Shaping the future of marine socio-ecological systems research: when early-career researchers meet the seniors
Bibliographic record
Abstract
Abstract As the environmental issues facing our planet change, scientific efforts need to inform the sustainable management of marine resources by adopting a socio-ecological systems approach. Taking the symposium on “Understanding marine socio-ecological systems: including the human dimension in Integrated Ecosystem Assessments (MSEAS)” as an opportunity we organized a workshop to foster the dialogue between early and advanced-career researchers and explore the conceptual and methodological challenges marine socio-ecological systems research faces. The discussions focused on: a) interdisciplinary research teams versus interdisciplinary scientists; b) idealism versus pragmatism on dealing with data and conceptual gaps; c) publishing interdisciplinary research. Another major discussion point was the speed at which governance regimes and institutional structures are changing and the role of researchers in keeping up with it. Irrespective of generation, training or nationality, all participants agreed on the need for multi-method approaches that encompass different social, political, ecological and institutional settings, account for complexity and communicate uncertainties. A shift is needed in the questions the marine socio-ecological scientific community addresses, which could happen by drawing on lessons learnt and experiences gained. These require in turn a change in education and training, accompanied by a change in research and educational infrastructures.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.187 | 0.122 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.023 | 0.030 |
| Scholarly communication | 0.045 | 0.032 |
| Open science | 0.004 | 0.031 |
| Research integrity | 0.019 | 0.035 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".