Ethical reflections on the COVID-19 pandemic in the global seafood industry: navigating diverse scales and contexts of marine values and identities
Bibliographic record
Abstract
Abstract The global crisis instantiated by the COVID-19 pandemic opens a unique governance window to transform the sustainability, resilience, and ethics of the global seafood industry. Simultaneously crippling public health, civil liberties, and national economies, the global pandemic has exposed the diverse values and identities of actors upon which global food systems pivot, as well as their interconnectivity with other economic sectors and spheres of human activity. In the wake of COVID-19, ethics offers a timely conceptual reframing and methodological approach to navigate these diverse values and identities and to reconcile their ensuing policy trade-offs and conflicts. Values and identities denote complex concepts and realities, characterized by plurality, fluidity and dynamics, ambiguity, and implicitness, which often hamper responsive policy-setting and effective governance. Rather than adopt a static characterization of specific value or identity types, I introduce a novel hierarchical conceptualization of values and identities made salient by scale and context. I illustrate how salient values and identities emerge at multiple scales through three seafood COVID-19 contextual examples in India, Canada, and New Zealand, where diverse seafood actors interact within local, domestic (regional/national), and global seafood value chains, respectively. These examples highlight the differential values and identities, and hence differential vulnerabilities, resilience, and impacts on seafood actors with the COVID-19 pandemic, which necessitate differentiated policy interventions if they are to be responsive to those affected. An ethical governance framework that integrates diverse marine values and identities, buttressed by concrete deliberation and decision-support protocols and tools, can transform the modus operandi of global seafood systems toward both sustainable and ethical development.
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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.086 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".