A theoretical and empirical review of the death-thought accessibility concept in terror management research.
Bibliographic record
Abstract
Terror management theory (TMT) highlights the motivational impact of thoughts of death in various aspects of everyday life. Since its inception in 1986, research on TMT has undergone a slight but significant shift from an almost exclusive focus on the manipulation of thoughts of death to a marked increase in studies that measure the accessibility of death-related cognition. Indeed, the number of death-thought accessibility (DTA) studies in the published literature has grown substantially in recent years. In light of this increasing reliance on the DTA concept, the present article is meant to provide a comprehensive theoretical and empirical review of the literature employing this concept. After discussing the roots of DTA, the authors outline the theoretical refinements to TMT that have accompanied significant research findings associated with the DTA concept. Four distinct categories (mortality salience, death association, anxiety-buffer threat, and dispositional) are derived to organize the reviewed DTA studies, and the theoretical implications of each category are discussed. Finally, a number of lingering empirical and theoretical issues in the DTA literature are discussed with the aim of stimulating and focusing future research on DTA specifically and TMT in general.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".