Brazil

data_labe

Data_labe is a data and narrative laboratory, formed by young residents of the Maré favela in Rio de Janeiro with the support of the Favela Observatory and the Data School. Its goal is to generate different participatory projects that take into account the potentialities and complexities of living in popular territories through data and maps. Some of the projects conducted by this lab include the Favelas Cultural Guide, the Quilombox, the Community Communication Map, as well as several data reports on the provision of water, the application of the favelas to elections, and domestic violence, among other issues.

Institutional design

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Formalization: is the innovation embedded in the constitution or legislation, in an administrative act, or not formalized at all?

Frequency: how often does the innovation take place: only once, sporadically, or is it permanent or regular?

Mode of Selection of Participants: is the innovation open to all participants, access is restricted to some kind of condition, or both methods apply?

Type of participants: those who participate are individual citizens, civil society organizations, private stakeholders or a combination of those?

Decisiveness: does the innovation takes binding, non-binding or no decision at all?

Co-governance: is there involvement of the government in the process or not?

Formalization
not backed by constitution nor legislation, nor by any governmental policy or program 
Frequency
regular
Mode of selection of participants
restricted 
Type of participants
citizens civil society  
Decisiveness
democratic innovation yields no decision  
Co-Governance
no 

Means


  • Deliberation
  • Direct Voting
  • E-Participation
  • Citizen Representation

Ends


  • Accountability
  • Responsiveness
  • Rule of Law
  • Political Inclusion
  • Social Equality

Policy cycle

Agenda setting
Formulation and decision-making
Implementation
Policy Evaluation

Sources

How to quote

Do you want to use the data from this website? Here’s how to cite:

Pogrebinschi, Thamy. (2017). LATINNO Dataset. Berlin: WZB.

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