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Cognizance and Consultation of Randomized Controlled Trials among Ministerial Policy Analysts

2012· article· en· W2155294372 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueReview of Policy Research · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversité Laval
FundersCentre Hospitalier Universitaire de QuébecUniversité Laval
KeywordsRandomized controlled trialPolitical scienceRandomized experimentPsychologyPublic relationsPublic administrationMedicine

Abstract

fetched live from OpenAlex

Abstract Consultation of scientific evidence by policy actors has been the foci of attention of knowledge utilization scholars for decades. The present study questioned the extent to which randomized controlled trials ( RCT s)—generally seen as the gold standard of scientific research—are known and consulted by policy analysts in ministerial settings. Using cross‐sectional data collected in 17 ministries in Q uébec ( C anada), our study showed that fairly high levels of policy analysts report never having heard of RCT s, thus possibly hindering effective communication of scientific results to relevant policy makers. Statistical analyses reveal the importance of cognitive factors in explaining both phenomena.

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)0.213
metaresearch head score (Gemma)0.418
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2130.418
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.546
GPT teacher head0.691
Teacher spread0.145 · 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