What's In a (Stage) Name? Public Personas, Private Selves, and the Transgression of Authenticity
Bibliographic record
Abstract
The K-pop star often goes by two names: the stage name and “real” name. On the Archive of Our Own, a major fan fiction repository, the tags are designed to facilitate searches for either name. Given that the common practice among K-pop fan fiction writers is to use the “real” name, this paper asks how a specific examination of the stage name in the K-pop medium might redefine the relationship between the stage name and the real name in celebrity discourse. To this end, this paper compares two different constructions of the celebrity text: one constructed by the K-pop industry through reality television and one constructed by fan fiction writers reflecting upon their own craft. This paper argues in favor of a connection between these constructions: namely, that the K-pop industry and K-pop fan fiction are both premised on the construction of a dichotomy between the public person and the private self that is performatively transgressed in order to generate an affect that cannot be evoked by either the public or the private alone. The paper concludes by suggesting that these transgressions point toward a new model of celebrity as embodied by the K-pop idol: not a static “persona” but a dynamic negotiation between the “very-much-public” and the “not-so-public.”
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".