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Record W4403778144 · doi:10.1177/19485506241287960

“Sisters Are Doin’ It for Themselves”: Gender Differences in Singles’ Well-Being

2024· article· en· W4403778144 on OpenAlexafffund
Elaine Hoan, Geoff MacDonald

Bibliographic record

VenueSocial Psychological and Personality Science · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

The experience of singles has been largely overlooked in relationship science, garnering a need for understanding correlates of singles’ well-being. Gender is an important focus of well-being research, and qualitative work on singlehood has suggested that men and women may have experiences of singlehood that differ in important ways. In this study ( N = 5941; 50% men; M age = 31.74), we provide the first comprehensive, descriptive profile of gender differences on a suite of variables with important ties to well-being in singlehood; satisfaction with relationship status, life satisfaction, sexual satisfaction, and desire for a partner. Our results suggest that single women, on average, report higher levels of satisfaction with relationship status, life satisfaction, sexual satisfaction, and lower desire for a partner. Exploratory analyses showed significant gender interactions with age and ethnicity. Overall, these findings suggest that women are, on average, happier in singlehood than men.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.162
GPT teacher head0.405
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2024
Admission routes2
Has abstractyes

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