The good, the bad, and the complex: Qualitative accounts of how people navigate singlehood benefits and challenges
Bibliographic record
Abstract
Singlehood is often described as a binary: some single people struggle, while other singles thrive. Yet, single people likely experience challenging and beneficial aspects of singlehood simultaneously. We used qualitative approaches to provide insight about how single people navigate aspects of singlehood that are challenging and aspects that offer opportunities to thrive. Eleven single adults took part in 30–45-minute semi-structured interviews. Single participants were of diverse ages and ethnic backgrounds, represented a gender balanced sample, and reported diverse relationship histories ranging from never coupled to divorced. Using reflexive thematic analyses, we identified three themes that reflected broader complexities about navigating singlehood challenges and benefits: (I) whether and when should single people invest in singlehood, (II) balancing the tension between singlehood facilitating autonomy versus romantic relationships facilitating deep emotional connection, and (III) how to respond to feelings or experiences of societal pressure to partner that encourages romantic coupling. These findings shed light on how single people manage mixed feelings about singlehood and romantic coupling.
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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 | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".