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Record W6964295617 · doi:10.25384/sage.c.6898101.v1

“Cat Ladies” and “Mama’s Boys”: A Mixed-Methods Analysis of the Gendered Discrimination and Stereotypes of Single Women and Single Men

2023· other· en· W6964295617 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSingle mothersQualitative researchSingle sexQualitative analysisSingle stageSingle-subject designPrejudice (legal term)

Abstract

fetched live from OpenAlex

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 <i>N =</i> 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: <i>Professional</i> (“independent,” “hard-working”), <i>Carefree</i> (“free,” “fun”), <i>Heartless</i> (“selfish,” “promiscuous”), and <i>Loner</i> (“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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.360
Teacher spread0.279 · 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 teacher head, not a consensus.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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