Death and Black Diamonds: Meaning, Mortality, and the Meaning Maintenance Model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Meaning Maintenance Model (MMM; Heine, Proulx, & Vohs, 2006 Heine, S. J., Proulx, T. and Vohs, K. D. 2006. The Meaning Maintenance Model: On the coherence of social motivation. Personality and Social Psychological Review, 10(2): 88–111. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) proposes that human beings innately and automatically assemble mental representations of expected relations. The sense of global meaning that these relations provide is regularly disrupted by unrelated or unrelatable experiences, which elicit feelings of meaninglessness. People respond to these disruptions by engaging in meaning maintenance to reestablish their sense of symbolic unity. Meaning maintenance often involves the compensatory reaffirmation of alternative meaning structures through a process termed fluid compensation. The MMM proposes a fundamental reinterpretation of the social psychological literature, arguing that meaning maintenance is a general mechanism that underlies a host of diverse psychological motivations, including self-esteem needs, certainty needs, and the need for symbolic immortality. In particular, the MMM stands in contrast to Terror Management Theory in that mortality salience is explained by the MMM to be one of many specific instantiations of threats to meaning that engenders fluid compensation.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it