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Varieties of Liberalism: Canadian Social Policy from the ‘Golden Age’ to the Present

2008· article· en· W2006720456 on OpenAlexaffabout
Rianne Mahon

Bibliographic record

VenueSocial Policy and Administration · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsLiberalismRestructuringInstitutionalismWelfare stateHistorical institutionalismNew institutionalismPolitical economyPath dependenceState (computer science)Government (linguistics)Social policySociologyWelfarePeriod (music)Political scienceEconomicsLawNeoclassical economicsPolitics

Abstract

fetched live from OpenAlex

Abstract The dominant welfare regimes approach, like the historical‐institutionalism on which it draws, predicts path‐dependent responses to contemporary challenges. According to this, Canada's social policy regime clearly belongs to the (mainly Anglo‐American) ‘liberal’ family, where markets and families retain a key role, supplemented by modest state supports. Yet, as some have recognized, there are important differences among liberal regimes and within a particular welfare regime over time. There are, in other words, ‘varieties of liberalism’. This article argues, moreover, that in the contemporary period Canadian welfare reform has been characterized by warring principles for redesign. While some have sought to deepen the postwar social project, the main trends have been neo‐liberal restructuring and, more recently, policies inspired by ‘inclusive liberalism’, though less deeply than under Blair's government in the UK. The continued existence of such alternatives suggests the need for a more nuanced conception of path‐dependent change, consistent with recent revisionist trends in historical‐institutionalism.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.281
Threshold uncertainty score0.834

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0260.024
Scholarly communication0.0110.002
Open science0.0010.004
Research integrity0.0030.004
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 head0.063
GPT teacher head0.355
Teacher spread0.291 · 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 designQualitative
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

Citations67
Published2008
Admission routes2
Has abstractyes

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