Resilience and transformation in times of economic crisis: The persistence of community in the Lisbon Metropolitan Area

ABSTRACT

The economic and financial crisis that hit various European countries, including Portugal, has caused a series of social effects and reactions that have been studied using a number of different conceptual approaches. The article looks at two types in particular: those which analyze populations’ levels of resilience regarding proximity and community relations; and those which address collective action movements and practices that seek to transform society. The main goal is to consider the fact that these distinct practices coexist in the same territories, suggesting that they should therefore not be analyzed separately. The other objective is to determine what sociological variables and socio-spatial contexts are key to these different types of practices. The study was based on the territory formed by the Lisbon Metropolitan Area (AML) and entailed a survey of 1,500 of its residents. The data indicate a persistence of proximity and community relations, mainly among residents of rural areas.

KEYWORDS:

• Resilience
• collective action
• urban
• rural
• community

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. In more recent texts about the internet and related social networks, Wellman refers to the notion of partial communities, which he says are linked to specialized ties and underlines the individualized nature (centered on each individual) of the networks formed online (Wellman & Haythornthwaite, 2002).

2. However, within the overall framework of these analyses, the focus on the community and its relationship with concepts such as social capital continues to be examined and debated (Carmo & Santos, 2014).

3. According to the 2011 General Population Census (Statistics Portugal – INE, in Portuguese), the AML consisted of 211 parishes. A Portuguese parish is a delimited administrative territory within a larger municipal council area.

4. For a more detailed description of the construction of this typology, see Santos (2016).

5. I.e. neighbors’ mutual knowledge of one another, how often each respondent talks to his/her neighbors, the degree of trust he/she has in them, and the existence of any support and family networks near the place of residence. The data regarding this section are presented in Tables A1 and A2 (see Appendix). Table A1 crosses these variables and the socio-territorial typology; Table A2 shows the cross with other characterization variables (age, education, occupational situation).

6. The four dependent variables are that the respondent: knows his/her neighbors; talks to them; trusts them; and lastly, has engaged in collective action practices.

7. The dependent variables and most of the independent ones used in the model were coded in binary form (“1” – Yes; “0” – Other responses). The independent variables cover three main dimensions: a) socioeconomic characterization – schooling up to year 9, situation in employment, aged 18 to 34 years old, higher social category (businessmen, senior executives, and managers), housing quality as a reason for choosing place of residence, perception that social situation has gone backwards; b) proximity relations – has support network, tells neighbors when goes away, relatives living close by was a reason for choosing place of residence, feeling unsafe with neighbors, spatial immobility; c) socio-territorial typology – “rural” is selected as the reference category of this variable in the regression model.

Additional information

Funding

This work was supported by the Portuguese Fundação para a Ciência e a Tecnologia [PTDC/ATP-EUR/5023/2012].