Enhanced Mood After a Getting-Acquainted Interaction with a Stranger: Do Shy People Benefit Too?
Bibliographic record
Abstract
People report positive moods and enhanced well-being when they socialize with friends and other close ties. However, because most people routinely have more encounters with acquaintances and strangers (social connections known as weak ties) than with close friends or kin ( strong ties), we deemed it important to examine whether interaction with weak ties also enhances happiness and well-being. This investigation, which analyzed data from two laboratory procedures, examined whether participants’ positive affect (PA) increased and negative affect (NA) decreased, from before to after a getting-acquainted interaction with a stranger. We also considered whether any benefits of the interaction were moderated by the participants’ level of shyness. Participants ( N = 270; 135 dyads) from a U.S. university completed mood indices before and after a getting-acquainted task. Their PA significantly increased and their NA significantly decreased from before to after the interaction. Shy participants experienced greater NA both before and after the getting-acquainted interaction (relative to less shy participants), but the shyness level of our participants did not moderate the pattern of change in their PA and NA. Shy participants experienced increases in PA and decreases in NA that were similar to those of less shy participants. We discuss implications of the results regarding the important role of weak social connections for increasing one’s daily mood, including for those who are shy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".