Bibliographic record
Abstract
This article is a redevelopment of my previous studies, characterizing the media genre of – and community building through – transgender video blogging. Focusing on one of the most famous video bloggers at the moment, the Canadian Julie Van Vu, I investigate new forms of transgender vlogging that embrace money making/self-commodification in a degree not seen before. Here, activism/advocacy co-exists with and goes through an explicit self-commodification. Drawing on existing research, I explore the mechanisms and characteristics of Vu as a micro-celebrity within YouTube as a platform. I suggest the concept of ‘subcultural microcelebrity’ to nuance, diversify and specify micro-celebrity as a concept and a practice. The article departs from – but also redevelops – the concept and characteristics of micro-celebrity to specify the ‘affective labour’. Micro-celebrities are expected to perform various kinds of labour, many of which are time and energy consuming but not necessarily economically profitable. Micro-celebrities must signal accessibility, availability, presence, and connectedness – and maybe most importantly authenticity – all of which presuppose and rely on some form of intimacy. I propose that intimacy as genre and as capital is deeply ingrained in the strategies, dynamics and affective labour of micro-celebrities. Intimacy is an important and necessary signifier in relation to both the form and content of the videos and the relation between the creators and their audience. Furthermore, intimacy works as an important currency within social media; thus, intimacy can be capitalized in manifold and intersecting ways, for example, for monetary purposes, social recognition and as a tool in advocacy work. The article hereby contributes to existing research on YouTube by redeveloping the concept of micro-celebrity in relation to affective labour and intimacy, analysing how these play out in new forms of transgender vlogging.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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".