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Patterns of seafarer injuries

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  • Neil Ellis
  • Michael Bloor
  • Helen Sampson

Abstract

In this paper, secondary analyses derived from injury data obtained from 16 maritime administrations are presented. Evidence of issues effecting reporting which argue against the aggregation of datasets of different administrations is examined. Some important dimensions of these issues are analysed. Considering two different large maritime administrations, evidence is presented indicating that injuries are systematically under-reported in general cargo ships, compared to other types of trades and that injuries are systematically under-reported by some crew nationalities within a given maritime administration. There is a clear need to invest in studies of the social processes of shipboard injury reporting, if we are to be able to interpret seafarer injury statistics.

Suggested Citation

  • Neil Ellis & Michael Bloor & Helen Sampson, 2010. "Patterns of seafarer injuries," Maritime Policy & Management, Taylor & Francis Journals, vol. 37(2), pages 121-128, March.
    • Handle: RePEc:taf:marpmg:v:37:y:2010:i:2:p:121-128
    DOI: 10.1080/03088830903533742
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    References listed on IDEAS

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    1. Stephen Roberts, 2000. "Occupational mortality among British merchant seafarers (1986-1995)," Maritime Policy & Management, Taylor & Francis Journals, vol. 27(3), pages 253-265.
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    Cited by:

    1. Jiangang Fei & Jianjun Lu, 2015. "Analysis of students' perceptions of seafaring career in China based on artificial neural network and genetic programming," Maritime Policy & Management, Taylor & Francis Journals, vol. 42(2), pages 111-126, February.
    2. Conghua Xue & Lijun Tang, 2019. "Organisational support and safety management: A study of shipboard safety supervision," The Economic and Labour Relations Review, , vol. 30(4), pages 549-565, December.
    3. Guizhen Zhang & Vinh V. Thai & Adrian Wing‐Keung Law & Kum Fai Yuen & Hui Shan Loh & Qingji Zhou, 2020. "Quantitative Risk Assessment of Seafarers’ Nonfatal Injuries Due to Occupational Accidents Based on Bayesian Network Modeling," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 8-23, January.

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