Being Alone with Others: A Unique Form of Social Contact and Its Impact on Momentary Positive Affect
Bibliographic record
Abstract
Social relationships are essential to human well-being. Although people receive the most benefit from interactions with others who are close to them (Reis, Sheldon, Gable, Roscoe, & Ryan, 2000), the need for human contact can also be satisfied through minimal interactions with others (Sandstrom & Dunn, 2014a, 2014b). This dissertation extended the research regarding the benefits of contact with acquaintances by proposing that being alone with others, i.e. being around others without verbally interacting with them, could be an alternative way of satisfying the need for social contact and improving positive affect. In an experience sampling study (N = 453), being alone with others was associated with similar positive (PA) and negative affect (NA), and lower sense of belonging, than being completely alone. Additional results supported existing research associating the best affective outcomes with interactions with close others, and higher positive affect after talking to acquaintances than not talking to them (Sandstrom & Dunn, 2014a). A second study was designed to test: whether merely sharing a space with others produces a higher sense of belonging; whether this belongingness could explain better outcomes of being alone with others compared to being alone; whether effects depend on performing the same task as others. Participants (N = 265) were randomly assigned to watch a pleasant video: alone, together with a confederate, or alone when a confederate was doing something else. I found no differences in the amplification of PA and sense of belonging, or in reduction of NA between the social conditions; however, these outcomes were also not different in the alone condition. Sharing a space with others, regardless of simultaneously performing a task together, did not lead to better outcomes than being alone. Trait introversion-extraversion was also explored, and two main trends were found in both studies: extraverts reported higher PA and sense of belonging than introverts in all situations, and introverts and extraverts reported similar amplifications of affective states in different social and experimental conditions. Overall, both studies revealed that being alone with others was worse for people's affective outcomes and sense of belonging than being completely alone, contrary to hypotheses.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".