The Influence of Deep Space and the Stars on Emotions
Bibliographic record
Abstract
Detailed photographs of deep space from the James Webb telescope are public, yet little is known about how such imagery might affect people. Using both face-to-face and online study designs, compared to exposure to photographs of urban environments, exposure to photographs of deep space and stars increased experiences of awe overall and also its 6 subfactors, and in particular vastness (e.g., "I felt in the presence of greatness") and accommodation ("I found it was hard to comprehend the experience in full"). Effects were generally larger for photographs of deep space than those of the stars. Mixed results were found on positive affect in general, with it sometimes increasing after exposure to deep space and the stars. No effects emerged on negative affect. Deep space and stars also led to higher ratings of pleasantness of the images, perceived restoration, and willingness to hang such photos in their room compared to urban photographs. Moderators were also assessed (i.e., feeling connected to the night sky and fear of the dark). Overall, results suggest that photographs of deep space from the James Webb telescope have similar, though not identical, effects as photographs of stars, both of which are generally more positive than urban photographs.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".