Bibliographic record
Abstract
In this article, we argue that a monument’s commemorative, artistic, and political essence can be turned off by its audiences. In this way, monuments find an afterlife in the everyday; they open to new horizons of ordinary significance, practicality, and accessibility. We compare three distinct approaches for creating an afterlife with monuments: from above, from below, and from both sides. Commemorative public art is framed as a medium for monuments to pass from active to dormant, and vice versa. First, a Nazi-era monument in Hamburg, Germany, was officially turned by publicly commissioned artistic intervention into a site of counterremembrance. Second, a monument in Montreal, Canada, shows how artistic, social performances can create bottom-up, unforeseen, and potentially transgressive functions to monuments. To illustrate the interplay of both top-down and bottom-up artistic approaches to bringing new life to monuments, a colonial site in Amsterdam, the Netherlands, shows how successive generations can recurringly revise a contested memory site. In the final section, we argue that monuments are never turned off for good. Where monuments can fade into the background, they can also have their salience agonistically turned back on again through artistic activism and adversarial forms of remembrance.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.033 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".