Attention switching between global and local elements: Distractor category and the level repetition effect
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract When selecting information at global and local levels of hierarchical stimuli, there is a robust effect of level repetition in which performance is more efficient when a target is presented at the same level as the previous target. Moreover, the effect is symmetrical; it affects global and local processing equally. Evidence exists to suggest the effect may be automatic; however, we show here that the level repetition effect requires some amount of competition from the ignored level, and that the nature of the irrelevant information can determine whether the level-repetition effect is symmetrical (global and local responses are affected equally) or asymmetrical (global responses are more greatly affected than local responses). In Experiment 1, the level-repetition effect was eliminated when information at the distracting level was invariant across trials; effects of hemisphere bias and level repetition were observed only when suppression or filtering of distractor information was required. Experiment 2 demonstrated that simple featural variance is sufficient to produce the level repetition effect and that the symmetry of the level-repetition effect is sensitive to Garner-type interference that affects global processing to a greater extent than local processing. In Experiment 3, we showed that the absence of a level-repetition effect in the invariant distractor condition persists when the position of relevant stimuli is random within a block, a manipulation which should greatly reduce the contribution of controlled attention. We conclude that simple featural variance at the ignored level is critical to produce the advantage of level repetition, and that the size of the effect can be asymmetrical.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it