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Record W4232453526 · doi:10.3138/9781442609730

Welfare Reform in Canada

2015· book· en· W4232453526 on OpenAlexaboutno aff
Daniel Béland, Pierre‐Marc Daigneault

Bibliographic record

VenueUniversity of Toronto Press eBooks · 2015
Typebook
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsWelfareWelfare reformPolitical scienceLaw

Abstract

fetched live from OpenAlex

Welfare Reform in Canada provides systematic knowledge of Canadian social assistance by assessing provincial welfare regimes and emphasizing changes since the late twentieth century. The book examines activation, social investment, and economic inequalities and provides nuanced perspectives on social welfare across Canada's provinces in relation to trends and issues in the country and beyond. These conceptual, international, and historical perspectives inform in-depth case studies of social assistance reform in each province. The key issues of social assistance in Canada, including gender relations, immigrants, Aboriginal peoples, and the impact of activation programs, are addressed, as is the possibility of convergence taking place in provincial welfare policy. This book is the second volume in the Johnson-Shoyama Series on Public Policy, published by the University of Toronto Press in association with the Johnson-Shoyama Graduate School of Public Policy, an interdisciplinary centre for research, teaching, and executive training with campuses at the Universities of Regina and Saskatchewan

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.190
Threshold uncertainty score0.940

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0200.004
Scholarly communication0.0090.002
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0310.002

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 head0.019
GPT teacher head0.213
Teacher spread0.194 · 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 designNot applicable
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

Citations25
Published2015
Admission routes1
Has abstractno

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