Lexical access in younger and older adults: The case of the mass/count distinction.
Bibliographic record
Abstract
Although lexicosemantic deficits are not typically seen in older adults, some studies indicate that age-related changes in semantic processing may occur. We had groups of older and younger adults perform speeded lexical decision on mass (e.g., honey), count (e.g., car), and dual nouns, which may be either mass or count (e.g., lamb). Singular dual nouns engendered significantly faster response times in older adults than mass and count nouns, whereas younger adults manifested similar response times to count and dual nouns. These results point toward a three-way distinction in the lexicon between mass, count, and dual nouns. Older adults appear to treat a larger set of nouns as dual than do younger adults. This may be due to awareness of the mass/count ambiguity present in a greater number of lexical items, as a result of their greater linguistic experience. Alternatively, in order to conserve processing resources, older adults may not activate mass/count information when recognizing a dual noun unless a mass or count reading is forced by context.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".