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Record W2346069715

Navigating Towards Shared Responsibility in Research and Innovation: Approach, Process and Results of the Res-AGorA Project

2016· book· en· W2346069715 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.

Bibliographic record

VenueFraunhofer-Publica (Fraunhofer-Gesellschaft) · 2016
Typebook
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsAgoraStakeholderResponsible Research and InnovationStakeholder engagementProcess (computing)Process managementKnowledge managementConceptual frameworkBusinessPolitical scienceEngineeringEngineering ethicsSociologyComputer sciencePublic relations
DOInot available

Abstract

fetched live from OpenAlex

The Res-AGorA project Res-AGorA was a three-year, EU FP7 project (2013–2016) which has co-constructed a good-practice framework, the “Responsibility Navigator”, with practitioners and strategic decision makers. This framework facilitates reflective processes involving multiple stakeholders and policy-makers with the generic aim of making European research and innovation more responsible, responsive, and sustainable. This framework was developed based on three years of intensive empirical research comprising an extensive programme of in-depth case-studies, systematic “scientometric” literature analysis, country-level monitoring (RRI-Trends) and five broadbased co-construction stakeholder workshops. The resulting Res-AGorA Responsibility Navigator was conceived as a means to provide orientation without normatively steering research and innovation in a specific direction. Furthermore, Res-AGorA’s “Co-construction Method” is a collaborative methodology designed to systematically support and facilitate the practical use of the Responsibility Navigator with stakeholders. The Responsibility Navigator, the Co-construction Method and accompanying materials areready to use by actors who wish to navigate Research and Innovation towards Responsible Research and Innovation. This book provides an overview of the project’s journey, its conceptual underpinnings and main results.

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)0.041
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.345
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0410.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.010
Science and technology studies0.0020.007
Scholarly communication0.0010.001
Open science0.0040.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0000.000

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 head0.298
GPT teacher head0.512
Teacher spread0.213 · 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