MétaCan
Menu
Back to cohort
Record W4312474492 · doi:10.2139/ssrn.4244579

A Science of Actionable Knowledge Research Agenda: Drawing from a Review of the Most Misguided to the Most Enlightened Claims in the Science-Policy Interface Literature

2022· review· en· W4312474492 on OpenAlexaff
Kripa Jagannathan, Geniffer Emmanuel, James Arnott, Katharine J. Mach, Aparna Bamzai‐Dodson, Kristen A. Goodrich, Ryan Myer, Mark W. Neff, Kathryn Dana Sjostrom, Kristin Timm, Esther Turnhout, Gabrielle Wong‐Parodi, Angela Bednarek, Alison M. Meadow, Art Dewulf, Christine Kirchhoff, R. W. Moss, Leah Nichols, Eliza Oldach, Maria Carmen Lemos, Nicole Klenk

Bibliographic record

VenueSSRN Electronic Journal · 2022
Typereview
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsScience policyInterface (matter)Political scienceData scienceEngineering ethicsEpistemologyKnowledge managementComputer sciencePublic administrationEngineeringPhilosophy

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.050
metaresearch head score (Gemma)0.123
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0500.123
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0260.028
Science and technology studies0.0020.011
Scholarly communication0.0150.021
Open science0.0030.006
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0020.001

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 head0.253
GPT teacher head0.518
Teacher spread0.265 · 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 designSystematic review
DomainMethods
GenreReview

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
Published2022
Admission routes1
Has abstractno

Explore more

Same venueSSRN Electronic JournalSame topicComplex Systems and Decision MakingFrench-language works237,207