Concurrent visual learning of adjacent and nonadjacent dependencies in adults and children.
Bibliographic record
Abstract
Concurrent learning of adjacent and nonadjacent dependencies has been shown in adults only. This study extended this line of research by examining dependency-specific learning for both adjacent and nonadjacent dependencies concurrently in both adults and children. Seventy adults aged 18 to 64 (40 women, 30 men; Experiment 1) and 64 children aged 10 to 11 years (40 girls, 24 boys; Experiment 2) were tested with a new serial reaction time (SRT) task in which they were trained for 5-8 min on materials comprising equally probable adjacent and nonadjacent dependencies. They were then asked to discriminate between trained and untrained dependencies in a familiarity task. Both adults and children showed implicit concurrent learning of both adjacent and nonadjacent dependencies. The two dependency types were learned to the same extent. However, adults showed a rapid, sustainable, and dependency-specific sensitivity throughout the SRT task while children only showed a dependency-specific sensitivity to violations of expectations after exposure. When the two groups were statistically compared, only adults showed a dependency-specific learning effect after exposure. These findings are in line with the age-related improvement model of dependency learning. (PsycInfo Database Record (c) 2021 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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".