Fluctuations in self-esteem and paranoia in the context of daily life.
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
Studies investigating the relationship between self-esteem and paranoia have specifically focused on self-esteem level, but have neglected the dynamic aspects of self-esteem. In the present article, the authors investigated the relationship between self-esteem and paranoia in two different ways. First, 154 individuals ranging across the continuum in level of paranoia were studied with the Experience Sampling Method (a structured self-assessment diary technique) to assess the association between trait paranoia and level and fluctuation of self-esteem in daily life. Results showed that trait paranoia was associated with both lower levels and higher instability of self-esteem. Second, the temporal relationship between momentary (state) paranoia and self-esteem was investigated in the daily life of these individuals. Results showed that a decrease in self-esteem was associated with an immediate increase in paranoia. The findings indicate that paranoid individuals are not only characterized by a lower level of self-esteem but also by more fluctuations in their self-esteem and that fluctuations in self-esteem predict the degree of subsequent paranoia. These results are consistent with the hypothesis that paranoia is associated with dysfunctional strategies of self-esteem regulation.
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 | 0.001 |
| 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