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Record W3174223238 · doi:10.3389/fmars.2021.662350

A Decade of Incorporating Social Sciences in the Integrated Marine Biosphere Research Project (IMBeR): Much Done, Much to Do?

2021· article· en· W3174223238 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

VenueFrontiers in Marine Science · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans CanadaInstitute for Marine Biosciences
FundersNatural Environment Research CouncilSight Research UKNational Science Foundation
KeywordsBiosphereOceanographyEnvironmental resource managementEnvironmental scienceGeographyEcologyBiologyGeology

Abstract

fetched live from OpenAlex

Successful management and mitigation of marine challenges depends on cooperation and knowledge sharing which often occurs across culturally diverse geographic regions. Global ocean science collaboration is therefore essential for developing global solutions. Building effective global research networks that can enable collaboration also need to ensure inter- and transdisciplinary research approaches to tackle complex marine socio-ecological challenges. To understand the contribution of interdisciplinary global research networks to solving these complex challenges, we use the Integrated Marine Biosphere Research (IMBeR) project as a case study. We investigated the diversity and characteristics of 1,827 scientists from 11 global regions who were attendees at different IMBeR global science engagement opportunities since 2009. We also determined the role of social science engagement in natural science based regional programmes (using key informants) and identified the potential for enhanced collaboration in the future. Event attendees were predominantly from western Europe, North America, and East Asia. But overall, in the global network, there was growing participation by females, students and early career researchers, and social scientists, thus assisting in moving toward interdisciplinarity in IMBeR research. The mainly natural science oriented regional programmes showed mixed success in engaging and collaborating with social scientists. This was mostly attributed to the largely natural science (i.e., biological, physical) goals and agendas of the programmes, and the lack of institutional support and push to initiate connections with social science. Recognising that social science research may not be relevant to all the aims and activities of all regional programmes, all researchers however, recognised the (potential) benefits of interdisciplinarity, which included broadening scientists’ understanding and perspectives, developing connections and interlinkages, and making science more useful. Pathways to achieve progress in regional programmes fell into four groups: specific funding, events to come together, within-programme-reflections, and social science champions. Future research programmes should have a strategic plan to be truly interdisciplinary, engaging natural and social sciences, as well as aiding early career professionals to actively engage in such programmes.

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)0.033
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.046
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0040.004
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 head0.132
GPT teacher head0.476
Teacher spread0.343 · 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