Self‐concept clarity and the evaluation and selection of incompatible dating partners
Bibliographic record
Abstract
Abstract Romantic compatibility is theorized to play a crucial role in the success and stability of romantic relationships, although evidence to date has been somewhat indirect. Previous experimental findings suggest that those lower, relative to higher, in self‐concept clarity find it more challenging to evaluate similarity (i.e., a contributor to compatibility) in prospective romantic partners. The current research extends these findings by directly examining self‐concept clarity and romantic partner (in)compatibility in real‐world experiences. Across two retrospective studies (N = 340), we found that those lower, relative to higher, in self‐concept clarity dated incompatible others more frequently, experienced greater difficulty judging compatibility, and were less decisive in their dating decisions. They also experienced greater dating‐related negative affect but did not report lower satisfaction in past dating. Exploratory mediation analyses further suggest that such individuals experienced greater dating‐related negative affect through dating incompatible others more often. Specifically, they were more likely to date incompatible others if they found it harder to judge compatibility and were less decisive in dating. These results suggest that individuals with a confused personal identity (i.e., low in self‐concept clarity) may find it more challenging to evaluate potential dating partners, leading them to rule out incompatible ones less often.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".