Same but different: meta-analytically examining the uniqueness of mortality salience effects
Bibliographic record
Abstract
One line of theorizing suggests considering death reminders—i.e., mortality salience (MS) inductions—unique in their effect on worldview defenses (e.g., Pyszczynski et al., 2006). Other theorizing suggests that meaning and certainty threats produce effects similar to MS and thus that these threats be considered theoretically equivalent (e.g., Proulx & Heine, 2006; McGregor, 2006). To help reconcile these discrepant perspectives, we meta-analytically examined MS effects as a function of the control condition utilized (meaning/certainty threats vs. other topics) and the length of delay between threat induction and subsequent defense. Results showed that MS and meaning/certainty threats both increased defensiveness after a short delay. But with a longer delay, MS produced even higher levels of defensiveness while meaning/certainty threats produced lower levels of defensiveness. Thus, the evidence supports a similarity between MS and meaning/certainty threat effects, but also a difference in time course that warrants their study as unique psychological threats. Copyright © 2010 John Wiley & Sons, Ltd.
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 | 0.049 | 0.138 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.023 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".