Curiosity and Interesting Conversations as Factors that Reduce Relational Boredom in Intimate Relationships
Bibliographic record
Abstract
This thesis examined the associations between curiosity, interesting conversations with intimate partners, and relational boredom.I hypothesized that high (vs low) socially-curious people have more frequent interesting conversations and use more interest-related self-regulatory strategies and that this, in turn, is associated with less boredom.Two online studies were conducted with samples of undergraduate students in dating relationships.In Study 1 (N = 137), people high (vs low) in social curiosity more frequently had interesting conversations, and interesting conversations were associated with less boredom.In Study 2 (N = 140), people high (vs low) in social curiosity used more interest-related self-regulatory strategies, and these strategies were associated with less boredom.In Study 2, curiosity subtypes (joyous exploration and thrillseeking) were also associated with using interest-related self-regulatory strategies.The results imply that curious people have skills to create experiences with their partners, such as interesting dinner conversations, that strengthen their relationships.
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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 | 0.001 | 0.012 |
| 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 | 0.002 |
| 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".