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Record W7126333370

Interest groups, public opinion, and path dependence: how Canada and the U.S diverged on healthcare policy

2021· other· en· W7126333370 on OpenAlexaboutno aff
Marco Adreyan de Laforcade

Bibliographic record

VenueOpenBU (Boston University) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsStalemateHealth carePublic opinionPoliticsPublic policyDivergence (linguistics)Power (physics)Health care reformHealth policy
DOInot available

Abstract

fetched live from OpenAlex

Despite being comparatively similar countries, the United States and Canada have taken very different historical tracks to developing their respective health care systems. While Canada incrementally developed a system of universal coverage through national public insurance, the United States repeatedly failed to achieve universal healthcare reform and infamously maintains its hybrid public-private system to this day. Scholars of comparative politics have produced numerous competing accounts of the conditions under which health care policy change occurs and explanations for the major factors that shaped policy divergence. However, there are few studies dedicated to explaining mechanisms for continued policy divergence and its impacts on public opinion. In this thesis, I comparatively examine the passage of Medicare in the United States in 1965 with the Canadian Medical Care Act of 1966 and present the results of a nationally representative U.S. public opinion survey. I find that a mechanism of path dependence, whereby interest groups and constituencies that participate in policy battles are strengthened or curtailed by their outcomes, weighed disproportionately on the power of the former in the United States. In Canada, path dependence created a stalemate in which early forms of policy entrepreneurship made healthcare expansion and reduction equally difficult to achieve. The contemporary survey reveals that U.S. public opinion largely favors healthcare reform on matters of principle rather than policy.

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)0.018
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.104
Threshold uncertainty score0.752

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0180.016
Scholarly communication0.0090.004
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.229
Teacher spread0.199 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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