Third-generation gravitational-wave observatories such as the Einstein Telescope (ET) will enable unprecedented studies of both cosmology and compact-object populations using large samples of “dark sirens,” i.e., gravitational-wave events without electromagnetic counterparts. In this presentation, we explore the ability of ET to jointly infer the underlying cosmological model and the mass and redshift distributions of binary black hole (BBH) mergers using one year of observations. We assume a flat ΛCDM cosmology and model the BBH population with a smoothed power-law plus Gaussian mass distribution and a Madau–Dickinson parametrization for the merger-rate redshift evolution. Using mock BBH catalogs generated for different signal-to-noise ratio (SNR) detection thresholds, we perform a hierarchical Bayesian analysis that consistently accounts for selection effects and measurement uncertainties. We find that decreasing the SNR threshold leads to a substantial improvement in the precision of the Hubble constant H₀ and the matter density parameter Ωₘ,₀, primarily due to the inclusion of a larger number of high-redshift events. However, this gain is accompanied by non-trivial degeneracies between cosmological and astrophysical parameters, whose structure evolves with the SNR threshold. This study highlights the importance of joint population–cosmology inference with third-generation detectors and demonstrates the strong potential of the Einstein Telescope to advance dark-siren cosmology while simultaneously deepening our understanding of black hole formation and evolution.