The secrets that you keep: Secrets and relationship quality
Bibliographic record
Abstract
Abstract Research indicates that preoccupation with secrets takes a toll on mental health. There is also some evidence to suggest that keeping secrets from one's romantic partner may harm the relationship as it implies a lack of trust that one's partner will be supportive. Two 4‐wave longitudinal surveys of 609 adults (34.3% men, 65.4% women; M age = 36.4) keeping a secret from their romantic partner was used to assess the lagged effect of preoccupation with the secret on subsequent relationship satisfaction, trust, and emotional intimacy as well as the reverse. Cross‐lagged panel modeling with random intercepts indicated that whereas individuals in poorer relationships were more preoccupied with their secrets, there was no evidence for cross‐lagged effects. The findings suggest that secrecy may be a symptom—not a cause—of a dissatisfying, distrustful and distant relationship.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 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 | 0.002 |
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".