Bibliographic record
Abstract
This thesis explores the significance of the trans werewolf figure in the circulation of art on Tumblr in the “#trans werewolf” tag. Based on ethnographic research conducted over a period of fourteen months, it approaches this topic through the lens of the discipline of folklore, primarily queer folklore and digital folklore. Some of the questions the thesis asks are: who is the trans werewolf, and what does trans werewolf art say about its community of creators and those who circulate and consume this art? The first chapter explores the Tumblr social media environment as a site of an established folk group in order to discuss the meaning-making, interpretation, and proliferation of trans werewolf art. The second chapter examines the general trends in contemporary werewolf media with a primary focus on Western media, and situates the werewolf as a symbol of otherness and abjection. It then discusses ways in which the trans werewolf aligns with or rejects that perspective. Based on ethnographic interviews, the third chapter considers the perspectives of trans werewolf artists on Tumblr, which are defined as the active bearers of this folk expression. This thesis finds that the trans werewolf as a figure primarily resonates with young adult, white, transmasculine, neurodivergent people living in Western countries such as the United States, the United Kingdom, and Canada. The figure’s function on Tumblr as it appears in #trans werewolf art seems to primarily represent community-building, self-representation, and protest of anti-trans rhetoric. Keywords: digital folklore, queer folklore, werewolf, werewolf art, digital art, queer art, Tumblr, social media, trans, transgender, trans folklore
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".