The Multidimensional Mortality Awareness Measure and Model
Bibliographic record
Abstract
For each of eight literature-identified conceptual dimensions of mortality awareness, questionnaire items were generated, producing 89 in all. A total of 359 participants responded to these items and to questionnaires measuring health attitudes, risk taking, rebelliousness, and demographic variables. Multivariate correlational analyses investigated the underlying structure of the item pool and the construct validity as well as the reliability of the emergent empirically derived subscales. Five components, rather than eight, were identified. Given the item content of each, the associated mortality awareness subscales were labeled as legacy, fearfulness, acceptance, disempowerment, and disengagement. Each attained an acceptable level of internal reliability. Relationships with other variables supported the construct validity of these empirically derived subscales and more generally of this five-factor model. In conclusion, this new multidimensional measure and model of mortality awareness extends our understanding of this important aspect of human existence and supports a more integrative and optimistic approach to mortality awareness than previously available.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".