We Were Meant to be: Do Implicit Theories of Relationships and Perceived Partner Fit Help Explain Post‐Relationship Contact and Tracking Behaviors Following a Breakup?
Bibliographic record
Abstract
ABSTRACT Those experiencing relationship termination often report using efforts to contact and/or track their ex‐partner, frequently with the intent of re‐establishing connection. Implicit beliefs about relationships as being predestined (destiny beliefs) or requiring cultivation for success (growth beliefs) appear to be linked to concepts of partner fit and attempts to re‐establish connection. Combining findings across four studies, this mixed‐methods research explored how beliefs about relationships and perceptions of partner fit were linked to post‐relationship contact and tracking (PRCT). Study 1 demonstrated that stronger endorsement of destiny (but not growth) beliefs was linked to recall of higher levels of PRCT. Study 2 replicated these findings and indicated that partner fit moderated the link between destiny beliefs and PRCT. Using an experimental design, Studies 3 and 4 showed it was possible to manipulate anticipated use of PRCT, particularly destiny beliefs. This work adds information to our understanding of how relationship beliefs impact adjustment following relationship loss, with implications for those supporting individuals in distress and highlighting the possibility of altering destiny beliefs to improve adjustment.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".