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Record W2921726801 · doi:10.2196/11745

Structural Transformation to Attain Responsible BIOSciences (STARBIOS2): Protocol for a Horizon 2020 Funded European Multicenter Project to Promote Responsible Research and Innovation

2019· article· en· W2921726801 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInnovation, Sustainability, Human-Machine Systems
Canadian institutionsnot available
FundersEuropean Commission
KeywordsProtocol (science)Transformation (genetics)Political scienceBusinessPublic relationsKnowledge managementMedicineComputer scienceBiologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Promoting Responsible Research and Innovation (RRI) is a major strategy of the "Science with and for Society" work program of the European Union's Horizon 2020 Framework Programme for Research and Innovation. RRI aims to achieve a better alignment of research and innovation with the values, needs, and expectations of society. The RRI strategy includes the "keys" of public engagement, open access, gender, ethics, and science education. The Structural Transformation to Attain Responsible BIOSciences (STARBIOS2) project promotes RRI in 6 European research institutions and universities from Bulgaria, Germany, Italy, Slovenia, Poland, and the United Kingdom, in partnership with a further 6 institutions from Brazil, Denmark, Italy, South Africa, Sweden, and the United States. OBJECTIVE: The project aims to attain RRI structural change in 6 European institutions by implementing action plans (APs) and developing APs for 3 non-European institutions active in the field of biosciences; use the implementation of APs as a learning process with a view to developing a set of guidelines on the implementation of RRI; and develop a sustainable model for RRI in biosciences. METHODS: The project comprises interrelated research and implementation designed to achieve the aforementioned specific objectives. The project is organized into 6 core work packages and 5 supporting work packages. The core work packages deal with the implementation of institutional APs in 6 European institutions based on the structural change activation model. The supporting work packages include technical assistance, learning process on RRI-oriented structural change, monitoring and assessment, communication and dissemination, and project management. RESULTS: The project is funded by Horizon 2020 and will run for 4 years (May 2016-April 2020). As of June 2018, the initial phase has been completed. The participating institutions have developed and approved APs and commenced their implementation. An observation tool has been launched by the Technical Assistance Team to collect information from the implementation of APs; the Evaluation & Assessment team has started monitoring the advancement of the project. As part of the communication and dissemination strategy, a project website, a Facebook page, and a Twitter account have been launched and are updated periodically. The International Scientific Advisory Committee has been formed to advise on the reporting and dissemination of the project's results. CONCLUSIONS: In the short term, we anticipate that the project will have a considerable impact on the organizational processes and structures, improving the RRI uptake in the participating institutions. In the medium term, we expect to make RRI-oriented organizational change scalable across Europe by developing guidelines on RRI implementation and an RRI model in biosciences. In the long term, we expect that the project would help increase the ability of research institutions to make discoveries and innovations in better alignment with societal needs and values. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11745.

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)0.051
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0510.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.013
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.341
GPT teacher head0.611
Teacher spread0.270 · 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