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Social Policy Preferences in Canada

2025· book-chapter· en· W4409694532 on OpenAlexaffabout
Sophie Borwein, Michael Donnelly, Tyler Romualdi

Bibliographic record

VenueOxford University Press eBooks · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsWestern UniversityUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Abstract This chapter provides a comprehensive account of trends in public opinion toward social policy in Canada over time. Leveraging a unique dataset encompassing every social policy question asked in Gallup Canada polls and the Canadian Election Study from 1971 to 2021, the following descriptive analyses uncover several key insights. First, with the exception of Quebec, this chapter finds either overtime stability or a slow leftward shift in Canadian attitudes, depending on the province. Second, many differences between groups—including between the provinces and between men and women—have remained largely consistent over time, though young men, in particular, have become relatively more conservative than middle-aged and older women, who have become relatively more progressive. The chapter finds the most evidence of divergence among voters for the New Democrats and Liberals, on the one hand, and the Conservatives, on the other. Finally, the results indicate the short-term responsiveness of Canadians’ preferences to economic conditions, with support for the welfare state decreasing during economic downturns.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.088
Threshold uncertainty score0.639

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.009
Science and technology studies0.0060.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.001

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 head0.039
GPT teacher head0.267
Teacher spread0.228 · 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 designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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