Bibliographic record
Abstract
Experiencing awe (an emotionally moving shift in frame of reference or expansion of schemata) has been shown to increase generosity, spirituality, and prosociality, and reduce tribalism. The present research used an experimental design to investigate the effects that awe experiences would have on individuals’ endorsement of materialistic values and beliefs. Awe and materialism are theoretically incompatible, as materialism typically emphasizes the individual’s personal acquisitive goals at the expense of non-material goals like fostering interpersonal relationships or seeking self-knowledge and spiritual fulfillment. Additionally, previous research has demonstrated a distinction between types of awe; self-diminishing awe, or that which causes the individual to consider a frame of reference far larger than themselves and their own goals, is of particular relevance to the present study. Considering previous research and this theoretical incompatibility, it was hypothesized that exposure to awe-inducing stimuli would decrease participants’ endorsement of materialist values and attitudes, as assessed by the Material Values Scale (MVS) and the Belk Materialism Scale (BMS). Participants were asked to fill out a number of self-report inventories and to watch a video or audio manipulation halfway through the materialism measures, providing a pre- and post-test for self-reported materialism. Self-esteem and dispositional awe were controlled for using the Self-Liking/Self-Competency scale (SCLS) and the awe subscale of the Dispositional Positive Emotions scale (DPES) respectively. Results showed a significant main effect across all three conditions (including control), but no significant differences between conditions. Implications, limitations, and directions for future research are discussed. Department: Psychology Faculty Mentor: Dr. David C. Watson
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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 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".