What social lives do single people want? A person-centered approach to identifying profiles of social motives among singles.
Bibliographic record
Abstract
= 3,195), we drew on the fundamental social motives framework to provide a theory-based description and understanding of different "types" of single individuals. Across two Western samples (primarily European and American) and one Korean sample (all collected during the COVID-19 pandemic in 2020-2021), we identified three groups of singles with relatively consistent motivational patterns: (a) singles with strong independence motives and little interest in affiliation, mating, or status (i.e., independent profile); (b) singles with great interest in self-protection as well as social connections and status (i.e., socially focused profile); and (c) singles with little interest in self-protection but moderate interest in affiliation (i.e., low safety focus profile). Notably, these profile features did not perfectly replicate in one smaller Western sample collected before the pandemic (particularly the low safety focus profile), highlighting the need to interpret the data with the historical background in mind. Across samples, the independence-oriented group of singles consistently reported greater satisfaction with singlehood compared to other groups. The three groups of singles also showed substantial differences in other affective and behavioral variables (e.g., how they spend their social time). These findings advance the growing body of research on singlehood by offering new theoretical perspectives on different types of singles. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".