Personality and Social Relationships: What Do We Know and Where Do We Go
Bibliographic record
Abstract
Personality and social relationships influence each other in multiple and consequential ways. To understand how people differ from each other in their personality and social behavior, how these differences develop, and how this affects further life outcomes, we need to better understand the interplay of personality and social relationships. Here, we provide an integrative overview on personality-relationship research across relationship types (everyday encounters, friendships, romantic, and family relationships), and personality characteristics. We summarize the state of research on (a) how much relationship aspects vary across actors, partners, and actor-partner relations, (b) which personality characteristics predict these variance components (i.e. actor, partner, and relationship effects), and (c) how social relationships work as contexts for personality development. Following an integrative process framework, key open questions are discussed concerning the processes that underlie personality-relationship and relationship-personality effects. We conclude with a call for conceptual integration, methodological expansion, and collaborative action.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".