Keeping track of characters: Factors affecting referential adequacy in children’s narratives
Bibliographic record
Abstract
This study considered the adequacy of references used by children to introduce, maintain, and reintroduce characters in complex narratives involving multiple characters. Sixty-three English-speaking Canadian children from kindergarten to second grade ( M age 7.0 years) told two multi-episode stories from wordless picture books. Analyses considered differences in referential adequacy both within-children and between grades. There was an unexpectedly large difference in adequacy levels across stories, mostly because of an overuse of pronouns in one story. Maintenance was the easiest referential function, whereas reintroduction proved more difficult than introduction only for the story with consistently lower adequacy levels. Participants across grades were affected by referential function and by story in analogous ways. The kindergartners did nonetheless obtain lower adequacy levels than the two higher grades due to a higher use of pronouns and because they were less able to clearly refer to characters even when they were using the same linguistic forms. Participants in the three grades successfully used a diversity of linguistic forms for their character references across referential functions. Together, these findings have important implications for referential cohesion in young school-aged children. First, they invite caution when drawing conclusions regarding developmental changes based on a single story. Second, they suggest that reintroduction may be particularly sensitive to story features that make referencing more demanding. Finally, they underscore the importance of considering reference within the broader textual context in order to produce a detailed account of referential abilities.
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 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 | 0.003 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 | 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".