Bibliographic record
Abstract
This paper seeks to reframe the way we think about the rise of “dehousing” (Hulchanski et al., 2009, p. 3) in Toronto. Outsourced private security and militaristic, colonial policing by the state (Kanji & Withers, 2021) displace people from warm air vents, tiny homes, tarps, tents, and other secluded places of refuge. Rather than see empty public space or fenced off parks as neutral ground amidst a housing crisis, I propose that these sites constitute a “ruin.” How might the ruins bear witness to the violence of dehousing? I frame my analysis through Crane’s premise (2021) that Nothing must be seen as a Something. She reveals how photography can help us in the documentation of Nothing (Crane, 2021). With the help of photographs, this paper attempts to animate the pedagogical witness of the places where Nothing remains. Rather than being conceived as a natural result of some “generic human tendency” (Crane, 2021, p. 121), ruins can be understood as part of presently existing unjust systems that must be changed. The “ruins of dehousing” turn us toward histories of colonial displacement, our relationship to public space, and our obligation to become conscious of Nothing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.068 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| 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".