Factors promoting greater preoccupation with a secret
Bibliographic record
Abstract
The secrets that are most taxing to one’s health and well‐being are those that are the most preoccupying to the secret‐keeper. However, it is currently unclear what makes a secret preoccupying. We conducted a four‐wave longitudinal study to assess four factors that should contribute to one’s degree of preoccupation with a secret kept from one’s spouse/romantic partner: perceived cost of revealing the secret, frequency of cues, fear of discovery, and individual differences in self‐concealment. Multilevel modelling of data from an online sample of 143 adults (51% women, 49% men; M age = 39.9, SD = 9.3) keeping a secret from their spouse/partner indicated that all four factors independently and positively predict greater preoccupation with a secret. Further, the first three factors also significantly predicted how preoccupied one would be with one’s secret two weeks later, taking into account how preoccupied one was with the secret at present. We conclude that the characteristics of the secret, as well as the secret‐keeper, can contribute to how preoccupying a secret is to an individual.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".