Exploring the Blue Economy Nexus: Government, Industry, and Market’s Perspectives on Seafood
Bibliographic record
Abstract
Seafood plays a pivotal role in global economies, livelihoods, and nutritional security. However, climate change and global pandemics pose significant threats to seafood harvests, production, supply chains, and marketing channels. The focus of my thesis is to understand the impact of external factors on our seafood resources and explore adaptive strategies in the face of uncertainties. We utilize economics techniques to study human-nature systems by zooming into social elements (government agencies, industry stakeholders, and fish farmers/fishermen) and aquatic resources. The three essays of my thesis delve into this inquiry from the perspectives of government, industry, and market, accordingly.The first chapter in my thesis, <i>Climate Change and Snow Crab Harvest - Applying Random Effect Estimators with Instrumental Variable</i>, estimates the snow crab harvest function with unbalanced panel data of eastern Bering Sea snow crab, Canadian snow crab, Japanese snow crab, and Barents Sea snow crab. Specifically, we analyze the relationship between snow crab biomass, stock, and catch. To address the endogeneity of stock in the harvest function, climate change indicators are selected as instrumental variables. We identify that the Arctic Sea ice extent is effective in addressing the endogeneity and the random effects instrumental variable model with error components two stage least squares estimator performs the best to control heterogeneity. We find that a 1% increase in snow crab fishing effort is associated with a 0.42% increase in snow crab harvest, and a 1% increase in snow crab stock causes a 0.98% increase in snow crab harvest. The reported estimates indicate a large stock-harvest elasticity and provide supporting evidence for government fishery agencies to prioritize stock enhancement in policy designs.The second chapter, <i>Online Media Sentiment Analysis of Shrimp and Salmon in the United States</i>, employs online media analytics on shrimp and salmon in the US to provide insights into consumer perceptions and potential demand signals for seafood. Search hits and mentions are quantified for top sources, domains, and prevalent terms. In addition, sentiment drivers and sentiment values are identified and calculated using natural language processing tools. The results reveal that the occurrence of peak mentions does not necessarily coincide with the peak of net sentiment, and farmed seafood consistently exhibits lower net sentiments compared to their wild counterparts. Autoregressive modeling is conducted to predict the dynamics of seafood’s net sentiments. The regional analysis demonstrates that public attitudes toward both farmed shrimp and salmon in the East North Central region exhibit a more positive net sentiment, while the New England and Middle Atlantic regions tend to have a lower net sentiment for farmed shrimp and salmon, respectively. The fitted forecast model serves as a supplementary tool for industry stakeholders to quickly respond to future public perceptions. Regional statistics also help the seafood industry tailor business strategies to different regions.In the third chapter, <i>Comparative Case Study of Small-Scale Fish Processing for Local Seafood Supply</i><i>,</i> we examine the feasibility of utilizing a shared-use commercial kitchen and on-farm kitchen to support small-scale local fish processing, which helps diversify marketing channels in the US Midwest and supply seafood to local food systems. A case study of each facility type is assessed for economic viability for fish farmers. The financial analysis suggests farmers interested in processing tilapia or rainbow trout from 2,500 lbs to 5,000 lbs per year utilize rental commercial kitchens. A minimum of 15% markup and processing of 10,000 lbs/year tilapia is required to make the on-farm kitchen option more viable. For farmers who process rainbow trout, 10,000 lbs/year with a 10% markup using an on-farm kitchen is a better choice. Factoring in the stochastic variability of raw product prices, rental rates, and set-up costs, we provide simulated ranges for economic metrics including profitability index, payback period, and net present values. The reports of estimated costs, revenues, and breakeven prices, provide fish farmers with suggested selling prices, kitchen choices, and production levels to achieve optimum profits under risks.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".