A Large-Scale Semantic Analysis of Verbal Fluency Across the Aging Spectrum: Data From the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
OBJECTIVES: The present study aimed to characterize changes in verbal fluency performance across the lifespan using data from the Canadian Longitudinal Study on Aging (CLSA). METHODS: We examined verbal fluency performance in a large sample of adults aged 45-85 (n = 12,686). Data are from the Tracking cohort of the CLSA. Participants completed a computer-assisted telephone interview that included an animal fluency task, in which they were asked to name as many animals as they could in 1 min. We employed a computational modeling approach to examine the factors driving performance on this task. RESULTS: We found that the sequence of items produced was best predicted by their semantic neighborhood, and that pairwise similarity accounted for most of the variance in participant analyses. Moreover, the total number of items produced declined slightly with age, and older participants produced items of higher frequency and denser semantic neighborhood than younger adults. DISCUSSION: These findings indicate subtle changes in the way people perform this task as they age. The use of computational models allowed for a large increase in the amount of variance accounted for in this data set over standard assessment types, providing important theoretical insights into the aging process.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".