Transgressive DIY (“Do It Yourself”) Spaces, Mixed Virtual/Physical Affinity Spaces, And Building Code Vigilantism
Bibliographic record
Abstract
This article first situates itself within the example of Toronto as one of UNESCO’s newly minted global “Cities of Culture.” This network of “creative cities” is intended to facilitate a framework for these cities to work together in “placing creativity and cultural industries at the heart of their development plans at the local level and cooperating actively at the international level.” As one of Toronto’s culture-oriented redevelopment strategies, its “Music City” initiative is an example of how music and sound can be used in city marketing and place branding, and how these redevelopment strategies must be more effectively deployed to protect the same cultural elements that are being marketed so that the diversities of “culture” and “music” in a city are better represented. To this end, this article then turns to the recent deadly fire that decimated Oakland’s Ghost Ship DIY community and live/work artist-run space as a prominent and applicable warning for the local governance and municipal legal frameworks of many other cities with similar artistically potent, but precarious and vulnerable, spaces of independent and grassroots art and culture. Tracing the nuanced interactions of mixed virtual/physical affinity spaces engaging groups and individuals that find a home in DIY spaces with those who would seek to have these spaces and individuals displaced reveals a growing trend of what can be termed: building code vigilantism. While Toronto is but one example where independent grassroots arts and culture spaces have been affected by building code vigilantism, similar communities in cities across North America have been targeted with the same processes and to the same displacing effect. As such, a micro examination that narrows in on the experience of a local DIY community—such as the one found in Toronto—is relevant to any other urban center interested in sustainable redevelopment strategies, legislation, and policies that rely on “culture.”
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".