Oh de Laval : Konsten att appropriera konst
Bibliographic record
Abstract
Denna uppsats handlar om den samtida konstnären Oh de Laval och utforskar med en semiotiskt förankrad analysmetod appropriering i två olika konstverk och samhörigheten mellan dem. Verken som analyseras i studien är Oh de Lavals, Luncheon on the grass, 2019 och Édouard Manet, Le Déjeuner sur l'herbe, 1863 och stöds av Pablo Picasso, Le Déjeuner sur l'herbe, 1959-1962. Studiens övergripande syfte undersöker hur appropriering av konst förekommer i de olika verken som analyseras samt en juridisk synvinkel kring ämnet. Studien stöds av teoretiska ramverk som inkluderar postkoloniala och feministiska perspektiv som öppnar upp frågor om ras, jämställdhet, kulturell appropriering och kvinnors representation i konsten.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 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".