Is position "special" in visual attention? Evidence that top-down processes guide visual selection.
Bibliographic record
Abstract
The role of spatial position in selective visual processing has been the source of recent debate. Experiments by Tsal and Lavie (1988) and van der Heijden et al. (1996) have been designed to establish the status of position in visual selection. Tsal and Lavie found that observers tend to select letters from a briefly presented array according to position. Using the same paradigm, van der Heijden et al. found that observers tend to select according to colour, except under conditions of low contrast and unrestricted eye movements. The present study attempted to reconcile these findings by exploring the influence of top-down processes (task instructions) while explicitly controlling for eye movements. Experiment 1 demonstrated there was no inherent selection bias for stimuli similar to those used by van der Heijden et al., suggesting that the tendency to select according to colour found by van der Heijden et al. was due to task demands. Experiment 2 further established the role of top-down factors by replicating the results of van der Heijden et al. with our stimuli. Experiment 3 demonstrated that selection can be switched from colour to position by changing the demands of the task. These results suggest that selection may be accounted for by task demands (e.g., instructions) with no priority access for position information.
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.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".