The Fiscalization of Social Policy: How Taxpayers Trumped Children in the Fight Against Child Poverty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Fiscalization of Social Policy offers a comparative-historical perspective on the growing use of tax expenditures for social policy purposes. McCabe primarily focuses on the policymaking experiences of the United States, Canada, and the United Kingdom, tracing differences in policy legacies to explain why the U.S., unlike its liberal counterparts, has not expanded its version of a child tax credit (CTC) to non-working families. The two puzzles underlying the basis of McCabe’s investigation make it clear why researchers of poverty and social policy ought to engage with the book’s arguments. McCabe first considers how we should understand the increasing fiscalization of welfare state expenditures. Second, he questions why CTCs in the U.S. are targeted at working families, whereas Canada and the UK have extended their tax credits to non-working families. In explaining the rise of fiscalization, McCabe convincingly points to convenient obfuscation strategies that have allowed policymakers to conceal the real costs of tax-based expansion. Policymakers across the liberal countries were able to classify tax expenditures as “revenues not collected” rather than typical social transfer expenditures. This practice served dual purposes: governments could signal to financial overseers that they were serious about cutting costs, while at the same time expanding benefits for their constituents.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it