Both cue directionality and mental perspective contribute to social attention
Bibliographic record
Abstract
Research showing that visual perspective of others spontaneously interferes with our own has led to a stimulating debate about whether social attention effects are driven by the directionality of agent’s social cues, the perceived content of their minds, or both. Here, we use a novel task to dissociate the contributions of these two variables. Participants viewed an image of an avatar (N=51) or an arrow (N=57) at fixation. From their own perspective, participants located a peripheral target (number 8) that was presented with a distractor at an opposing location. The cue pointed at the target or at the distractor equally often. Further, the cue’s and the participants’ mental content either matched or mismatched depending on whether the cue indicated the target or the distractor. Replicating past work showing the typical effects of cue directionality, participants were overall faster to respond to targets when central cues pointed at the target. However, their responses were additionally facilitated when the perspective content matched relative to when it mismatched irrespective of cue type. As such, these results suggest that both cue directionality and mental content contribute to social attention and raise additional questions about the specific contributions of agency with social and non-social cues.
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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 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".