Bibliographic record
Abstract
Previous research has shown that the experience of schadenfreude (pleasure derived from someone else’s misfortune) serves an adaptive value by alerting individuals of competing rivals or mating opportunities (Colyn & Gordon, 2013). The present study examined gender differences in the experience of schadenfreude towards a male and female celebrity in a sample of 203 undergraduate students. The findings show that women (n = 102) reported greater schadenfreude towards the female celebrity, whereas men (n = 101) reported more intense schadenfreude overall towards both the female and male celebrity. Furthermore, several predictors of schadenfreude were examined including empathy, envy, deservingness, and hostility. The results indicate that schadenfreude was correlated strongly with deservingness (r = .63) and weakly correlated with empathy (r = - .11). The findings from this study suggest that schadenfreude is a multi-determined emotion that can be evoked by many factors such as gender, social values, and an individual’s reaction towards the misfortune. Discipline: Psychology Honours Faculty Mentor: Dr. David Watson
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".