Housing booms in gateway cities By DavidLey, West Sussex: Wiley. 2023. 336pages. $41.95 (paperback). ISBN: 9781119853602
Bibliographic record
Abstract
In Housing booms in gateway cities, David Ley sets out “to examine the place of the homeownership market—its price trends, their causes and consequences, and its management by government—in the economy and the society of five gateway cities” (p. 13). Contributing to the discussions on wealth accumulation and housing in asset-based societies, the author builds his study on three precepts: (1) the increasing importance of housing as an investment asset and a popular wealth accumulation strategy, (2) the attractiveness of property markets in gateway cities for investors, and (3) the rise of unaffordable housing in these locales. With a particular focus on the post-2008 period, Ley investigates five gateway locations (Singapore, Hong Kong, Sydney, Vancouver, and London) to explain how the rise of housing prices in each context stems from the particular inter-relationships of local and global processes, notably, the priorities and strategies of elite growth coalitions and government responses to local realities and transnational pressures. Without providing a fully fledged comparison of the five cases, the author shows how the circumstances in each gateway city resonate with one another in that they face similar pressures, follow similar trends, and provoke similar government dilemmas. Each empirical chapter takes a deep dive into the housing market of one gateway city, highlighting the complex and evolving inter-connections between national sociodemographic and economic trends, global and geopolitical pressures, national political framings, and other significant local social realities. The chapter on Singapore shows that homeownership has long been framed as a form of asset-based welfare within the government's nation-building agenda, which has resulted in careful and sustained government interventions in the housing market over time (Singapore is presented as the outlier case). Moving to Hong Kong, Ley shows how the dynamics of the local housing market contribute to and are part of a growing class divide between owners and renters, mostly due to an unchecked elite growth coalition centred around global property developers. The study of Sydney adds to this mix the responsibility of governments in encouraging local and global investors to participate in the local housing market, often in a way that replaces an explicit housing policy with financial and tax measures. In Vancouver, Ley documents governments’ reluctance to acknowledge and resolve dysfunctional aspects of the local housing market, as well as recent efforts to reregulate the sector and address housing supply and affordability. Finally, in his study of London, and more specifically, the “season of excess” (p. 184) during the 2012 Olympics, the author highlights the key role of decades-old austerity policies and a neoliberal mindset restricting governments’ ability to deliver affordable housing and address rising inequalities. Whereas the empirical chapters provide valuable insights into the similar pressures and particular dynamics affecting the various locales, the introductory and concluding chapters ground the conceptual significance of studying affordability in the housing market to deepen our understanding of the contemporary dynamics of gateway cities. Ley puts forth highly relevant and carefully crafted observations about gateway cities, including housing market trends and pressures since the 1970s, and the role of global investment, especially from Asia, on price gains. The author also provides a much-needed discussion of the negative consequences of housing booms, including rising housing inequalities for key demographics such as youth, migrants, and peoples of colour, as well as their growing marginalization from asset-based wealth accumulation based on housing. This focus on the consequences of housing booms and policy responses does limit a broader, more complete look at everyday life in gateway locations amid these trends. Nonetheless, one of the most impactful arguments Ley makes throughout the book is how governments’ endorsement of asset-based welfare policies has shaped the timidity of their interventions to cool local housing markets and has resulted in many policy failures (with the exception of Singapore), leading to housing unaffordability and residential alienation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.139 | 0.056 |
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".