<｜begin▁of▁sentence｜>### Instruction:
Imagine we are in a consulting scenario where we are advising an organization on structuring their mentorship program to ensure an inclusive environment where diversity in exchanges is quantified and balanced. To visualize this, we are considering a network representation of these mentorship exchanges. Each node in this network is a participant, arrows (edges) represent the mentorship direction, and the degree of connectivity corresponds to the number of exchanges.

To ensure an equitable distribution of mentorship interactions, we propose a directed graph model. Each participant (node) is involved in exactly two mentoring exchanges, where they mentor two others (out-degree of 2) and are mentored by two different individuals (in-degree of 2). 

For better structuring, we’ve defined a directed joint degree dictionary that quantifies the desired number of edges between nodes of different mentoring capacities. The specification is such that we want participants who mentor once (out-degree of 1) to be mentored by two individuals (in-degree of 2) exactly twice, participants who mentor twice (out-degree of 2) to be mentored by individuals who mentor three times (in-degree of 3) also twice, and finally, individuals who mentor three times (out-degree of 3) should be mentored by individuals who mentor once (in-degree of 1) twice as well. This directed joint degree dictionary can be depicted as `nkk = {1: {2: 2, 3: 0}, 2: {1: 0, 3: 2}, 3: {1: 2, 2: 0}}`, where `nkk[k][l]` indicates the number of directed edges from nodes with out-degree k to nodes with in-degree l.

In a practical sense, the organization seeks to determine if this particular configuration of mentorship program is feasible given the directed joint degree requirements. Would such a distribution ensure a diverse and inclusive engagement among the participants of the program?
### Response:
import networkx as nx

# Define in-degrees and out-degrees
in_degrees = [2, 2, 2]
out_degrees = [2, 2, 2]

# Define the directed joint degree dictionary (nkk)
nkk = {1: {2: 2, 3: 0}, 2: {1: 0, 3: 2}, 3: {1: 2, 2: 0}}

# Check if the direct joint degree is valid
is_realizable = nx.is_valid_directed_joint_degree(in_degrees, out_degrees, nkk)

print('Is the directed joint degree realizable?', is_realizable)
<|EOT|>
