Developing a Socio-Economic
Dataframe
• AIM:
• Construct, test and refine a framework for
the collection and management of socioeconomic fisheries data
• Make recommendations on how it could
be operationalised – especially when
making policy.
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
Dataframe Concept
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 socioeconomic fisheries data around the world
• Field research in Amble, Peterhead and
Shetland to test draft Dataframe
• Project workshops to develop and refine
structure
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
Field Research
• Peterhead, Shetland (Lerwick) and Amble
• Look at how accessible and well documented socioeconomic 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
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
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
L1
L2
L3
L4
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
Recommendations
• Request amendments to the Data
Collection Regulation for inclusion of
specific data
• Establish quantitative and qualitative datagathering mechanisms for data aspects
not currently included under the Data
Collection Regulation
• Develop technical structure of Dataframe
and its user-interface
Outcome
• Achievement of recommendations will
enable governments, managers, resource
users, community organisations and
stakeholders to propose and make longterm policies that are more socioeconomically sensitive to fisheries and
fisheries communities and sectors
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…