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Record W7099806266

Prepared for

2014· article· en· W7099806266 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsCorporationVariety (cybernetics)PopulationRentingQuality (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

CMHC offers a wide variety of housing-related information. For details, call 1 800 666-2642 or visit our Web site at www.cmhc-schl.gc.ca Cette publication est aussi disponible en français sous le titre: , PF 2 This research project was (partially) funded by Canada Mortgage and Housing Corporation ("CMHC"). The contents, view, and editorial quality of this report are the responsibility of the author(s) and CMHC accepts no responsibility for them or any consequence arising from the reader's use of the information, materials, and techniques described herein. PREFACE Between the early 1980s and the mid-1990s, the situation facing renters in Canada changed. The demography of Canada's population changed, the economy went through boom, bust, and much restructuring, and changes in spending by governments on social programs forced some renters (not to mention homeowners) to make difficult choices. This report assembles compara-ble data on the change in condition of renter households between the early 1980s and mid 1990s. The first part of the report describes how the circumstances of Canadian renters changed over

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.091
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0050.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.9090.779

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 head0.030
GPT teacher head0.223
Teacher spread0.192 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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