Left wings to the left: Posing and perceived political orientation
Bibliographic record
Abstract
Images of individuals posing with the left cheek toward the camera are rated as more emotionally expressive than images with the right cheek toward the camera, which is theorized to be due to right hemisphere specialization for emotion processing. Liberals are stereotyped as being more emotional than conservatives. In the present study, we presented images of people displaying either leftward or rightward posing biases in an online task, and asked participants to rate people's perceived political orientation. Participants rated individuals portrayed with a leftward posing bias as significantly more liberal than those presented with a rightward bias. These findings support the idea that posing direction is related to perceived emotionality of an individual, and that liberals are stereotyped as more emotional than conservatives. Our results differ from those of a previous study, which found conservative politicians are more often portrayed with a leftward posing bias, suggesting differences between posing output for political parties and perceived political orientation. Future research should investigate this effect in other countries, and the effect of posing bias on perceptions of politicians.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".