Application of a translational research model to assess the progress of occupational safety research in the international commercial fishing industry

2014 ◽  
Vol 64 ◽  
pp. 71-81 ◽  
Author(s):  
Devin L. Lucas ◽  
Laurel D. Kincl ◽  
Viktor E. Bovbjerg ◽  
Jennifer M. Lincoln
Keyword(s):  
Translational Research ◽  
Occupational Safety ◽  
Commercial Fishing ◽  
Fishing Industry ◽  
Research Model ◽  
Safety Research

scholarly journals Application of Data Linkage Techniques to Pacific Northwest Commercial Fishing Injury and Fatality Data 

2021 ◽  
Author(s):  
Jasmine Nahorniak ◽  
Viktor Bovbjerg ◽  
Samantha Case ◽  
Laurel Kincl
Keyword(s):  
Pacific Northwest ◽  
Occupational Safety ◽  
Data Linkage ◽  
Trauma Registry ◽  
The United States ◽  
Commercial Fishing ◽  
Bayes Classifier ◽  
Safety Research ◽  
Linkage Methods ◽  
Nonfatal Injuries

Abstract BackgroundCommercial fishing consistently has among the highest workforce injury and fatality rates in the United States. Data related to commercial fishing incidents are routinely collected by multiple organizations which do not currently coordinate or automatically link data. Each dataset has the potential to generate a more complete picture to inform prevention efforts. Our objective was to examine the utility of using statistical data linkage methods to link these datasets in support of incident surveillance and hazard assessment in the commercial fishing industry.MethodsIn this feasibility study, we identified true matches and discrepancies between de-identified datasets using the Python Record Linkage Toolkit. Four commercial fishing datasets from Oregon and Washington were linked: the Commercial Fishing Incident Database, the Vessel Casualty Database, the Nonfatal Injuries Database, and the Oregon Trauma Registry. The datasets each covered different date ranges within 2000 - 2017, containing 458, 524, 184, and 11 cases respectively. Several data linkage classifiers were evaluated.ResultsThe Naïve-Bayes classifier returned the highest number of true matches between these small datasets. A total of 41 true matches and 8 close matches were identified, of which 29 were determined to be duplicates. In addition, linkage highlighted 4 records that were not commercial fishing cases from Oregon and Washington. The optimum match parameters were the date, state, vessel official number, and number of people on board.ConclusionsStatistical data linkage enables accurate, routine matching for small de-identified injury and fatality datasets such as those in commercial fishing. It provides information needed to improve the accuracy of existing data records. It also enables expanding and sharpening details of individual incidents in support of occupational safety research.

scholarly journals Application of data linkage techniques to Pacific Northwest commercial fishing injury and fatality data

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jasmine Nahorniak ◽  
Viktor Bovbjerg ◽  
Samantha Case ◽  
Laurel Kincl
Keyword(s):  
Pacific Northwest ◽  
Occupational Safety ◽  
Statistical Data ◽  
Data Linkage ◽  
The United States ◽  
Commercial Fishing ◽  
Small Data ◽  
Data Sets ◽  
Data Set ◽  
Safety Research

Abstract Background Commercial fishing consistently has among the highest workforce injury and fatality rates in the United States. Data related to commercial fishing incidents are routinely collected by multiple organizations which do not currently coordinate or automatically link data. Each data set has the potential to generate a more complete picture to inform prevention efforts. Our objective was to examine the utility of using statistical data linkage methods to link commercial fishing incident data when personally identifiable information is not available. Methods In this feasibility study, we identified true matches and discrepancies between de-identified data sets using the Python Record Linkage Toolkit. Four commercial fishing data sets from Oregon and Washington were linked: the Commercial Fishing Incident Database, the Vessel Casualty Database, the Nonfatal Injuries Database, and the Oregon Trauma Registry. The data sets each covered different date ranges within 2000–2017, containing 458, 524, 184, and 11 cases respectively. Several data linkage classifiers were evaluated. Results The Naïve-Bayes classifier returned the highest number of true matches between these small data sets. A total of 41 true matches and 8 close matches were identified, of which 29 were determined to be duplicates. In addition, linkage highlighted 4 records that were not commercial fishing cases from Oregon and Washington. The optimum match parameters were the date, state, vessel official number, and number of people on board. Conclusions Statistical data linkage enables accurate, routine matching for small de-identified injury and fatality data sets such as those in commercial fishing. It provides information needed to improve the accuracy of existing data records. It also enables expanding and sharpening details of individual incidents in support of occupational safety research.

scholarly journals Current States and Future Trends in Safety Research of Construction Personnel: A Quantitative Analysis Based on Social Network Approach

