An age-related deficit in resolving interference: Evidence from speech perception.
Bibliographic record
Abstract
The presence of noise and interfering information can pose major difficulties during speech perception, particularly for older adults. Analogously, interference from similar representations during retrieval is a major cause of age-related memory failures. To demonstrate a suppression mechanism that underlies such speech and memory difficulties, we tested the hypothesis that interference between targets and competitors is resolved by suppressing competitors, thereby rendering them less intelligible in noise. In a series of experiments using a paradigm adapted from Healey, Hasher, and Campbell (2013), we presented a list of words that included target/competitor pairs of orthographically similar words (e.g., ALLERGY and ANALOGY). After a delay, participants solved fragments (e.g., A_L__GY), some of which resembled both members of the target/competitor pair, but could only be completed by the target. We then assessed the consequence of having successfully resolved this interference by asking participants to identify words in noise, some of which included the rejected competitor words from the previous phase. Consistent with a suppression account of interference resolution, younger adults reliably demonstrated reduced identification accuracy for competitors, indicating that they had effectively rejected, and therefore suppressed, competitors. In contrast, older adults showed a relative increase in accuracy for competitors relative to young adults. Such results suggest that older adults' reduced ability to suppress these representations resulted in sustained access to lexical traces, subsequently increasing perceptual identification of such items. We discuss these findings within the framework of inhibitory control theory in cognitive aging and its implications for age-related changes in speech perception. (PsycINFO Database Record
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".