Project Team
Project Leader:
- Stein Østbye - UiT the Arctic University of Norway
Collaborators:
- Derek Clark - UiT the Arctic University of Norway
- Mikko Moilanen - UiT the Arctic University of Norway
- Espen Sirnes - UiT the Arctic University of Norway
- Agnès Festré - UiT the Arctic University of Norway & Université Côte d'Azur
- Iván Barreda-Tarrazona - University Jaume I
- Jaakko Simonen - Oulu University
Students:
- Chris Andersen - PhD, UiT the Arctic University of Norway
- Jemina Kotila - PhD, Oulu University
- Joona Lohtander - PhD, Oulu University
Research Project
Project Description
One type of capital that is particularly important, and possibly underrated, is social capital at the community level. Unlike financial, physical, and human capital that can be accumulated and owned individually, social capital accumulation has a collective dimension external to the individual. Social capital is a feature of social structure and does not devaluate because of use, but rather because of lack of use: social capital is self-reinforcing when reciprocity increases connectedness between people, leading to greater trust, confidence and capacity to innovate. In tightly knit communities transaction costs are lower, as costs of enforcing contracts and monitoring are smaller. Knowledge and expertise can be exchanged more easily than in low-trust communities, and people might take more risk because of the informal social safety net. Social capital may therefore lead to positive individual and community-level outcomes, including cohesive communities, individual well-being, more efficient use of scarce resources, and higher economic growth.
Social innovation that increases social capital is key for building resilient and sustainable Arctic communities. Successful communities will, all else equal, in the long term contribute to higher average living standards and a more equitable distribution within the community, but also to closing the inequality gap between the Arctic North and the South within the country.
Social innovation may increase social capital and social resilience. A particular novel form of social innovation is digital social innovation, which may not only have positive effects on social capital but also compensate for lack of social capital. Community-centric digital platforms embedded in local communities have the potential to build community resilience and navigate external crises. In the past, bonding social capital may have been sufficient to avoid problems of excess use and free-riding related to natural resources. Assume the population becomes less homogenous. Digital platforms may then help decentralized collective action, despite more heterogeneity, by rewarding common efforts that can limit the free-riding effect. We intend to use digital social innovation as a case study of social innovation by looking into the potential of digital platforms as a substitute or complement to social capital in increasing resilience.
Secondly, we intend to apply a neural-network word embedding model, to analyze potential cultural differences in meanings of social capital, that is attitudes to trust and reciprocity. How do understandings of trust and reciprocity differ across languages and places in Arctic Scandinavia? Word embedding models require very large collections of text to reproduce accurate semantic relationships and are demanding in terms of computing capacity. We therefore use access to super computers and large text corpora both in Saami and Norwegian and extend this to Swedish and Finnish. We consider extending the analysis further (third year) to other Arctic Nordic languages. We intend to use regional metadata to look at possible correlation between results from the semantic analysis and measures of inequality. The work will be conducted in collaboration with linguists at UiT.
Self-organized collective action and resilience are often facilitated by social capital. The proportion of co-operators in social dilemma games may be used as a simple metric for social capital in a population of experimental subjects. We will explore whether heterogeneity varies across subject-pools from various places and whether co-operating is the default response. We will also here use metadata for the area where the subject-pool is located in order to explore correlations with measures related to inequality and living standards.
Geographical Areas
Norway
Sweden
Finland
Objectives, Axes and Work Packages
Objectives
A. Describe
B. Explain
C. Imagine
Axes
1. Current state of wealth distribution
2. Social transitions and trends in the distribution of wealth
3. Towards a more equitable distribution
Work Packages
3.4. Social innovation, reconciliation and adaptation