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Record W4285055345 · doi:10.1007/978-3-030-98985-9_2

Political Science In, Of, and With Public Health

2022· book-chapter· en· W4285055345 on OpenAlexaff
Patrick Fafard, Adèle Cassola, Isaac Weldon

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsYork UniversityUniversity of Ottawa
Fundersnot available
KeywordsStalematePoliticsPublic healthTypologyPolitical sciencePublic policyPublic administrationSociologyMedicineLaw

Abstract

fetched live from OpenAlex

Abstract There is stalemate of sorts between two views of the place of politics in public health. The public health enterprise is concerned with the ways in which “politics” interferes with the making of public health policy whereas political science sees politics as endemic and something to be better understood. To transcend this stalemate this exploratory essay proposes a typology of the possible interactions between political science and public health: political sciencewithout, in, of,and ideallywithpublic health. Each has different implications for what role political science can play in better understanding the role scientific evidence does and does not play in the making of public health 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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.017
Scholarly communication0.0110.005
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.002

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 head0.071
GPT teacher head0.314
Teacher spread0.243 · 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.

Study designTheoretical or conceptual
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

Citations9
Published2022
Admission routes1
Has abstractyes

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