Forging connections, pursuing social justice: a tribute to Maarten Bavinck’s conceptual and institution-building contributions to maritime studies
Bibliographic record
Abstract
Abstract This paper is written in recognition of the contributions that Maarten Bavinck has made to the field of maritime studies and for the inspiration that he has been for many. It is hard to separate Maarten’s academic and institution-building contributions from his personal qualities, particularly his interest in human relationships. Maarten’s aptitude for building bridges between people, ideas, and institutions has allowed him to connect people in larger knowledge generation and action projects and forge new conceptual bridges. In addition to reflecting shortly on Maarten's key role in establishing the Centre for Maritime Research (MARE) as a institutional anchor in maritime studies, this paper reviews on some of his important and original contributions to four academic domains: legal pluralism, interactive governance, the study of fisheries conflicts, and the environment-development interface. Common threads across these domains include his long-term commitment to meticulous fieldwork in South Asia that grounds his work so firmly, his focus on achieving a more socially just use of marine and coastal resources, and his pragmatic approach that has led to original connections across distinct conceptual and institutional fields.
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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 | 0.021 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.111 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".