Compensatory conviction in the face of personal uncertainty: Going to extremes and being oneself.
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
Study 1 participants' self-integrity (C. M. Steele. 1988) was threatened by deliberative mind-set (S. E. Taylor & P. M. Gollwitzer, 1995) induced uncertainty. They masked the uncertainty with more extreme conviction about social issues. An integrity-repair exercise after the threat, however, eliminated uncertainty and the conviction response. In Study 2, the same threat caused clarified values and more self-consistent personal goals. Two other uncertainty-related threats, mortality salience and temporal discontinuity, caused similar responses: more extreme intergroup bias in Study 3, and more self-consistent personal goals and identifications in Study 4. Going to extremes and being oneself are seen as 2 modes of compensatory conviction used to defend against personal uncertainty. Relevance to cognitive dissonance and authoritarianism theories is discussed, and a new perspective on terror managenment theory (J. Greenberg, S. Solomom, & T. Pyszczynski, 1997) is proposed.
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 | 0.002 | 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 | 0.000 |
| 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