Memorialisation and remembrance: on strategic forgetting and the metamorphosis of psychiatric asylums into sites for tertiary educational provision
Bibliographic record
Abstract
This paper builds on earlier investigations of psychiatric asylum closure by focusing on their not infrequent successor role as educational facilities. We ask two questions: what conditions underpin a transition to educational re-use, and how is former asylum use remembered and memorialised in the successor context? Through recounting and interpreting the histories of acquisition and adaptation at two sites (Carrington, Auckland and Lakeshore, Toronto), we build a narrative that suggests a variable response to the shadows cast by stigma and the vilification of asylum. We distinguish between memorialisation (material reminders on site) and remembrance (narratives of past use). Former asylum sites, we contend, are attractive for educational users for their campus-like settings, range of buildings and (now) suburban locations. For city residents and planners replacing one institutional use with another keeps the site green, brings employment, and retains semi-public access. Memorialisation is often strategically low-key and remembrance more personal and individual. The net result is a relict landscape that speaks to the transcendence of stigma despite the relatively recent demise of the asylum.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.032 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".