Performing, Translating, Fashioning: Spectatorship in the Surveillant World
Bibliographic record
Abstract
Despite the disciplinary power of surveillance, I argue artistic performances may also provide a space of resistance and self-fashioning. Discussions on artistic performance emphasize the ambivalence and uncertainty of art to resist existing power structures and create alternative meaning. However, how concretely, and when, do artistic performances challenge these structures often remains uncertain. Their popularity does not guarantee the depth of their engagement with surveillance practices, and apparent resistance may hide unconscious cooptation and blatant reproduction of existing inequalities and power structures. To understand the political effect of artistic performances, I argue one needs to look at how they participate to the redefinition of individual and collective selves. This must include attention to spectatorship as a different category from state and corporate surveillance. Spectators engage with performers, reinforce or deny their claim to self-fashioning. By looking at spectators one can better understand how a performance can be (or fail to be) self-fashioning not only for the performer but also collectively for the spectators.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.034 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".