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Record W2076567773 · doi:10.1177/0010414002035006004

Ideas and the Welfare State

2002· article· en· W2076567773 on OpenAlexaffabout
Linda A. White

Bibliographic record

VenueComparative Political Studies · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNormativeInstitutionalisationGovernment (linguistics)Public policyWelfare stateState (computer science)WelfarePopulationPolitical sciencePublic economicsPublic administrationEconomic growthEconomicsPolitical economyDevelopment economicsSociologyPoliticsLaw

Abstract

fetched live from OpenAlex

This article examines the legacy of American and Canadian welfare state development to explain surprisingly comparable levels of child care provision. It highlights the ironies of policy history while demonstrating the importance of ideas as independent causal factors in the development of public policies and the effect of their institutionalization on future policy development. Maternalist, nativist, and eugencist imperatives led U.S. governments to intrude in areas normally considered part of the private sphere and led to the adoption of policies to respond to a perceived decline primarily of the White population. These policies provided a normative and institutional basis for future government involvement in child care funding and programs, even after the conditions that led to the original policies changed. In Canada, the lack of large-scale entrenchment of similar ideas constrained an otherwise more interventionist government and made it more difficult for child care policies to find governmental and societal acceptance.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.231
Threshold uncertainty score0.459

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0110.038
Scholarly communication0.0080.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.210
GPT teacher head0.439
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations36
Published2002
Admission routes2
Has abstractyes

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