New Modes of Housing Consumption: Financialization, Multi-Scalar Governance, and the Transformation of Tenure
Bibliographic record
Abstract
Financialization has fundamentally changed the modes of housing consumption. Housing is no longer mainly provided as shelter but increasingly has become a means for driving the finance-led capitalist accumulation. Among housing research, the division of housing by tenure categories (such as owning and renting) has been a deep-rooted convention. But as various housing tenure sectors all have been transformed by financial capital and became financialized, this division seems to be dissolving. The states, at all geographical scales, use distinctive measures to manipulate housing consumption for the purpose of instigating the finance-led capitalist accumulation system. This dissertation examines the changing modes of housing consumption under financialization, with a special focus on the changing meaning of housing tenure and the roles of multi-scalar states in this process. The dissertation deepens our knowledge about new models of housing consumption in the contemporary. It also sheds some light on how existing housing research programs shall be reframed and revised so as to better understand the contemporary housing question. The dissertation is organized as three articles which are preceded by an introductory chapter and followed by a concluding chapter. While the three articles all combine empirical materials and theoretical arguments, the first article focuses on studying an empirical case and the other two articles pursue theoretical insights. The first article studies Toronto’s affordable housing policy. It demonstrates the distinctive extents of financialization in multi-scalar states’ affordable housing policies. The second article critiques the dichotomous understanding of housing tenure as consisting of owning and renting in the field of housing studies. It attempts to re-conceptualize housing tenure in a relational dialectical manner as a relation of the occupant to financial markets. The third article critiques the unreflective division of housing by tenure categories in the financialization of housing literature in geography. It directly builds on David Harvey’s Marxian theory of capital to explicate the meaning of housing tenure and how it matters for financialization. It generates theoretical implications for studies on the financialization of housing literature and financialized urban governance literature.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".