The US Debtfare State and the Credit Card Industry: Forging Spaces of Dispossession
Bibliographic record
Abstract
Abstract: Credit card debt is a ubiquitous feature of neoliberal capitalism. To explain the notable growth of credit card usage in the US, I adopt a historical materialist approach that employs two key analytical concepts—cannibalistic capitalism and the debtfare state—to capture the material, institutional and ideological dimensions of this process. Viewed within the bounds of cannibalistic capitalism, a mode of accumulation primarily based on the expansion of fictitious capital and secondary forms of exploitation, the debtfare state enhances the social power of money by allowing major credit card issuers (banks) to generate high levels of income from uncapped interest rates and policies that ensure the extension of plastic money to those who fall within Marx's category of the surplus population. While the expansion of debt subjects surplus workers to the disciplinary requirements of the market, it is unable to suspend the main tensions of cannibalistic capitalism, prompting ongoing reconstructions of the debtfare state.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".