Visuospatial attention is guided by both the symbolic value and the spatial proximity of selected arrows.
Bibliographic record
Abstract
There is considerable evidence that overlearned symbols, especially arrows, can orient attention to peripheral locations. In 2003, Pratt and Hommel showed that when 1 arrow is selected from a set of arrows, based on an attentional control setting for a specific target color, the selected arrow determines the orientation of attention. Recently, Leblanc and Jolicoeur (2010) reexamined this finding, and concluded that spatial proximity of the arrow to the target, not the symbolic value of the arrow, determines the orienting of attention. Here, we manipulated both the symbolic value of the cue (direction arrows or directionless circles) and the proximity of the cue to the peripheral target location (near or far), and found that although proximity does play a role in the orienting of attention (larger cuing effects were found with far cues than near cues), the symbolic content of the cue also plays an important role (larger cuing effects were found with arrows than circles). Thus, both the symbolic value and the spatial proximity of cues affect the orienting of attention.
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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 | 0.000 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".