No potential conflict of interest was reported by the author(s). This work was ethically approved by the EASHW of University of Antwerp, with approval number SHW_2023_23_1. Additional information This work was supported by the Flemish Science Fund (FWO) under Grant [G098023N]; the Austrian Science Fund (FWF) under Grant [I6320-G].

ABSTRACT Nonprofit organizations increasingly integrate volunteers alongside paid staff to address growing demands for social services amid austerity measures assuming that they complement the expertise of paid staff. This study combines the frameworks of brokerage and boundary work to explore the strategies used by paid staff and volunteers to navigate boundaries in their collaboration.

ABSTRACT School choice policies allow parents to act on their preferences when choosing a school for their child(ren). These policies, however, can lead to planning problems for policymakers . We contribute to a better empirical understanding of parental school preferences and the factors shaping these preferences. Using survey data (n = 4,574), we contrast five machine learning algorithms with logistic regression.