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Record W4412475325 · doi:10.1080/00918369.2025.2529364

Performing (Homo)Sexual Citizenship Under Authoritarian Rule: Gay Couple Vlogs and Everyday Intimacy in China

2025· article· en· W4412475325 on OpenAlexaff
Zihao Zhou

Bibliographic record

VenueJournal of Homosexuality · 2025
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAuthoritarianismCitizenshipChinaGender studiesPsychologyMale HomosexualitySociologySocial psychologyDemocracyPolitical sciencePoliticsLawMen who have sex with men

Abstract

fetched live from OpenAlex

This article explores fufu (夫夫) vlogs—user-generated video diaries of Chinese gay male couples on Bilibili—as performative acts of (homo)sexual citizenship under authoritarian rule. Drawing on frameworks of sexual, cultural, and performative citizenship, the study examines how these vlogs negotiate relational recognition, legal marginality, and mediated visibility within a tightly censored digital ecology. Combining digital ethnography and reflexive thematic analysis, the article demonstrates that fufu vlogs simultaneously reproduce and resist heteronormative ideals, offering emotionally legible yet normatively constrained depictions of gay life. While these performances often align with conservative scripts of monogamy, domesticity, and filial piety, they also tactically inhabit legal loopholes—such as the Assigned Guardianship System and hukou affiliation—to enact forms of symbolic and relational legitimacy. Crucially, viewer interactions through danmu and comment threads constitute informal pedagogical spaces, circulating information and cultivating civic awareness. The article conceptualizes these mediated practices as performing Chinese authoritarian (homo)sexual citizenship—a mode of gay belonging negotiated through ambivalent performances of public visibility, normative proximity, and strategic intimacy.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.034
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0000.000
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 head0.040
GPT teacher head0.399
Teacher spread0.359 · 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.

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

Citations3
Published2025
Admission routes1
Has abstractyes

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