Assessing Reverence in Contexts
Bibliographic record
Abstract
Deeply rooted in Western and Eastern civilization, reverence is a cardinal virtue that embraces meaning and purpose in life. It is also a self-transcending positive emotion, associated with specific worldviews that may determine the context in which an individual senses it. To date, few psychological studies have addressed this concept. To address the gap, we drew two different study samples to validate a contextualized Sense of Reverence scale (SOR). Capitalizing on the cardiac data of older patients, Study I extended the validation of the twofold scale, reverence in religious and secular contexts (R- and S-reverence), by correlating it with measures of general religiousness and positive attitudes. Study II confirmed the structure and further validated the scale in healthy Canadian and U.S. students. Using structural equation modeling, Study II evaluated differential associations of R- and S- reverence. S-reverence was related to spiritual support from nontraditional sources, a belief in death as a natural end, and psychological functioning connected with growth, as indicated by openness, creativity, and personal growth. R-reverence was associated with spiritual support from traditional sources, a belief in a rewarding afterlife, and psychological functioning connected with adjustment, as indicated by agreeableness, conscientiousness, and personal adjustment. Both forms of reverence were positively related to self-transcendence.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".