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Record W7042938790

Restriction on Foreign Buyers and Investment in Vancouver Additional property transfer tax and its impact on foreign buyer and housing market

2017· other· en· W7042938790 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2017
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsInvestment (military)Foreign direct investmentProperty (philosophy)Transfer (computing)Property market
DOInot available

Abstract

fetched live from OpenAlex

The paper examines housing market trend, and home buying activities of Chinese buyers in Greater Vancouver, by focusing on the few months before and after the introduction of additional foreign property tax for foreign buyers (APTT). Employing regional housing data and interviews, the study identifies the characteristics of Chinese buyers’ home buying activities and their reaction towards APTT. And whether and how this policy affects housing market is also explored. It is found that the shrink of foreign buyers in Greater Vancouver is more associated with the cooling down of single family housing market than townhouse or apartment. However, the fairness APTT is questioned by interviewees, because of the latent racism under this policy. And it also fails to restrict all the actors who engage in housing speculation. The study concludes that APTT has a short term influence on foreign buyers as well as housing market, and modifying and improving the policy is necessary for better control housing speculation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0280.002

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.

Opus teacher head0.025
GPT teacher head0.213
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractno

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