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Record W3194136522 · doi:10.1177/01968599211040835

Who Counts as Trans? A Critical Discourse Analysis of Trans Tumblr Posts

2021· article· en· W3194136522 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

VenueJournal of Communication Inquiry · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMainstreamTransgenderHegemonySociologyIdentity (music)IdeologyCritical discourse analysisVisibilityNarrativeSocial mediaGender studiesMedia studiesPoliticsPolitical scienceAesthetics

Abstract

fetched live from OpenAlex

Internet and social media sites have long served as a rich form of community-building and knowledge exchange within transgender communities. In particular, Tumblr has become a popular site among trans youth in recent years. Paralleling changes in medical and mainstream societal understandings of what it means to be transgender, trans Tumblr users have engaged in dialogue and debate about the definitions and limits of trans identity. While research has established the potential for positive identity-formation among LGBTQ+ youth on Tumblr, it is also important to consider how online trans communities may re-inscribe hegemonic narratives in addition to disrupting dominant discourses and ideologies. Using a critical discourse analysis of Tumblr posts, this research analyses how trans Tumblr users define “who counts as trans,” including how users define gender dysphoria and its relationship to trans identities. Our findings provide critical insight into how trans communities define the boundaries of their identities in a struggle for visibility, resources, and respect.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.075
GPT teacher head0.455
Teacher spread0.381 · 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