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Record W4387878009 · doi:10.1080/01442872.2023.2271417

Assessing policy transfer from the United States to the British National Health Service

2023· article· en· W4387878009 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.

Bibliographic record

VenuePolicy Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsAmericanizationPolicy transferRelevance (law)Health policyService (business)Policy analysisPublic administrationSociologyNational PolicyPolitical scienceHealth carePublic economicsEconomicsLawEconomy

Abstract

fetched live from OpenAlex

Much has been written about the claim that the British National Health Service (NHS) is becoming more like the US health care system, something a number of commentators view as a form of "Americanization".Yet, that term is imprecise and unhelpful for rigorous analysis of what has, and has not, happened.This paper uses the lens of policy transfer to explore this issue, which provides a sharper insight into policy development.The paper examines the relevance of the Dolowitz and Marsh framework for the study of policy transfer from the US to the British NHS from 1979 onwards.In terms of the framework's main research questions, the discussion of the potential US influence on the NHS case stresses the role of policy entrepreneurs in policy transfer.In terms of policy success, however, commentators suggest a mix of uninformed, incomplete, or inappropriate transfer.We conclude that Dolowitz and Marsh do provide a useful framework that asks relevant questions about policy transfer, which provides a more nuanced account of policy transfer from the US to the NHS than the crude term "Americanization".

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0050.000
Scholarly communication0.0010.000
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 head0.185
GPT teacher head0.481
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