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Record W2142374214 · doi:10.1177/1075547001022004003

Climbing the Ladder of Research Utilization

2001· article· en· W2142374214 on OpenAlexaff
Réjean Landry, Nabil Amara, Моктар Ламари

Bibliographic record

VenueScience Communication · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsClimbingClimbTransmission (telecommunications)Stage (stratigraphy)Knowledge managementComputer scienceEngineeringBiologyTelecommunicationsEcology

Abstract

fetched live from OpenAlex

In this article, the Knott and Wildavsky stages of knowledge utilization are considered separately and compared with the previous stage to find factors explaining why researchers are able to climb up the ladder of knowledge utilization from the echelon of no transmission to transmission, then to cognition, reference, effort, influence, and application. The results suggest that there are barriers to climbing and that these barriers are primarily located between the stage of no transmission and the stage of transmission. These results carry theoretical and policy implications that are explored in the last part of the article.

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)0.019
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.077
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.005
Science and technology studies0.0070.008
Scholarly communication0.0130.015
Open science0.0020.012
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.841
GPT teacher head0.702
Teacher spread0.139 · 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
DomainMethods
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

Citations269
Published2001
Admission routes1
Has abstractyes

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