Age-related differences in referential production: A multiple-measures study.
Bibliographic record
Abstract
Contemporary research on aging has provided mixed evidence for whether older adults are less effective than younger adults at designing and delivering spoken utterances. However, most of these studies have focused on only specific aspects of this process. In addition, they tend to vary significantly in terms of the degree of complexity in their chosen stimuli or task. The present study compares younger and older adults' performance using a referential production paradigm involving simple everyday objects. We varied referential context such that a target object was either unique in its category (e.g., one shirt), or was accompanied by a same-category object (e.g., two shirts). We evaluated whether speakers' descriptions provided listeners with sufficient information for identification, and whether speakers spontaneously adapt their speech for different addressee types (younger adult, older adult, automated dialogue system). A variety of measures were included to provide a comprehensive perspective on adults' performance. Interestingly, the results revealed few or no age differences in measures related to production performance (speech onset latency, speech rate, and fluency). In contrast, consistent differences were observed for measures related to descriptive content, both in terms of informativity and variability in lexical selection: Older adults not only provided more information than necessary for referential success (e.g., superfluous modifiers), but also exhibited greater variability in their selection of modifiers. The results show that, although certain aspects of the production process are well-preserved across the adult lifespan, meaningful age-related differences can still be found in simple referential tasks with everyday objects. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".