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Record W3084537780

Exploring the Trajectory of Housing Assistance Policies in Canada

2020· article· en· W3084537780 on OpenAlexvenueaboutno aff
Jon Careless

Bibliographic record

VenueAlternate routes · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsTrajectoryBusinessPhysics
DOInot available

Abstract

fetched live from OpenAlex

This article explores the degree to which changes in housing assistance policies (HAPs) reflect the structural shift from the welfare state era towards neoliberalism and financialization, as opposed to efforts concerning the right to shelter that have emerged in Canada between the mid-twentieth century and the housing surge of the 1990s and early-to-mid 2000s. My central argument is that the HAPs instituted by the Canadian state during the welfare state era were shown to garner limited legitimacy among policy-makers and served as an effective scapegoat for a state that came to shift the goals of HAPs towards purposes more explicitly associated with neoliberalism and financialization. To support this argument, I make the following claims that are informed by my empirical findings. Firstly, I show how Canada’s transition from the pre-1980s welfare state era into the contemporary epoch of neoliberalism and financialization saw the state largely withdraw from providing HAPs in the form of public assistance. The twenty first century brought drastic cutbacks to social housing support through public resources. At the same time, I explain that HAP policies were diverted to ramp up the demand for homeownership and access to mortgages which primarily benefited lenders

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0050.002
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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.

Opus teacher head0.087
GPT teacher head0.215
Teacher spread0.129 · 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 designQualitative
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

Citations3
Published2020
Admission routes2
Has abstractno

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