Object-hood’s Indecencies: <i>Tilted Arc</i> and the Lessons Learnt in Breakdown
Bibliographic record
Abstract
Abstract This essay looks to re-evaluate sculptor Richard Serra’s famous claim that “to remove the work is to destroy it.” Using OOO, and particularly Graham Harman’s interpretation of Martin Heidegger’s tool analysis, in order to analyze the now famous moment when Tilted Arc was de-installed from Federal Plaza, Manhattan in 1989, this paper argues that the work was not in fact destroyed but rather that its ontological autonomy was even more absolutely revealed in that moment as such. Although it is the case that art objects and sites are prone to discursive co-construction and evaluation, it is this analysis’ claim that they both are possessive of a deep, substantive form also, a form resistant to appropriation. Tilted Arc therefore revealed something even more insidious and dangerous to those who opposed it than the power of art to speak back to its surroundings. Rather, it uncovered the substantive objecthood of the site itself.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.049 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 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".