Times, They Are a Changin': An Examination of Congruent Temporal Appraisals for Self and the Romantic Partner
Bibliographic record
Abstract
As time passes, people change.Change can affect relationships in many ways.I explored trajectories of expected change through time for people evaluating themselves or their romantic partner.Individuals perceive and predict change for their partners in similar ways as for themselves, expecting improvement from the present to the future (Study 1 and 2).I next explored how expected change for the self and for the partner in relation to one another affect relationships.Two partners might change congruently or change at different rates, in different ways.Predicting discrepant change was linked to lower relationship quality and less personal happiness compared to predicting no change or congruent change, both in correlational (Study 3 and 4) and primed designs (Study 5).Across studies, change expectations seemed most linked to outcomes when examined generally rather than in specific domains (Study 3-5).Growth can benefit relationships when it occurs congruently with one's partner.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".