Expropriation and the Socio-Economic Status of Neighbourhoods in Canada: Equal Sharing of the Public Interest Burden?
Bibliographic record
Abstract
Expropriation – the non-consensual taking of privately-owned property by the state in exchange for the payment of compensation – is a widely-used tool of land use planning in Canada as it is in many other states. While in principle all privately-held properties are equally susceptible to expropriation in Canada, legal frameworks on expropriation fail to guard against the possibility that less-wealthy neighbourhoods become more susceptible to expropriation than more wealthy ones (the 99% versus the 1% to put it in the terms used by the Occupy movement of the early part of this decade). The paper examines existing legal frameworks as well as a number of historical expropriation projects in Canada to depict how and why this may come to pass. It does so with a comparative eye turned towards the United States. The paper concludes with several recommendations for strengthening expropriation law frameworks in Canada to ensure that the property of the less-wealthy is as well protected as those properties in higher-income neighbourhoods. La expropiación –la adopción no consentida de una propiedad privada a manos del estado, a cambio de una compensación económica– es una herramienta ampliamente utilizada en la planificación urbanística, tanto en Canadá como en muchos otros estados. Aunque en principio, todas las propiedades en manos privadas tienen la misma posibilidad de ser expropiadas en Canadá, los marcos jurídicos en materia de expropiación fallan a la hora de proteger a los barrios con menos recursos para que no sean más susceptibles a la expropiación que los más ricos (el 99% frente al 1%, según los datos utilizados por el movimiento Occupy durante la primera parte de esta década). Este artículo analiza los marcos legales y una serie de proyectos de expropiación históricos en Canadá para describir cómo y por qué puede llegar a ocurrir esto. Se realiza una comparación con la situación en Estados Unidos. El artículo concluye con una serie de recomendaciones para fortalecer los marcos de la ley de expropiación en Canadá, y asegurar que las propiedades de los menos ricos están protegidas de la misma manera que las propiedades en los barrios más acomodados. DOWNLOAD THIS PAPER FROM SSRN: http://ssrn.com/abstract=2572207
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".