The Beguiling: Glamour in/as Platformed Cultural Production
Bibliographic record
Abstract
Arguing that questions of power expressed through aesthetic form are too often left out of current approaches to digital culture, this article revives the modernist aesthetic category of glamour in order to analyze contemporary forms of platformed cultural production. Through a case study of popular feminism, the article traces the ways in which glamour, defined as a beguiling affective force linked to promotional capitalist logics, suffuses digital content, metrics, and platforms. From the formal aesthetic codes of the ubiquitous beauty and lifestyle Instagram feeds that perpetuate the beguiling promise of popular feminism, to the enticing simplicity of online metrics and scores that promise transformative social connection and approbation, to the political economic drive for total information awareness and concomitant disciplining, predicting and optimizing of consumer-citizens, the article argues that the ambivalent aesthetic of glamour provides an apt descriptor and compelling heuristic for digital cultural production today.
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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 | 0.004 |
| 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 | 0.032 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".