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However, despite concerted efforts to promote gender equality and women's empowerment, significant challenges persist in realizing the full potential of women's participation in GVCs. Barriers such as limited access to education and training, gender-based discrimination, and unequal opportunities continue to hinder women's economic advancement, particularly in developing countries.
One of the significant hurdles in addressing these challenges lies in the complexity of analyzing the vast amounts of data associated with GVCs and women's participation. Conventional analytical methods often struggle to capture the intricate relationships and patterns within these datasets, limiting their effectiveness in informing evidence-based policies and interventions.
To overcome this limitation and unlock the socio-economic benefits of gender-inclusive GVCs, innovative approaches are needed. In this context, the intersection of machine learning technology and women's economic empowerment offers promising avenues for driving positive change. Machine learning, a branch of artificial intelligence, encompasses a diverse set of algorithms and techniques that enable computers to learn from data and make predictions or decisions without explicit programming.
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