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Record W2900630539 · doi:10.1093/jos/ffz022

Do Children Interpret ‘or’ Conjunctively?

2020· article· en· W2900630539 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

VenueJournal of Semantics · 2020
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsConcordia UniversityUniversity of Calgary
Fundersnot available
KeywordsUtteranceComputer scienceReplicateCompetence (human resources)LinguisticsPsychologyArtificial intelligenceSocial psychologyMathematicsPhilosophy

Abstract

fetched live from OpenAlex

Abstract Preschoolers often struggle to compute scalar implicatures involving disjunction (or), in which they are required to strengthen an utterance by negating stronger alternatives, e.g. to infer that, ‘The girl has an apple or an orange’ likely means she does not have both. However, recent reports surprisingly find that a substantial subset of children interpret disjunction as conjunction, concluding instead that the girl must have both fruits. According to these studies, children arrive at conjunctive readings not because they have a non-adult-like semantics, but because they lack access to the stronger scalar alternative and, and employ doubly exhaustified disjuncts when computing implicatures. Using stimuli modelled on previous studies, we test English-speaking preschoolers and replicate the finding that many children interpret or conjunctively. However, we speculate that conditions which replicate this finding may be pragmatically infelicitous, such that results do not offer a valid test of children’s semantic competence. We show that when disjunctive statements are uttered in contexts that render the speaker’s intended question more transparent, conjunctive readings disappear almost entirely.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.308
Teacher spread0.279 · 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