronoun interpretation was tested pre- and post-training. Children in the Gesture condition were significantly more likely to interpret ambiguous pronouns as the first-mentioned character after training. Results from the comparison conditions were ambiguous: there was a small but non-significant effect of training, but also no significant differences between conditions.

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 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 score0.628
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.337
Teacher spread0.322 · 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 teacher head, not a consensus.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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