It Depends Who Is Watching You: 3-D Agent Cues Increase Fairness
Bibliographic record
Abstract
Laboratory and field studies have demonstrated that exposure to cues of intentional agents in the form of eyes can increase prosocial behavior. However, previous research mostly used 2-dimensional depictions as experimental stimuli. Thus far no study has examined the influence of the spatial properties of agency cues on this prosocial effect. To investigate the role of dimensionality of agency cues on fairness, 345 participants engaged in a decision-making task in a naturalistic setting. The experimental treatment included a 3-dimensional pseudo-realistic model of a human head and a 2-dimensional picture of the same object. The control stimuli consisted of a real plant and its 2-D image. Our results partly support the findings of previous studies that cues of intentional agents increase prosocial behavior. However, this effect was only found for the 3-D cues, suggesting that dimensionality is a critical variable in triggering these effects in a real-world settings. Our research sheds light on a hitherto unexplored aspect of the effects of environmental cues and their morphological properties on decision-making.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".