Debtor Assistance and Debt Advice: The Role of the Canadian Credit Counselling Industry
Bibliographic record
Abstract
A continuing theme of our work, and that of others, has been the failure of insolvency law to keep pace with the new problems faced by low-income debtors. Researchers have suggested that the cost of personal bankruptcy puts it beyond the reach of many of those in need of it, though it has proven difficult to demonstrate conclusively that large numbers of low income debtors would take advantage of bankruptcy if the price was lower. In this paper, we analyze another industry — the not-for-profit credit counselling industry — that has grown rapidly in recent years and that offers a different sort of remedy for financial distress. We begin in Section II with a brief history of the credit counseling industry in Canada and in the US. We show how the industry has evolved from a small set of government-subsidized and community-based not-for-profit groups into an industry that is heavily subsidized by credit suppliers and, for the most part, lacking any significant community connection. In Section III, we briefly set out the regulatory framework that seems to encompass credit counselling agencies (“CCA”), both for-profit and not-for-profit. We do not, however, reach any conclusions on the application of this framework to Canadian CCA. Instead, we describe the concepts underlying the framework in a coordinated way. In Section IV, based on a set of "mystery calls" to the largest CCA, we show that most simply have nothing to offer low-income debtors and that most do not do a good job of providing information concerning the alternatives available to them. Rather than introducing substantive legislative or legal rules to help low-income debtors, the Canadian federal government has chosen instead to promote financial education with its 2010 Task Force on Financial Literacy. In Section V, we briefly analyze the Task Force process, suggesting that it largely overlooked the needs of the poor.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.022 | 0.011 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".