Does a history of involuntary selection generate attentional biases?
Bibliographic record
Abstract
Voluntarily allocating attention to task-relevant features engenders attentional biases for frequently attended stimuli, even when they become irrelevant (ie., selection history). Little is known, however, to what extent effortful, voluntary attention is a necessary component in the formation of such selection biases. Do task-irrelevant, abrupt onsets, which reflexively draw attention to a particular location, engender attentional selection biases for involuntarily attended locations, biases that persist in the absence of explicit exogenous cues? Using a preregistered data collection and analysis plan (accepted, Psychonomic Bulletin & Review, final manuscript in preparation), we manipulated spatial attention during an orientation discrimination task: two Gabor patches (randomly and independently rotated clockwise or counterclockwise of vertical) were simultaneously presented (8° left/right of fixation); a postcue indicated which was the target. To generate different selection histories for left/right locations, we delivered precues more often to one location (2:1 ratio) during the first half of the study (most-cued side counterbalanced across observers, equal numbers valid and invalid trials at each location). In the second half, no precues were presented, and observers continued the orientation discrimination task. If exogenous attentional selection generates persistent biases, performance should be better on the previously most-cued side, relative to least-cued side. As expected, abrupt onsets reflexively modulated visual processing in the first half: task accuracy increased, and RTs decreased, when the precue appeared near the forthcoming target (valid trials), relative to the distractor (invalid trials). When precues were removed in the second half, however, we found no evidence that exogenous selection history modulated task performance: task accuracy and RTs at previously most/least cued sides were statistically indistinguishable; precue-free follow-up sessions (one day and one week later) also showed indistinguishable performance at left/right locations. Thus, unlike voluntarily directed attention, reflexively allocating attention may not be sufficient to engender historically-contingent selection biases.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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; 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".