| 000 | 01361nam a22001337a 4500 | ||
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| 999 |
_c532807 _d532807 |
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| 008 | 260319b ||||| |||| 00| 0 eng d | ||
| 100 |
_aWhetsell, Travis A. and Siciliano, Michael D. _959788 |
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| 245 | _a Applied causal inference in public sector network | ||
| 260 | _aPublic Administration Review | ||
| 300 | _a85(6), Nov-Dec, 2025: p.1771-1787 | ||
| 520 | _aPublic administration research has increasingly turned to network analysis to understand complex inter-organizational and interpersonal dynamics. While the discipline has made significant progress in analyzing networks, it has yet to adequately address causality. This gap limits our ability to provide evidence-based insights to practitioners who must make strategic decisions within networks. This article calls for the systematic integration of causal design into network research. We identify challenges that complicate causal analysis and discuss a set of practical research designs to address threats to validity. Borrowing insights from adjacent disciplines, we demonstrate how the logic of causal inference can be applied to public sector networks. We aim to equip scholars and practitioners with the tools to evaluate causal relationships in networks.- Reproduced https://onlinelibrary.wiley.com/doi/10.1111/puar.70009 | ||
| 773 | _aPublic Administration Review | ||
| 942 | _cAR | ||