Bibliographic record
Abstract
THE PROBLEM WITH PROVOCATION: ON LARS VON TRIER, ENFANT TERRIBLE OF DANISH ART FILM Anyone interested in contemporary art is likely to have spent a good deal of time pondering the nature and role of artistic provocation. Provocation as a crucial feature of artistic practice was largely unknown before 1800 (Walker 1999: 1). The idea of 'shocking the recipient' was, however, 'a dominant principle of artistic intent' for members of the various avant-garde movements that emerged in the early decades of the 20th century (Peter Bürger, cited in Walker: 2), and at this point the provocateur is a well-known and even expected figure in the landscape of art. It is not difficult to think of examples of artworks that are self-evidently about creating a sense of outrage. Let me mention just a few well-known works that prompted a public outcry: Rick Gibson's Human Earrings (1985), which consists of a...
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".