Why—contrary to much expert and popular opinion—more education may not be the answer to skyrocketing inequality. For generations, Americans have looked to education as the solution to economic disadvantage. Yet, although more people are earning degrees, the gap between rich and poor is widening. Cristina Groeger delves into the history of this seeming contradiction, explaining how education came to be seen as a panacea even as it paved the way for deepening inequality. The Education Trap returns to the first decades of the twentieth century, when Americans were grappling with the unprecedented inequities of the Gilded Age. Groeger’s test case is the city of Boston, which spent heavily on public schools. She examines how workplaces came to depend on an army of white-collar staff, largely women and second-generation immigrants, trained in secondary schools. But Groeger finds that the shift to more educated labor had negative consequences—both intended and unintended—for many workers. Employers supported training in schools in order to undermine the influence of craft unions, and so shift workplace power toward management. And advanced educational credentials became a means of controlling access to high-paying professional and business jobs, concentrating power and wealth. Formal education thus became a central force in maintaining inequality. The idea that more education should be the primary means of reducing inequality may be appealing to politicians and voters, but Groeger warns that it may be a dangerous policy trap. If we want a more equitable society, we should not just prescribe more time in the classroom, but fight for justice in the workplace.

The book features original papers from International Conference on Cryptology & Network Security with Machine Learning (ICCNSML 2022), organized by PSIT, Kanpur, India during 16 – 18 December 2022. This conference proceeding will provide the understanding of core concepts of Cryptology & Network Security with ML in data communication. The book covers research papers in public key cryptography, elliptic curve cryptography, post quantum cryptography, lattice based cryptography, non-commutative ring based cryptography, cryptocurrency, authentication, key agreement, Hash functions, block/stream ciphers, polynomial based cryptography, code based cryptography, NTRU cryptosystems, security and privacy in machine learning, block chain, IoT security, wireless security protocols, cryptanalysis, number theory, quantum computing, cryptographic aspects of network security, complexity theory, and cryptography with machine learning.