Developing a SocioEconomic Dataframe

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Developing a Socio-Economic Dataframe

• AIM
• Construct, test and refine a framework for the
  collection and management of socio-economic
  fisheries data
• Make recommendations on how it could be
  operationalised especially when making policy.

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Rationale

• Commitment within the CFP to take account of
  social, economic and environmental factors in a
  balanced manner (EC 2002) when taking fisheries
  management decisions.
• No system for monitoring and analysing social and
  economic circumstances of fisheries communities
  and sectors, so commitment not met
• Project to develop methodology for systematic and
  consistent analysis of social and economic
  implications of fisheries management policy

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Dataframe Concept
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The Work

• International team UK, Holland, Denmark
• Looked at industry, community and institutional
  factors that assessments of the socio-economic
  implications of policy need to consider
• Comprehensive literature search to review the
  collection, management and use of socio-economic
  fisheries data around the world
• Field research in Amble, Peterhead and Shetland
  to test draft Dataframe
• Project workshops to develop and refine structure

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Literature Review

• Institutionalisation of socio-economic analysis
  requires prioritisation in terms of time and
  resources at policy level
• Local participation important in data collection
  and management BUT
• Socio-economic expertise is also necessary to
  ensure correct interpretation of collected data
• Industrial, community and institutional
  information is already used in fisheries
  management decision-making and can be organised,
  accessed and understood via systems of databases,
  indicators and profiles
• Community Profile system in the US a good example

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Field Research

• Peterhead, Shetland (Lerwick) and Amble
• Look at how accessible and well documented
  socio-economic data is within fisheries and
  communities
• Assess the utility of the Dataframe concept in
  practice
• Found data at a range of scales, at diverse
  locations, and with high degree of
  incompatibility and discrepancy
• Data sources include government statistics on
  catching sector and general population, public
  websites for institutional information, eg LAs,
  and local knowledge for non-fleet fishery sector
  and social network data

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Sorting the Data

• Data inserted into draft Dataframe, analysed and
  refined during two workshops. Finalised with two
  main components
• Community and sectoral socio-economic profiles,
  underpinned by a full-scale baseline study of
  fishing communities and sectors
• Seven socio-economic indicators related to
  industry, community and institutional spheres,
  underpinned by annual quantitative and
  qualitative data-gathering processes, such as the
  EU Data Collection Regulation

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The 7 Indicators

• Industry Profitability, Employment, Economic
  value
• Community Population, Social well-being
• Institutional Arrangements Social policy,
  Fisheries governance
• Requires quantitative data (eg under Data
  Collection Regulation) and qualitative
  socio-economic data.
• Requires data to be collected at the community
  scale
• Without local-scale data, the analysis of
  socio-economic impacts of policy on fishing
  communities would not be possible

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Conclusions

• Multi-layer Dataframe combined with systematic
  data-gathering process to ensure utility and
  durability of the Dataframe for intended uses
• Strategic policy development
• Socio-economic impact assessment
• Improve capacity of managers and communities to
  maintain information

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Recommendations

• Request amendments to the Data Collection
  Regulation for inclusion of specific data
• Establish quantitative and qualitative
  data-gathering mechanisms for data aspects not
  currently included under the Data Collection
  Regulation
• Develop technical structure of Dataframe and its
  user-interface

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Outcome

• Achievement of recommendations will enable
  governments, managers, resource users, community
  organisations and stakeholders to propose and
  make long-term policies that are more
  socio-economically sensitive to fisheries and
  fisheries communities and sectors

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Next Steps

• Identify possibilities for research,
  collaboration and action in the EU
• Involve governments, research institutes?
• Potential to suggest research to Commission?
• Review of work already undertaken?
• Discuss