Future of Third Sector Research

.- The Third Sector research: the construction of a field of study.

.- Section I - Theory.

.- Theory of the Third Sector.

.- Commentary on "Theory of the Third Sector".

.- Section II - Definition.

.- Third Sector: the building of a research field.

.- The terminological debate.

.- In search of a positive, historical and experimentalist definition of civil society.

.- Defining civil society in the turbulent times - lessons from Poland.

.- Defining Civil Society - Commentary.

.- Section III - Classification.

.- Part One: The Classification of Civil Society, Nonprofit and Third Sector Organizations.

.- Part Two: Turning a Critical Lens on Nonprofit Classification: Opportunities and Challenges in the Digital Age

.- CSO classification: a commentary from Latin America.

.- Section IV - Aggregation.

.- Data Aggregation: An Overview of Opportunities and Obstacles from the National to the Global.

.- Capturing Data on Volunteering in a Global Dimension: a Window of Opportunity for Furthering Third Sector Research.

.- Technologies for Data Aggregation: An Overview of Technologies and Opportunities to Propel Third Sector Research.

.- Commentary on "Data Aggregation" by Elizabeth Bloodgood, Ksenija Fonovic, and Francisco Santamarina.

.- Section V - Faith.

.- The Relationship between the Third Sector and Religion.

.- Analyzing civil society in the Arab world: a conceptual review.

.- Religion and faith-based organizations in Brazil's social policies.

.- Commentary on Section V Faith.

.- Section VI - Ways forward.

.- Third-Sector Research: Ubi eras, quo vadis?.

.- Commentary on Section VI - Third-Sector Research: Ubi eras, quo vadis?.

.- Future Challenges Facing Third Sector Research.

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• Instituições internacionais
• Administração pública
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civil society;third sector research;nonprofit;civil origins theory;social economy;voluntary sector;nonprofit sector;independent sector;charitable sector;faith-based;International Comparative Nonprofit Organization project;ICNPO;data analysis;machine learning;Open Access