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.

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 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

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 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

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

Figure 2 – Illustration of the four layers of the dataframe

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 data-gathering 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 long-term policies that are more socio-economically 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…