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Record W2395066296 · doi:10.1080/13597566.2016.1181061

Devine intervention? Lessons in systemic retrenchment from Canada’s most generous welfare state

2016· article· en· W2395066296 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRegional & Federal Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsConcordia University
FundersCanada Research Chairs
KeywordsRetrenchmentBureaucracyWelfare stateSocial WelfareWelfareState (computer science)Welfare reformRevenuePolitical scienceEconomicsPublic administrationPolitical economyPoliticsMarket economyLawFinance

Abstract

fetched live from OpenAlex

This article tackles the importance of systemic retrenchment in welfare state research by focusing on two core elements neglected in the literature: the civil service and governmental revenues. Saskatchewan has possessed key ingredients associated with generous welfare states: a dominant left-wing party, a supportive bureaucracy and important non-visible fiscal revenues. According to the comparative welfare state literature, this is also an excellent recipe for maintaining a generous welfare state amid attempts, primarily by right-wing governments, to scale it back. Yet, most social indicators in the post-Devine years demonstrate that Saskatchewan can no longer be considered a leading welfare state in Canada. Reforms to the bureaucracy and a host of financial measures resulting in a near default explain why the Devine government was successful in its efforts to disrupt the CCF/NDP social legacy despite the fact that the NDP regained power for 16 years afterwards.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.063
GPT teacher head0.358
Teacher spread0.296 · 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