How do selected arrows guide visuospatial attention? Dissociating symbolic value and spatial proximity.
Bibliographic record
Abstract
Previous research on the control of visuospatial attention showed that overlearned symbols like arrows have the potential to induce involuntary shifts of attention. Following work on the role of attentional control settings and of the content of working memory in the involuntary deployment of visuospatial attention, Pratt and Hommel (2003) found that this unintentional orienting by an arrow depended on its top-down selection, contingent on the attentional control settings, that is to say, the target selection cue. However, in this study, each arrow was closer to the location it indicated than to any other location, raising the issue of attention being drawn to the arrow location, facilitating processing at adjacent locations, rather than pushed to the symbolically cued location. In the present study, we dissociated symbolic cueing and spatial proximity cueing by the selected arrow. The results support the proximity cueing hypothesis.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".