Diversity in singlehood experiences: Testing an attachment theory model of sub‐groups of singles
Bibliographic record
Abstract
OBJECTIVE: Relationship science has developed several theories to explain how and why people enter and maintain satisfying relationships. Less is known about why some people remain single, despite increasing rates of singlehood throughout the world. Using one of the most widely studied and robust theories-attachment theory-we aim to identify distinct sub-groups of singles and examine whether these sub-groups differ in their experience of singlehood and psychosocial outcomes. METHOD: Across two studies of single adults (Ns = 482 and 400), we used latent profile analysis (LPA) to identify distinct sub-groups of singles. RESULTS: Both studies revealed four distinct profiles consistent with attachment theory: (1) secure; (2) anxious; (3) avoidant; and (4) fearful-avoidant. Furthermore, the four sub-groups of singles differed in theoretically distinct ways in their experience of singlehood and on indicators of psychosocial well-being. CONCLUSIONS: These findings suggest that singles are a heterogeneous group of individuals that can be meaningfully differentiated based on individual differences in attachment security.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".