Curating the forensic gaze in traumatic memorial sites: Recalibrating the sense of materiality in Santiago's Londres‐38
Bibliographic record
Abstract
This paper focusses on the forensic work put on display at Londres-38, a building in Santiago Chile designated as a National Monument, which once functioned as a torture and extermination centre under Pinochet's dictatorship. Striving to avoid conventional memorial practices, or didactic strategies that would morbidly represent the past horror, Londres-38 curatorially opts for very few educational props, so that visitors can have a peculiarly direct encounter with the materiality of the building. The paper engages with one of the few displays employed at Londres-38: a time-looped video detailing the forensic work undertaken on a small washroom. Despite the years that have passed, remaining within its walls, floors, and on the surfaces of the National Monument are material traces left by the detainees-disappeared: scratches and inscriptions, as well as DNA, that are still being forensically harvested. The paper discusses how the video exhibit documents a pedagogical performance of how the unperceived can come to light, how the erasure of the violent past can be made to re-appear as a matter of public concern through a certain sensibility to materiality that is unique to forensics. At issue in the paper is the curatorial–pedagogical strategy employed that invites us to immerse and try out for ourselves the forensic sensibility that tends to and gazes at the materiality of the building in a particular way so that the embedded evidence therein can come to matter and move us to hear the unsettled call for justice in our present.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.030 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.003 | 0.005 |
| 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".