Bibliographic record
Abstract
Being placed in a high pressure situation may impact people’s narcissistic tendencies. When in a situation that is threatening to one’s sense of self, people may self-promote and strive to attain social attention (i.e., report more narcissistic admiration) or may self-protect and behave defensively (i.e., report more narcissistic rivalry). This study explored how a stressful situation (i.e., a job interview) increases one’s desire for social admiration or antagonism. In order to induce pressure, we manipulated the amount of time participants took to complete a task and the amount of researcher pressure applied. In this study, participants (N = 300) imagined themselves in an interview context, where they listed as many answers to an interview question as they could before time expired. Participants completed the task in either 15s (high time pressure) or 60s (low time pressure). Before completing the task, participants received a statement designed to strongly encourage them to do well on the task (high researcher pressure) or received no such statement (low researcher pressure). We then measured participants' narcissistic admiration and rivalry, using the Narcissistic Admiration and Rivalry Questionnaire. Although researcher pressure had no impact on narcissism, we found that those in the low time pressure condition showed slightly higher scores on narcissistic rivalry compared to those in the high time pressure condition. Overall, it seems that pressure influences the extent to which individuals exhibit antagonistic narcissism, where more pressure results in decreased confidence and rivalry. Department: Psychology Faculty Mentor: Dr. Miranda Giacomin
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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 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".