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Record W3176042825 · doi:10.1017/s0305000921000349

The influence of prominence cues in 7- to 10-year-olds’ pronoun resolution: Disentangling order of mention, grammatical role, and semantic role

2021· article· en· W3176042825 on OpenAlexafffund
Liam P. Blything, Maialen Iraola Azpiroz, Shanley Allen, Regina Hert, Juhani Järvikivi

Bibliographic record

VenueJournal of Child Language · 2021
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Alberta
FundersEconomic and Social Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyLinguisticsDemonstrativeObject (grammar)Dative caseVariation (astronomy)Subject pronounPersonal pronounSubject (documents)PronounReflexive pronounObject pronounGazeComprehensionComputer science

Abstract

fetched live from OpenAlex

Abstract In two visual world experiments we disentangled the influence of order of mention (first vs. second mention), grammatical role (subject vs object), and semantic role (proto-agent vs proto-patient) on 7- to 10-year-olds’ real-time interpretation of German pronouns. Children listened to SVO or OVS sentences containing active accusative verbs ( küssen “to kiss”) in Experiment 1 (N = 72), or dative object-experiencer verbs ( gefallen “to like”) in Experiment 2 (N = 64). This was followed by the personal pronoun er or the demonstrative pronoun der . Interpretive preferences for er were most robust when high prominence cues (first mention, subject, proto-agent) were aligned onto the same entity; and the same applied to der for low prominence cues (second mention, object, proto-patient). These preferences were reduced in conditions where cues were misaligned, and there was evidence that each cue independently influenced performance. Crucially, individual variation in age predicted adult-like weighting preferences for semantic cues (Schumacher, Roberts & Järvikivi, 2017).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.244

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)0.0000.000

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 head0.004
GPT teacher head0.260
Teacher spread0.256 · 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.

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

Citations5
Published2021
Admission routes2
Has abstractyes

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