“Cat Ladies” and “Mama’s Boys”: A Mixed-Methods Analysis of the Gendered Discrimination and Stereotypes of Single Women and Single Men
Bibliographic record
Abstract
Do single women and single men differ in their experiences of “singlism”? This mixed-methods research examined whether single women and single men report quantitative differences in amounts of singlehood-based discrimination and explored qualitative reports of stereotypic traits associated with single women and single men. We recruited Canadian and American single adults across two Prolific studies (total N = 286). The results demonstrated that single female and male participants did not differ in their personal discrimination, but female participants perceived single women to experience more discrimination than single men. Furthermore, qualitative analyses revealed four overlapping “archetypes” of single women and men including: Professional (“independent,” “hard-working”), Carefree (“free,” “fun”), Heartless (“selfish,” “promiscuous”), and Loner (“lonely,” “antisocial”). Overall, single women and men may experience similar stereotypes and discrimination, but there are also important nuances that highlight the need for more research at the intersection of gender and singlehood.
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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 | 0.023 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".