Evidence for proactive interference in the focus of attention of working memory.
Bibliographic record
Abstract
Proactive interference (PI) occurs when an earlier item interferes with memory for a newer item. Whereas some researchers (e.g., Surprenant & Neath, 2009a) argue that PI can be observed in all memory systems, some multiple systems theorists (e.g., Cowan, 1999) propose that items in the focus of attention of working memory are immune to PI. Two experiments tested whether PI occurs when the to-be-remembered items are assumed, by multiple-systems theorists, to be held in the focus of attention. In each experiment, subjects saw four trials in a row with the same type of to-be-remembered items, followed by four trials in a row with a different type of material. On each trial, only 3 stimuli were shown, which is below the capacity limit of the focus of attention, and subjects were asked if a probe item was one of those 3 items seen. In both experiments, response time increased from Trial 1 to Trial 4, suggesting that items from the earlier trials interfered with memory on the later trials. In addition, release from PI was shown in that response times decreased with a change of materials. The results replicate those first reported by Hanley and Scheirer (1975), and pose a problem for theorists who argue that parts of short-term memory are immune to PI.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".