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The Fiscalization of Social Policy

2018· book· en· W2804257114 on OpenAlexaboutno aff
Joshua T. McCabe

Bibliographic record

VenueOxford University Press eBooks · 2018
Typebook
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTax creditDistribution (mathematics)Tax reformDirect taxEconomicsIndirect taxPublic economicsAusterityAd valorem taxPoliticsValue-added taxExceptionalismPolitical sciencePolitical economyLaw

Abstract

fetched live from OpenAlex

This book challenges the conventional wisdom on American exceptionalism, offering the first and only comparative analysis of the politics of child and in-work tax credits. This comparative approach, analyzing the US, Canada, and the UK, upends everything we thought we knew about the politics of tax credits, accounting for both the timing of their development and the distribution of their benefits among families across liberal welfare regimes. Rather than attributing these changes to antiwelfare attitudes, mobilization of conservative forces, shifts toward workfare, or racial antagonism, the book argues that the growing use of tax credits for social policy was a strategic adaptation to austerity in all three countries but that the historical absence of family allowances in the US left the country with a policy legacy that institutionalized a distinct “logic of tax relief,” ensuring that the poorest American families would be ineligible for tax credits. Focusing on the twin puzzles of the growth and distribution of new tax credits across the three countries, the book explains both their convergence on the use of these tax credits and the US’ divergence from the UK and Canada on the distribution of these tax credits’ 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.908
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.282
Teacher spread0.255 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations17
Published2018
Admission routes1
Has abstractyes

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