KIDS 2.1 – Key Indicators for Demographic Sustainability 2.1

Project description:

The KIDS 2.1 (Key Indicators for Demographic Sustainability 2.1) project addresses the critical demographic challenge of low fertility in Slovakia by analyzing the socio-economic, cultural, and psychological drivers of reproductive behavior among young adults (Millennials and Gen Z, aged ~18–35). A central focus is to improve the understanding of how contemporary value shifts—changing priorities regarding work, autonomy, and traditional norms—interact with structural constraints to shape the motivations of young people regarding family formation. The primary objective is to provide an empirical foundation for demographic policies capable of sustaining a fertility rate of approximately 2.1 children per woman.

This research employs a rigorous mixed-method approach that integrates sociological data collection with advanced computational modeling. The methodology is structured into four phases: (1) the development of a culturally attuned survey instrument (KIDS 2.1) aligned with international standards; (2) the execution of a nationally representative survey (n≈1,200) embedded within the World Values Survey (WVS) Wave 9, ensuring the inclusion of marginalized groups such as the Roma community; (3) qualitative validation through focus groups to contextualize how value shifts influence decisionmaking; and (4) the application of the SK-DigiTwin Multi-Agent Artificial Intelligence (MAAI) platform.

By translating complex motivational profiles into behavioral rules for AI agents, the project will simulate the impact of various policy interventions on fertility trends. The expected outcomes include evidence-based recommendations for harmonizing not only the economic incentives with the evolving values of young adults to support family formation.

Project aims:

1. Develop, validate and implement the KIDS 2.1 quantitative research module to measure reproductive and family motivations of young Slovaks.
2. Precisely map the socio‑economic, cultural, psychological and value‑based factors that support or hinder family formation in Slovakia.
3. Transform these empirical findings into behavioural rules and parameters suitable for multi‑agent AI simulation in SK‑
4. Use SK‑DigiTwin to simulate how alternative family‑policy packages would impact fertility behaviour over time under different societal conditions.
5. Deliver clear, evidence‑based and normatively transparent recommendations to help policymakers design effective, cohesion‑preserving pro‑family policies.