Bibliographic record
Abstract
Individual media events, from the extraordinary to the mundane, as well as the logic they present, have transcended society. Media events no longer happen in isolation, they are intertextually and extratextually linked and mixed together. The ability to view, create, join in, and affect the shape of media events has caused a profound shift in the conception of what they are. What Daniel Dayan and Elihu Katz refer to as individual media events, Guy Debord, Michel Foucault and Douglas Kellner consider collectively as spectacle. Their work on media events and spectacle features a debate on the role of contestation within it. Live audience members have an opportunity to impact media events and the spectacle either through individual or collective action. This action can go along with the intents ascribed to the media event and spectacle, or it can oppose them. Contestation often takes the form of an oppositional interruption of the linear messaging promoted within media events and spectacle. Contestation is typically a strategy used by voices that feel marginalized by the images of the spectacle. But contestation of media events and spectacle through their own logic becomes a means of deeper seduction.
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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.012 | 0.088 |
| Scholarly communication | 0.022 | 0.029 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.005 | 0.010 |
| 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".