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Record W4411160677 · doi:10.54254/2753-7064/2024.23641

The Impact of Playing the Otome Game on Single Women’s Interest in Real-life Romantic Relationships

2025· article· en· W4411160677 on OpenAlex
J Chen, Luo Yu, Yujuan Jiang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCommunications in Humanities Research · 2025
Typearticle
Languageen
FieldPsychology
TopicChild Therapy and Development
Canadian institutionsWestern University
Fundersnot available
KeywordsRomancePsychologySocial psychologyDevelopmental psychologyPsychoanalysis

Abstract

fetched live from OpenAlex

Otome games have gained popularity among women, offering a space to fulfill their emotional and romantic desires. This study explores how playing Otome games may reduce single women’s interest in real-life romantic relationships through the lens of evolutionary psychology. We designed a study with 200 single Chinese women aged 18-35 who have not previously played Otome games, to play an Otome game called Love and Deepspace for three months and we will record their gaming time and monetary expenditure. The study aims to test the hypothesis that increased engagement in Otome games, measured by time and money spent, negatively correlates with participants’ interests in real-life romantic relationships. Our research examines how supernormal stimuli—idealized traits in virtual romantic partners—appeal to female mating preferences, contributing to an evolutionary mismatch. This mismatch may have significant implications for how modern virtual dating experiences shape romantic behaviors, with potential effects on societal trends such as declining interest in real-life romantic relationships.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.536
GPT teacher head0.511
Teacher spread0.025 · 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