Effects of bilingualism, aging, and semantic relatedness on memory under divided attention.
Bibliographic record
Abstract
We examined how encoding and retrieval processes were affected by manipulations of attention, and whether the degree of semantic relatedness between words in the memory and distracting task modulated these effects. We also considered age and bilingual status as mediating factors. Monolingual and bilingual younger and older adults studied a list of words from a single semantic category presented auditorily, and later free recalled them aloud. During either study or retrieval, participants concurrently performed a distracting task requiring size decisions to words from either the same or a different semantic category as the words in the memory task. The greatest disruptions of memory from divided attention (DA) were for encoding rather than retrieval. The effect of semantic relatedness was significant only for DA at encoding. Older age and bilingualism were associated with lower recall scores in all conditions, but these factors did not influence the magnitude of memory interference. The results suggest that encoding is more sensitive to semantic similarity in a distracting task than is retrieval. The role of attention at encoding and retrieval is discussed.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".