The project facilitates rural development by working closely with regional stakeholders, including at policy level, to make rural areas and professions more attractive for existing populations and those with an emerging interest in the sector (rural newcomers). Through a balanced geographic coverage targeting Northern, Southern, Western, Eastern and Central Europe, the project provides a comparative assessment of challenges facing rural areas and people, as well as measures adopted by regional actors in order to tackle them. Novel techniques (AI-powered text-mining) are used alongside more traditional approaches like ex-post evaluation to analyse the effectiveness of the identified measures. The resulting evidence on current situation provides a baseline against which future developments in key rural sectors such as farming, forestry and fishery (FFF) are projected using qualitative (foresight) and quantitative (modelling) techniques. The latter will rely on a purpose-built web application for simulating alternative futures. The tool is one of the key technical outputs that decision makers can use to transform current practices in a way that ensures the best possible long-term outcome for their region. Cross-cutting priorities incorporating age, gender and various other demographic and socio-economic factors are considered during all stages of the project, from the needs analysis and evaluation through to the foresight, policy modelling and adaptation. Last but not least, the cocreation principle is firmly embedded into the PoliRural structure to ensure the views of two main target audiences – policy makers and grassroot rural populations – are actively exploited and used as input throughout the policy codesign cycle.

PoliRural is first and foremost a policy co-design exercise undertaken to achieve a simple objective: improve rural attractiveness of European regions. The entire exercise is therefore conceived as a means to achieving that end in five sequential steps

1. Needs analysis. This important first step seeks to understand what makes rural areas and professions attractive or unattractive, for existing and would-be rural populations. Mixed research techniques are used in combination with text mining to gather information on why people want to stay, leave or migrate to rural
areas. The term attractiveness is operationalize and explored separately for potential newcomers and those already living in rural settings.

2. Intervention matching. The second step assesses whether the identified needs are met by adequate response mechanisms. Is there a corresponding measure for each need from either public or private sector? If so, how exactly does it work? Answers to these questions will come from desk research as well as close consultation with people directly responsible for such interventions i.e. decision makers.

3. Policy evaluation. The third stage is a comprehensive evaluation exercise which uses text-mining, among other techniques, to establish a baseline for future scenarios and design thinking to identify potential new policies. The evaluation can be broadly distinguished between human centric and non-human centric. The former, as the name suggests, focuses on data collection from human participants; the latter on obtaining information from sources like academic literature, news articles, blogs and social media.

4. Future outlook. The penultimate stage in the policy co-design cycle will draw on qualitative (foresight) and quantitative (modelling) approaches to explore the evolution of rural areas and people in several scenarios. The foresight stream will include a series of face-to-face activities involving grassroot rural populations, experts and regional decision makers with the wherewithal to influence policy. Foresight results will feed the policy modelling exercise, which will explore the effect of different control variables (economic, social, demographic etc.) and policy changes (or status quo) on the future trajectory of rural development.

5. Policy transformation. The final stage involves the amendment of existing policies or creation of new ones in line with the preferences of key regional stakeholders. After alternative futures to decision makers, the expectation is that necessary changes will be made based on the preferred outcome. That said, decision makers may prefer not to wait until stage four is complete but start implementing small changes as soon as the results of stage one, two or three become available.


H2020-RUR-2018-2: Building modern rural policies on long-term visions and societal engagement


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