<｜begin▁of▁sentence｜>### Instruction:
As a Philanthropy Advisor, imagine you're assisting a foundation dedicated to supporting education in underserved communities. They've utilized a network analysis tool, like NetworkX, to map out the connections between schools, students, and educational programs in various regions.

Now, they've loaded a graph representing these connections from a GML file and have implemented a clustering algorithm to identify groups of schools that collaborate closely with each other. Your task is to help them determine which edges in the graph connect schools from different clusters. This insight will aid them in understanding cross-collaboration opportunities and potential partnerships to enhance their impact on education.
### Response:
from igraph import Graph

# Assuming you have a graph 'g' and a VertexClustering object 'clustering'

# Read in the graph
#g = Graph.Read('path_to_your_graph_file.gml')

# Assume 'clustering' is obtained through some community detection method
#clustering = g.community_edge_betweenness().as_clustering()

# Get the boolean vector for edge crossings between clusters
edge_crossing = clustering.crossing()

# Print out which edges are crossing between clusters
for edge_id, is_crossing in enumerate(edge_crossing):
    print(f'Edge {edge_id}: {is_crossing}')
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