Beyond Monumentalization: Activating Empathy for the “Lost Subjects of History” through Embodied Memorial Performance
Bibliographic record
Abstract
What is the range of our empathy in a globalized world where neoliberal policies and the myriad of violences they produce hurl the debris of history’s catastrophic wreckage into our present, our future? Who do we remember and who do we mourn in a world in which grief is hierarchically constituted, and lives differentially valued along hemispheric, geopolitical, racial, and gendered faultlines? “Beyond Monumentalization: Activating Empathy for the ‘lost subjects of history’ through Embodied Memorial Performance” explores these questions by juxtaposing readings of two embodied and publicly situated memorial performances — Haunting (2013), and Vigil (2002) — with an examination of Stanford University’s institutionalization of dominant memory in and through architectural (and pedagogical) design.
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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 | 0.004 | 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 | 0.008 | 0.027 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".