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Record W4409459857 · doi:10.1080/19491247.2025.2482229

Canadian community land trusts through a comparative institutionalist lens: continued liberalization, or welfare partnership revisited?

2025· article· en· W4409459857 on OpenAlexaboutno aff
Jason S. Spicer, Mia Trana

Bibliographic record

VenueInternational Journal of Housing Policy · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipWelfareLiberalizationThrough-the-lens meteringEconomicsBusinessLens (geology)Market economyFinanceBiology

Abstract

fetched live from OpenAlex

The community land trust (CLT), a non-profit organisational model created in the U.S. primarily to enable community control of affordable housing, has since spread to other countries, including Canada. What differences exist, if any, between CLTs in these two ‘most similar’ countries? Based on statistical analysis of the results of comprehensive bi-national CLT surveys, we identify five differences, with Canadian CLTs comparatively younger, larger and greater in number per capita, more reliant on government than non-governmental/philanthropic funding, more reliant on unpaid/volunteer labour, and more associated with tenure forms which do not directly enable individual household wealth creation, such as zero-equity co-operatives and rental units. Deploying various comparative institutionalist frameworks, we suggest Canadian CLTs have evolved in a manner congruent with the historically distinctive features of its social welfare and housing regimes, which persist in maintaining institutional arrangements that differ from the U.S., marked by reduced liberalisation and enhanced social welfare partnerships.

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)0.004
metaresearch head score (Gemma)0.012
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 score0.135
Threshold uncertainty score0.981

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0110.016
Scholarly communication0.0090.005
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.084
GPT teacher head0.331
Teacher spread0.246 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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