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Record W2095444746 · doi:10.1111/1467-9507.00129

The Confused Robot: Two‐Year‐Olds’ Responses to Breakdowns in Conversation

2000· article· en· W2095444746 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

VenueSocial Development · 2000
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsDalhousie University
Fundersnot available
KeywordsUtteranceConversationGricePsychologySession (web analytics)Developmental psychologySocial psychologyLinguisticsPragmaticsCommunicationArtificial intelligenceComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Preschool children at two ages conversed with a toy robot during a play session. During the conversations the robot inserted either general (e.g., What?) or specific (e.g., Piggy is in what?) contingent queries in response to selected utterances. The children’s replies to these breakdowns in conversation indicated they were sensitive to the pragmatic requirements of these different types of query. By 33 months of age, the children replied to general queries with complete repetitions of their prior misunderstood utterance, and replied to specific queries with only the required constituentinformation. At 27 months of age, the children’s predominant strategy was to reply to both forms of query with complete repetitions, although the data suggest some degree of sensitivity to these different forms is also present in this younger group. These results are interpreted in terms of children’s sensitivity to Grice’s (1975) quantity rule and the potential changes in social cognition underlying children’s compliance with this rule.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.998

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.021
GPT teacher head0.310
Teacher spread0.289 · 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