Bibliographic record
Abstract
Cities concern themselves with the organization of space. Their principal work involves the mapping, zoning, regulating, taxing, developing, owning, protecting, patrolling, and servicing of land. As a result, cities exert considerable control over the rights of use that property owners enjoy, but they also make many uses possible through the building of infrastructure and the provision of services. However, the effects are not unidirectional; the institution of property is not simply inert clay in the hands of a city. Cities govern the actions of owners and, by extension, shape the institution of property, but this multidimensional institution is, in turn, a powerful influence on the shape and character of cities. The four papers in this “Property in the City” special issue of the UBC Law Review were part of a workshop of the same name devoted to considering the interplay of property and cities. Two of the articles—Teresa Scassa’s “Sharing Data in the Platform Economy: A Public Interest Argument for Access to Platform Data” and Elizabeth Judge and Tenille Brown’s “Pokemorials: Placing Norms in Augmented Reality”—highlight the transformative power of technological change on the institution of property and, in varying ways, on the composition of cities. The two other articles—Dorit Garfunkel’s “High-Rise Residential Condominiums and the Transformation of Private Property Governance” and Douglas Harris’s “Owning and Dissolving Strata Property”—focus on condominium property. The result is a collection of papers that begin to capture something of the constitutive power of property and of cities.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.015 | 0.014 |
| Insufficient payload (model declined to judge) | 0.041 | 0.017 |
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".