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Record W4412111032 · doi:10.12927/hcpol.2025.27615

Commentary: Risk and Causality: The Contribution of Policy Researchers to Public Decisions

2025· article· en· W4412111032 on OpenAlexaffvenue
Pierre-Gerlier Forest

Bibliographic record

VenueHealthcare policy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsAction (physics)Causality (physics)Context (archaeology)Order (exchange)InstitutionDecision makerPoliticsPositive economicsPublic policyEpistemologyEconomicsSociologyPolitical scienceLaw and economicsLawSocial scienceManagement sciencePhilosophyHistory

Abstract

fetched live from OpenAlex

(Aron 1963: 11). One concerns the risks arising from policy action, or inaction, in a situation or context that is always unique and peculiar, and the other, the uncertainty attached to the results of the action. Greatly simplified, because a decision is rarely made by only one person, outside an institution and the constraints that follow, a decision maker's first order of business is to consider the many consequences that may stem from intervening (or not) to change a situation or solve a problem (Tong 1987). In parallel, the decision maker will want evidence that the measures that are considered can succeed, based on experience or by default, on some plausible "theory" of social action (Edenhofer and Kowarsch 2019).

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)0.004
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0000.000
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 head0.162
GPT teacher head0.532
Teacher spread0.370 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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