Giving Credit where it's Due: Public Policy and Household Debt in the United States, the United Kingdom and Canada
Bibliographic record
Abstract
Abstract The dominant account of rising household indebtedness in the United States, the United Kingdom and Canada claims that current economic stimuli, namely low nominal interest rates and rising property markets, are the key reasons debt has grown so rapidly since the mid-1990s. By drawing on key theoretical assumptions from neoclassical economics, policy makers have argued that rising debt levels since the mid-1990s shows that households are rational agents taking advantage of cheaper credit to purchase assets; thus, the equilibrating effect of market society translates into a balance between rising debt and rising assets. This article puts forward an alternative framework for evaluating potential contributing factors of rising household indebtedness in the United States, the United Kingdom and Canada by evaluating the long-term impacts of policies implemented to achieve non-inflationary growth. Using a neo-Gramscian method of analysing historical structures, it is argued that growing household indebtedness was not an inevitable outcome of the policy of non-inflationary growth. Instead, it was most likely a product of a confluence of forces as rising demand for credit by households (due to downward pressure on wages) combined with increased supply of credit (as banks sought profitable returns in a liberalised market) to generate indebtedness. By locating the specific policy processes that contributed to mass household indebtedness this article tries to more accurately understand the origins and effects of politically-led structural change.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".