Strategic and lexical retrieval processes in free verb fluency: The influence of age and education
Bibliographic record
Abstract
This study investigated age- and education-related differences in performance on a free verb fluency task in healthy adults. A sample of 170 participants was divided into two age groups (50-60 and 75+ years) and asked to produce as many verbs as possible within 60 seconds. Responses were analyzed for total production, temporal distribution, retrieval strategies (semantic, phonological, and alphabetic clustering and switching), and lexical characteristics (frequency and syllable length). Robust regression models revealed that older adults produced fewer verbs, particularly during the initial 30 seconds, and exhibited fewer phonological and alphabetic switches, indicating reduced cognitive flexibility. In contrast, semantic clustering patterns and lexical frequency measures did not differ significantly with age. Education was positively associated with total output, switching behavior, and lexical conventionality, suggesting that cognitive reserve contributes to fluency performance. These findings highlight both quantitative and qualitative age-related changes in lexical retrieval and support the moderating role of education on executive-linguistic functioning in late adulthood.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".