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Record W2547600055 · doi:10.1080/09654313.2016.1244516

A review of (almost) 20 years of regional innovation systems research

2016· review· en· W2547600055 on OpenAlexafffund
David Doloreux, Igone Porto Gómez

Bibliographic record

VenueEuropean Planning Studies · 2016
Typereview
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsHEC Montréal
FundersSocial Sciences and Humanities Research Council of CanadaNorges Forskningsråd
KeywordsRegional scienceField (mathematics)Work (physics)Regional innovation systemPolitical scienceSociologyEngineering

Abstract

fetched live from OpenAlex

The literature on regional innovation systems (RISs) has grown impressively in the last two decades. The objective of this study is to provide a comprehensive assessment of all RIS articles published in scholarly journals between 1998 and 2015. It aims to inform researchers of the empirical results obtained so far and highlight areas that need further work. This review describes how the RIS field has developed, charts the current body of RIS research and discusses recommendations for moving the RIS field forward.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0090.017
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.583
GPT teacher head0.565
Teacher spread0.018 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
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

Citations113
Published2016
Admission routes2
Has abstractyes

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