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Record W2088472527 · doi:10.1017/s030500090000461x

The acquisition of control crosslinguistically: structural and lexical factors in learning to licence PRO

2001· article· en· W2088472527 on OpenAlexaff
Helen Goodluck, Arhonto Terzi, Gema Chocano

Bibliographic record

VenueJournal of Child Language · 2001
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychologySentenceLinguisticsComplement (music)InfinitiveSubject (documents)Meaning (existential)Lexical itemInterpretation (philosophy)Control (management)VerbArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Rules for interpreting empty category (EC) subjects of complement clauses vary crosslinguistically across structural and lexical dimensions. In adult Greek, a distinction is made between the verbs meaning WANT and TRY, the former but not the latter permitting the EC subject of its subjunctive complement to refer outside the sentence. The EC is pro for WANT and PRO for TRY. In adult Spanish, both the verbs meaning WANT and TRY require the EC subject (pro) to refer outside when the complement is in the subjunctive, and require the EC subject (PRO) to refer to the main clause subject when the complement is in the infinitive. Twenty-three Greek-speaking four- to five-year-olds and 10 adults, 29 Spanish-speaking four- to five-year-olds, 18 six- to seven-year-olds and eight adults took part in act-out experiments. The results indicate an awareness of language-particular distinctions governing the interpretation of EC complement subjects. However, child speakers of both languages experience difficulty in giving sentence external reference, leading to error in the case of subjunctive sentences for Spanish-speaking children. We argue that the data overall is most compatible with children having access to the empty category PRO by age four, and that failure to give external reference of an EC when required can plausibly be treated as performance error. A picture verification task produced less clear results, but points to the need for data from younger children to establish whether there is an early stage in which lexical semantics dominates children's interpretation of ECs.

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 score0.105
Threshold uncertainty score0.161

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 head0.007
GPT teacher head0.312
Teacher spread0.305 · 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

Citations19
Published2001
Admission routes1
Has abstractyes

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