By Agendas: Stig Rästa

The expertise clearly focuses on the social sector and the accessibility of services, particularly highlighting the role of care workers, teachers, and social workers. Emphasis is placed on the quality of services and the human dimension—for instance, transforming a nursing home into a warm community. While technical data or statistics are absent, the practical challenges of social work are addressed in depth.

The speaker demonstrates knowledge of the European Union's comparative tax burden data and employs specific fiscal policy terminology (tax burden, tax revenues). The analysis focuses on evaluating macro-level economic risks and strengths within the context of a low tax burden.

The speaker demonstrates a strong understanding of the legal mandates of the Police and Border Guard Board (PPA) and the governance surrounding modern technological tools, such as cameras and Automated Number Plate Recognition (ANPR). They draw comparisons with neighboring countries (Finland, Sweden, Latvia) regarding the deployment of similar systems to underscore Estonia's necessity to progress. It is stressed that recordings may only be utilized in clearly defined circumstances.

The speaker demonstrates expertise in macroeconomics, particularly in the areas of productivity, export structure, and research and development (R&D). Specific statistical data is utilized, noting that services account for 42% of total exports and that GDP per hour worked is 25–30% lower than the EU average. This expertise is grounded in the speaker's background as a private entrepreneur involved in the music industry.

The speaker demonstrates expertise in international law and human rights protection mechanisms, explaining in detail the functioning of the Optional Protocol and the procedure for submitting complaints to the UN. He is aware of the problems concerning the committee’s workload and inefficiency, and explains the proposed solution (amendment to Article 20, paragraph 1) aimed at making the committee’s work faster and more efficient.

Insufficient dataset.