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This guide provides comprehensive standards for analyzing and reporting results in Organization Science, a field characterized by diverse methodologies. It ensures methodological rigor and transparency whether the work is qualitative (establishing trustworthiness), quantitative (matching estimators to design), computational (reporting seeds and sensitivity), or formal/analytical. It emphasizes full reproducibility and mechanism-based inference.

NetworkX is a powerful Python package designed for creating, manipulating, and analyzing complex networks and graphs. It supports various graph types (Directed, Undirected, MultiGraphs) and provides extensive functionality for graph algorithms, including shortest path calculation, centrality measures (like PageRank), community detection, and connectivity checks. Users can generate synthetic networks, read/write data from multiple formats (GraphML, CSV, Pandas), and visualize results using Matplotlib. Ideal for social network analysis, biological research, and system modeling.