Did Buddha turn the other cheek too? A comparison of posing biases between Jesus and Buddha
Bibliographic record
Abstract
People tend to exhibit a leftward bias in posing. Various studies suggest that posing to the left portrays a stronger emotion, whereas posing to the right portrays a more neutral emotion. Religions such as Christianity emphasize the role of strong emotions in religious experience, whereas religions such as Buddhism emphasize the calming of emotions as being important. In the present study, we investigated if the emphasis on emotionality of a religion influences the depiction of their religious figures. Specifically, we coded 484 paintings of Jesus and Buddha from online art databases for whether the deity exhibited a left bias, right bias, or central face presentation. The posing biases were analysed to discover whether paintings of Jesus would more frequently depict a leftward bias than paintings of Buddha. Jesus is more commonly depicted with a leftward bias than Buddha, and Buddha is more commonly depicted with a central face presentation than Jesus. These findings support the idea that the amount of emotionality that is to be conveyed in artwork influences the whether the subject is posed with a leftward bias.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".