Performative Interior Design in the Criminal Courtroom
Bibliographic record
Abstract
This paper engages with the idea that interior design is a performative practice. The central question of interest is dramaturgical rather than instrumental: How do building interiors “act” and how do these performances construct a particular definition of the situation? We critically bring into play related academic discussions of “political interiors” and “the good organization” by exploring the built environment of the court of law. The good organization is an ideal–type used to help identify and understand the deficiencies of actual organizations. We show that ontological politics is at work when performative design enables problematic realities. This study relied on a microethnographic research method using participant observation as the data collection strategy. It focused on a Canadian interior design project that implemented a workplace violence assessment in the criminal courtrooms of the Nova Scotia justice system. We use theatrical performance as a research lens, drawing on dramaturgy, as a fruitful way to engage with the concept of political interiors. This expands beyond mainstream epistemological assumptions about the grounds for knowing. We find that criminal courtrooms, as the physical expression of the good organization, are rooted in questionable design assumptions that are seldom examined. The nominalist stance in this paper promotes a more complete understanding of the realities of interior space that are socially constructed through physical settings that create, preserve, and promote hierarchy, personal stigma, and theatricality.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.033 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| 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".