Variations in adult use of referring expressions during storytelling in different interactional settings
Bibliographic record
Abstract
Abstract During the language acquisition process children experience language in different interactional settings. In terms of child-directed speech, we argue that children are exposed to different models that vary according to different factors. This chapter aims at grasping some aspects of these models, with a focus on referring expressions. Data consists of narratives in three interactional settings: mother-child interactions (Mother-to-Child context), kindergarten sessions (School context), and adults telling a story to an experimenter (Adult-to-Experimenter context). Children were aged from 3 to 7. We compared the participants’ uses of referring expressions in these three contexts and, in the Mother-to-Child context, mothers interacting with a language impaired child or not. Results show that adults’ uses of nouns and clitic pronouns vary according to the interactional setting, and that the uses of mothers and teachers when interacting with children at home or in school do not correspond to those of adults in an experimental setting.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".