MétaCan
Menu
Back to cohort

The Impact of Censorship of LGBTQ Content on Xiaohongshu on Queer Expression

2024· article· en· W4390503998 on OpenAlex

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 · 2024
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsCensorshipQueerExpression (computer science)Content (measure theory)Identity (music)Sexual identityHomosexualityInternet privacyPsychologySociologyMedia studiesGender studiesHuman sexualityPolitical scienceComputer scienceArtLawAesthetics

Abstract

fetched live from OpenAlex

This essay delves into the impact that the censorship of LGBTQ content on Xiaohongshu can have on the expression of queer individuals. This research conducted an analysis of the censorship mechanism of Xiaohongshu, collected tags commonly used by LGBTQ users, and proceeded to analyze the data. Subsequently, the examination of the connection between the causes and effects of the adjustments made at the societal level is done, as well as the stereotypes surrounding the LGBTQ community. Tumblr is being used as an example of how it can help LGBTQ members to find their identity, find peers and friends, and locate communities. All in all, it is concluded that LGBTQ members’ attempts to pass censorship can facilitate engagement with the public, which may dispel stereotypes. However, it is essential to acknowledge that these adjustments may also inadvertently create new stereotypes.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.687
GPT teacher head0.608
Teacher spread0.078 · 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