2021 ◽  
Vol 18 (3) ◽  
pp. 883
Author(s):  
Xiangcheng Meng ◽  
Alan H. S. Chan
Keyword(s):  
Social Network ◽  
Path Analysis ◽  
Construction Industry ◽  
Occupational Safety ◽  
Future Trends ◽  
Network Approach ◽  
Main Path ◽  
Safety Research ◽  
Main Path Analysis ◽  
Social Network Approach

The construction industry is recognized as a high-risk industry given that safety accidents and personnel injuries frequently occur. This study provided a systematic and quantitative review of existing research achievements by conducting social network approach to identify current states and future trends for the occupational safety of construction personnel. A total of 250 peer-reviewed articles were collected to examine the research on safety issues of workers in construction industry. Social network approach was applied to analyze the interrelationship among authors, keywords, and citations of these articles using VOS viewer and CitNetExplorer. A knowledge structure map was drawn using main path analysis (MPA) towards the collected papers, which was implemented by Pajek. In line with the findings of social network analysis, five research groups, and six keyword themes were identified in accordance with the times of cooperation of researchers and correlation among keywords of the papers. Core papers were identified by using main path analysis for each research domain to represent the key process and backbone for the corresponding area. Based on the finding of the research, significant implications and insights in terms of current research status and further research trends were provided for the scholars, thus helping generate a targeted development plan for occupational safety in construction industry.

scholarly journals From Line to Loop, A Circular 3D Printing Initiative for Upcycling Commercial Fishing Plastics

2021 ◽  
Author(s):  
◽  
Matthew O'Hagan
Keyword(s):  
3D Printing ◽  
Large Scale ◽  
Commercial Fishing ◽  
Fishing Gear ◽  
Fishing Industry ◽  
Distributed Manufacturing ◽  
Research Through Design ◽  
Management Scheme ◽  
The Pacific ◽  
Manufacturing Technologies

<p>The current linear use of plastic products follows a take, make and waste process. Commonly used by large scale industries, including the commercial fishing industry, this process results in approximately 8 million tonnes of plastic entering the ocean every year. While the fishing industry supplies livelihoods, a valuable food source and financial capital to millions of people worldwide, it’s also a significant contributor to the ocean plastics crisis. Without effective recycling schemes, an estimated 640,000 tonnes of plastic fishing gear is abandoned, lost or discarded within the ocean every year. New Zealand is no exception to this problem, as China’s waste import ban, as well as a lack of local recycling infrastructures, has resulted in the country’s commercial fishing gear polluting local coastlines as well as islands in the pacific. With the only other option for the plastic fishing gear being landfill, there is a critical need for circular initiatives that upcycle used plastic fishing gear locally into eco-innovative designs.  This research examines the issue by investigating how used buoys, aquaculture ropes and fishing nets from New Zealand’s fishing company ‘Sanford’ may be upcycled into eco-innovative designs through distributed manufacturing technologies. It introduces the idea of the circular economy, where plastic fishing gear can be reused within a technical cycle and explores how 3D printing could be part of the solution as it provides local initiatives, low material and energy usage and customisation. Overall, the research follows the research through design based on design criteria approach. Where materials, designs and systems are created under the refined research criteria, to ensure the plastic fishing gear samples are upcycled effectively into eco-innovative designs through 3D printing.  The tangible outputs of this research demonstrate how a circular upcycling system that uses distributed manufacturing technologies can create eco-innovative designs and provide a responsible disposal scheme for plastic fishing gear. It provides a new and more sustainable waste management scheme that could be applied to a range of plastic waste streams and diverts materials from entering the environment by continuously reusing them within the economy.</p>

Necessary Components of Economic Surplus in Fisheries Economics

1980 ◽  
Vol 37 (5) ◽  
pp. 858-870 ◽  
Author(s):  
Lee G. Anderson
Keyword(s):  
Consumer Surplus ◽  
Fish Stock ◽  
Commercial Fishing ◽  
Fishing Industry ◽  
Fisheries Economics ◽  
Economic Surplus ◽  
Detailed Model ◽  
Maximum Economic Yield ◽  
Worker Satisfaction ◽  
Different Levels

There are four main types of economic surpluses that can be achieved when exploiting a fishery. They are rent to the productive nature of the fish stock, normal factor rents to inputs, consumer surplus, and what is called here, worker satisfaction bonus, WSB. The latter refers to nonmonetary benefits individuals can obtain from participating in commercial fishing and, to be complete, in other occupations as well. It is discussed frequently, but has never received any formal treatment in the literature. In this paper the logic behind WSB in the fishing industry is discussed and its implications on policy is shown. A detailed model is developed which can show how all of the components of economic surplus relate to one another and how they will vary at different levels of output.Key words: fisheries economics, economic surplus, worker satisfaction bonus, maximum economic yield

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