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Record W2037119928 · doi:10.1177/0162243906296854

The Legitimation and Dissemination Processes of the Innovation System Approach

2007· article· en· W2037119928 on OpenAlexaffabout
Mathieu Albert, Suzanne Laberge

Bibliographic record

VenueScience Technology & Human Values · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicUniversity-Industry-Government Innovation Models
Canadian institutionsUniversité de MontréalUniversity of Toronto
Fundersnot available
KeywordsLegitimationGovernment (linguistics)Public relationsSociologyPrestigePolitical scienceEpistemic communityPublic policyPublic administrationPoliticsLaw

Abstract

fetched live from OpenAlex

A new approach in science policy making named the innovation system (IS) approach has been developed during the past three decades. Its primary goal is to better understand the processes through which scientific knowledge is produced and transferred to businesses to improve their competitiveness and develop national and/or regional economies. This approach has been adopted as an analytical framework and guideline for science policy making by numerous public sector organizations around the world. Using a case study of the Canadian and Québec public sectors, our research seeks to understand why the IS approach has gained the adherence of government employees and how it has been disseminated from international organizations down to regional civil servants. Findings show that adherence to the IS approach stems from the prestige of the Organisation for Economic Cooperation and Development (OECD) and its associated epistemic community, and from the cultural authority science exerts on government employees; these two factors bestow cultural authority onto the IS approach. The perceived scientific validity of the IS approach also leads government employees to consider its underlying economistic worldview as an unquestionable reality.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaScience and technology studies
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptScience and technology studies
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.073
metaresearch head score (Gemma)0.130
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0730.130
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.004
Science and technology studies0.0100.078
Scholarly communication0.0220.021
Open science0.0030.014
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.0070.001

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 head0.019
GPT teacher head0.255
Teacher spread0.237 · 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

Labeled directly by 2 models reading the full record.

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

Citations52
Published2007
Admission routes2
Has abstractyes

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