The development of referential choice in English and Japanese: a discourse-pragmatic perspective
Bibliographic record
Abstract
The present research investigated whether children's referential choices for verb arguments are motivated by pragmatic features of discourse referents across different developmental stages, not only for children learning null argument languages but also for those learning overt argument languages. In Study 1, the form (null, pronominal, or lexical) and referential status (given or new) of verb arguments were systematically analysed in six English-speaking and six Japanese-speaking children and their mothers when the children were at 1;9 and 3;0. In Study 2, non-linguistic pragmatic correlates (pointing, reaching, moving, making a head motion, or purposeful gaze direction toward a referent) were analysed in addition to the form and referential status of arguments at each of four linguistic periods between MLU 1 00 and 4 00 in two English-speaking and two Japanese-speaking children and their mothers. The results revealed that, when both linguistic and non-linguistic referential behaviours were considered, the English-speaking children showed patterns consistent with language-universal as well as language-specific discourse-pragmatic principles by 2;0 (between MLU 2 00 and 2 99), whereas the Japanese-speaking children did not show these patterns even as late as 3;0 (MLU 4 00 and above). Results also indicated that the children who were exposed to more consistent discourse-pragmatic referential patterns from their input tended to show these patterns earlier than those exposed to inconsistent patterns. Together these findings suggest that both the referential status of discourse referents as well as parental input predict children's referential choices across typologically different languages.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".