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Record W4410232359 · doi:10.3138/cpp.2024-041

Tilting the Playing Field Away from the Discharge of Debts: The Case of Consumer Proposals in Canada

2025· article· en· W4410232359 on OpenAlexaffvenueabout
Saul Schwartz, Stephanie Ben‐Ishai

Bibliographic record

VenueCanadian Public Policy · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCredit Risk and Financial Regulations
Canadian institutionsYork UniversityCarleton University
Fundersnot available
KeywordsField (mathematics)DebtArtAdvertisingBusinessFinanceMathematics

Abstract

fetched live from OpenAlex

We examine the increasing prevalence of consumer proposals as a debt relief option in Canada, highlighting the shift in insolvency regulation toward creditor interests and the implications of this for debtors. Canada has two federally regulated debt relief options. One is bankruptcy, which generally offers the discharge of most debts after nine months but requires that large assets, such as homes and cars, be sold for the benefit of creditors. The other is the consumer proposal, which protects large assets (e.g., homes and vehicles) but requires monthly payments for 60 months before any debt is forgiven. Consumer proposals have become significantly more common over time, rising from 23 percent of consumer insolvencies in 2009 to 79 percent in 2024. Using the Oaxaca–Blinder decomposition and data on the universe of insolvencies in 2011 and 2019, we show that changes in the average characteristics of the debtors—debts, assets, and income—do not account for this increase. Instead, unobservable factors are at the root of the increase. We hypothesize that it is the behaviour of those who benefit financially from the increase—the licensed insolvency trustees who administer the procedures and the large creditors—that is the most likely unobserved influence.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.227
Teacher spread0.207 · 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 teacher head, 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
Published2025
Admission routes3
Has abstractyes

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