Taking the Extra Listening Mile: Processing Spoken Semantic Context Is More Effortful for Older Than Young Adults
Bibliographic record
Abstract
OBJECTIVES: Older adults use semantic context to generate predictions in speech processing, compensating for aging-related sensory and cognitive changes. This study aimed to gauge aging-related changes in effort exertion related to context use. DESIGN: The study revisited data from Harel-Arbeli et al. (2023) that used a "visual-world" eye-tracking paradigm. Data on efficiency of context use (response latency and the probability to gaze at the target before hearing it) and effort exertion (pupil dilation) were extracted from a subset of 14 young adults (21 to 27 years old) and 13 older adults (65 to 79 years old). RESULTS: Both age groups showed a similar pattern of context benefits for response latency and target word predictions, however only the older adults group showed overall increased pupil dilation when listening to context sentences. CONCLUSIONS: Older adults' efficient use of spoken semantic context appears to come at a cost of increased effort exertion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".