Collapse and recovery of seafood wholesale prices in time of COVID‐19
Bibliographic record
Abstract
Abstract The COVID‐19 pandemic has spread around the world, disrupting economies, societies and daily life. Early research anticipated significant negative impacts for the globalized seafood supply network. Here, we explore the impact of the COVID‐19 pandemic on wholesale prices from five major seafood markets around the world. An anomalies analysis was used to establish a 5‐year baseline price for each commodity. Daily price data from 2020 were compared to the baseline to identify collapses (>1.96 SE from baseline) and analyse collapse characteristics (timing, duration and magnitude). Non‐uniform price collapses were observed across, and within, the markets analysed. Toyosu (Tokyo) Market experienced price collapses to 51% of commodities, Rungis (Paris) 36%, Mercamadrid (Madrid) 19%, Mercado La Nueva Viga (Mexico City) 35% and the Portland Fish Exchange (Portland, Maine) 32%. Collapse magnitude varied from 11% to 79% of the 5‐year average price. Average collapse duration ranged from 13 to 24 weeks with some commodities (4%–22%) remaining collapsed at the end of 2020. For markets where volume data were available, collapses were also noted (59% of commodities in Toyosu, 10% in Mercamadrid and 19% in Portland Fish Exchange); in these cases, the volume collapse was more severe than the related price collapse. To better detect, anticipate and respond to future shocks, we recommend that relevant government agencies conduct comprehensive economic reviews of the COVID‐19 pandemic throughout the seafood supply chain, including the outcomes of emergency measures, short‐ and long‐term implications of market volatility and identify areas of supply and labour vulnerabilities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".