By Plenary Sessions: Tõnis Lukas

The speaker demonstrates knowledge of the historical backing asset of the Estonian kroon (forest, until 1997, 4,021 tracts) and links this to contemporary climate goals. Specific terminology related to central bank operations is employed, referencing, for instance, the reduction in the use of 1- and 2-cent coins as a concrete energy-saving measure.

The speaker demonstrates deep expertise in education system funding (equalization fund coefficients, per-capita funding vs. class-set based funding) and demographic processes (internal migration, decline in birth rate). Technical terms such as the "remoteness coefficient" are used, and specific examples are provided from municipalities (Jõelähtme, Rõuge, Lääneranna) and schools (Metsküla, Lüganuse) to support their arguments.

The speaker demonstrates in-depth knowledge of immigration regulations (the quota limit, 13 exceptions, the 1.5-times salary criterion) and labor market data, referencing data from Statistics Estonia and OSKA reports. He/She is familiar with salary ranges across various sectors and highlights previous experience managing a large vocational education center. The expertise is focused on analyzing the relationship between specialists' salary levels and quota exceptions.

The speaker demonstrates a thorough knowledge of immigration regulations, specifying 13 different types of exceptions to the immigration ceiling and the applicability of the quota to third countries. Furthermore, he/she is familiar with the salary criteria (a minimum of 1.5 times the standard salary) required for top specialists to be exempted from the quota.

Demonstrates profound expertise in the field of education and language policy, referencing prior experience as Minister of Education and regular engagement with the association representing large families. The text employs specific terminology and data points, such as B1-level exam failures, the differentiation fund, the career model, and workload calculation. It analyzes the distortion of statistics resulting from regional disparities (Ida-Virumaa, municipalities surrounding Tallinn) and provides historical comparisons with Soviet-era school models.