Argentina

COVID-19 Purchasing Observatory

The COVID-19 Purchasing Observatory was created by the NGO Poder Ciudadano with the purpose of monitoring public purchases and procurement during the pandemic, taking into account that an administrative decision issued by the National Cabinet in March 2020 enabled an exceptional purchasing procedure in the emergency context. The Oversight seeks to monitor purchases and contracts and present them in a unified digital database, which is made available to the public. Additionally, the observatory assesses the degree of transparency of the National Government in this matter and issues policy recommendations.

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
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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