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Record W2523073545

Mandatory Financial Education as Prerequisite to Personal Insolvency Relief: The North American Experience

2016· article· en· W2523073545 on OpenAlexaboutno aff
Jason J. Kilborn

Bibliographic record

VenueSSRN Electronic Journal · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBankruptcyMandateInsolvencyFinancial distressFinanceEmpirical evidenceBusinessGoing concernFinancial managementEconomicsActuarial scienceAccountingPolitical scienceFinancial systemAuditLaw
DOInot available

Abstract

fetched live from OpenAlex

This chapter from a forthcoming volume on prevention of overindebtedness explores mandatory financial education in consumer bankruptcy. Requiring individual debtors to undergo such counseling or education as a prerequisite to discharge relief is a seemingly sound idea in a vain search for compelling theoretical and empirical support. The North American experience provides neither. Canada since 1992 and the United States since 2005 have both required individual debtors to receive financial management counseling or training pre-discharge, even though available evidence of the causes of consumer bankruptcy and evaluations of the education provided strongly suggest that this mandate is not filling a real need. Sound theory and reliable evidence strongly suggest that it is unjustified to mandate financial management training for those seeking relief from personal financial distress, which results most often from unforeseen accidents of life, not lack of basic financial knowledge or mismanagement. The ultimate question is whether the significant costs of mandating financial education are justified by its limited and likely illusory benefits.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.005
GPT teacher head0.228
Teacher spread0.223 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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