To see others in ourselves: justice and architectural ambiguity in the Tuol Sleng Genocide Museum
Bibliographic record
Abstract
Grounded in Amartya Sen’s work on justice, identity, and violence, this article studies the Tuol Sleng Genocide Museum in Cambodia as a space that encourages the ethical assessment of justice through non-didactic, disjunctive resonance between the normative and the unfamiliar. Defining architecture as a meaningful spatio-temporal continuum, the article employs an analytical methodology drawn from creative praxis to argue that our senses of identity are formed through architecture both cognitively, in our response to the known, and affectively, in our experience of the unknown. In order to retain the discursive nature of justice, this continuum needs to operate with a destabilising ambiguity to avoid exclusive ‘othering’. This ambiguity allows for our sense of identity to expand beyond group-based ideologies that can sustain and hide societal violence.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.037 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".