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CANVAS - Towards Safer and Attractive Cities: Crime and Violence Prevention through Smart Planning and Artistic Resistance

On going

About

Abstract: Responding to the rising insecurity and crime rates in Europe, CANVAS is a ground-breaking project that combines the smart specialization goal of ICT applied to cultural industries, with the societal challenge of building safer and inclusive cities. It supports major planning agendas regarding Safer Cities and the inclusion of vulnerable groups by pushing forward the third generation of Crime Prevention Through Urban Design and Planning (CP-UDP, née CPTED), i.e. it combines community-based partnerships with ICT developments in crime modeling.

Promoting innovative partnerships between academia, administration, police, artists and community (namely NEET) in neighborhoods in three Portuguese cities, CANVAS is a major step forward as it assumes a holistic place-based approach to crime and social exclusion, emphasizing both spatiality and sociality. First, based on the concepts of crime concentration, territorial stigmatization and smart policing it will develop a pioneering GIS crime prevention DST that can be applied by local authorities and police forces to understand geo-patterns of behavior, crime and insecurity, and thus test and apply scenarios of urban and socio-cultural requalification. Second, based on the concepts of community planning/policing, collective efficacy and arts-in-action it will capitalize on the potential of cultural capital to be a catalyst for youths to gain sense of belonging and thus cope with, and help prevent, violence and insecurity.

Working in focus groups with local artists, youth-centered prevention-in-action initiatives will be supported. Using digital humanities’ techniques, important cognitive maps of insecurity and the socio-spatial impact of cultural transformations will be made, whist through the creation of cultural outputs, commitment for prevention and social integration is fomented. Then, fed by a geocoded database of crime, socio-economic, morpho-functional and cognitive variables, the DST will generate important knowledge on the socio-urban causes that lead to insecurity hotspots. A safe map-app and a digital CP-UDP monitoring dashboard will be developed to enhance the skills of decision-makers and dwellers. By combining CP-UDP with culture-led regeneration; by uniting geo-social sciences with cutting-edge ICT expertize; and by engaging local communities and non-governmental actors with institutional partners; the project will develop and apply planning, design, socio-cultural and artistic responses that will counter social stigmatization, and reduce feelings of insecurity, crime and violence.

CANVAS fills an important gap in scientific research by presenting the combination of planning, geographical and sociological smart territorial tools as effective, human-centered and sustainable alternatives to traditional crime deterrents; and producing relevant evidence-base, long-lasting social dynamics and highly replicable solutions that support municipal planning, leading to safer and attractive environments.

Reference: POCI-01-0145-FEDER-030748

Scientific area: Geography and Sociology

End beneficiaries/target population: Populations living in deprived areas of Porto, Lisbon and Albufeira. Young NEET living in deprived areas of Porto, Lisbon and Albufeira.

Timeline: 2018-2022

Team Members
Useful Links
Partners
Faculdade de Letras da Universidade do Porto (FLUP) (Proponente)
Centro de Estudos em Geografia e Ordenamento do Território (CEGOT)
Instituto de Sociologia da Universidade do Porto (IS-UP)
Polícia Municipal de Lisboa
Funding Entity
Fundo Europeu de Desenvolvimento Regional (FEDER), através do Programa Operacional Competitividade e Internacionalização COMPETE 2020 e Fundação para a Ciência e a Tecnologia, I.P. (FCT)
Ano de início
2018

Contactos

Faculdade de Letras da Universidade do Porto
Via Panorâmica, s/n
4150-564 Porto, Portugal

Phone: +351 226 077 132
Email: isociologia@letras.up.pt

 

Other Contacts

 

Partners

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Ref. UIDP/00727/2020

Ref. UIDB/00727/2020

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