An attentional bias for LEGO® people using a change detection task: Are LEGO® people animate?
Bibliographic record
Abstract
Animate objects have been shown to elicit attentional priority in a change detection task. This benefit has been seen for both human and nonhuman animals compared with inanimate objects. One explanation for these results has been based on the importance animate objects have served over the course of our species' history. In the present set of experiments, we present stimuli, which could be perceived as animate, but with which our distant ancestors would have had no experience, and natural selection could have no direct pressure on their prioritization. In the first experiment, we compared LEGO® "people" with LEGO "nonpeople" in a change detection task. In a second experiment, we attempt to control the heterogeneity of the nonanimate objects by using LEGO blocks, matched in size and colour to LEGO people. In the third experiment, we occlude the faces of the LEGO people to control for facial pattern recognition. In the final 2 experiments, we attempt to obscure high-level categorical information processing of the stimuli by inverting and blurring the scenes. (PsycINFO Database Record
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".