Internally Generated Simulations of Success and Failure Orient Visual Attention
Bibliographic record
Abstract
Recent research has found that spatial mechanisms of action-perception processes contribute to concept formation through simulation, such that conceptual processes can affect perceptual processes (Barsalou, 2003). While the effects of simulation on perception have been found with concrete (Estes et al., 2008) and metaphorical (Gozli et al., in press) conceptual words, the present research focuses on the contribution of spatial mechanisms to internal representation of other people. To accomplish this, participants were given three short stories containing two protagonists, one of whom was doing very well and another that was struggling. In the first experiment, each story was followed by a visual discrimination task in which one of four cue names appeared at fixation (the positive protagonist, the negative protagonist, and two new names) followed by a target (X or O) that appeared either above or below the name. Participants identified the target letter as quickly as possible with a keypress when the cue name was one that occurred in the previous story. Consistent with a simulation account, processing names interfered with target processing at the metaphorically compatible location (e.g., target appeared above following the positive name at fixation). In the second experiment, after each of the stories, one the four names appeared either above or below the fixation point and participants were asked to determine if the name had been used in the previous story as quickly as possible. As predicted by simulation, positive names were responded to more quickly when presented in upper space with negative names faster in lower space. The findings of these experiments show that internally-generated simulations of other people who are associated with success or failure recruits mechanisms of visual-spatial attention. This study provides striking further evidence for the strong connections between conceptual processes and the mechanisms of action-perception. Meeting abstract presented at VSS 2013
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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 | 0.014 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".