The contribution of discursive and cognitive factors in referential choices made by elderly people during a narrative task
Bibliographic record
Abstract
The present study focuses on referential choices made by healthy aged adults during narrative discourse, and their relationship with cognitive and socio-cognitive abilities. Previously, some studies have shown that, compared to young adults, older adults produce more pronouns when referring to various entities during discourse, regardless of the accessibility level of the referent for the addressee. This referential behavior has been interpreted in relation to the decrease of cognitive abilities, such as working memory abilities. There is, as of yet, little empirical evidence highlighting which cognitive competences preferentially support referential choices during discourse production. Here, we focus on three categories of referential markers (indefinite, definite markers and pronouns) produced by 78 participants from 60 to 91 years old. We used a storytelling task enabling us to examine the referential choices made at three discourse stages (introduction, maintaining or shift of the referent in focus) and in increasing levels of referential complexity (one vs two characters, and different vs same gender). In addition to specifically assessing how increasing age influences referential choices, we also examine the contribution of various cognitive and socio-cognitive skills that are presumed to play a specific role in referential choices. We found that both age and specific cognitive abilities (planification, inhibition, and verbal episodic memory) had an effect on referential choices, but that these effects depended on when (at which discourse stage) the referential markers were produced. Overall, our study highlights the complex interplay between discursive and cognitive factors in referential choices made by healthy older speakers.
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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 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".