MétaCan
Menu
Back to cohort
Record W2614105263 · doi:10.4337/9781784718770.00023

Health policy and territorial politics: disciplinary misunderstandings and directions for research

2018· book-chapter· en· W2614105263 on OpenAlexfundno aff
Scott L. Greer

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2018
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
FundersEuropean CommissionQueen's UniversityMcGill UniversityPrinceton UniversityYale University
KeywordsPoliticsMainstreamFederalismSkepticismComparative politicsPolitical scienceState (computer science)DisciplinePolitical economyPublic administrationSocial scienceSociologyEpistemologyLaw

Abstract

fetched live from OpenAlex

The territorial politics of health is both underexploited by mainstream political scientists and the subject of a large and distinctive health policy literature that rarely connects with political science. This chapter first argues for the usefulness of health as a source of data for a more grounded and policy-focused territorial politics. It then summarizes the health policy approach to territorial politics, arguing that its empirical findings, more than its theories, can enrich political science on the topic. Subsequently, it turns to the findings of political scientists, highlighting the extent to which comparative welfare state literature is skeptical about federalism and could handle it much better, and the extent to which the literature about federalism and health is mostly nationally specific and over-represents North American experiences. The last sections turn to some findings for comparative territorial politics from health policy studies, and some potential future directions for research.

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 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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.228
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.124
GPT teacher head0.388
Teacher spread0.264 · 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 teacher head, not a consensus.

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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueEdward Elgar Publishing eBooksSame topicGlobal Public Health Policies and EpidemiologyFrench-language works237,207