Verification of a labor market domain using an academic crowdsourcing system - Esteban J. Azofeifa; Galina M. Novikova (Discrete and Continuous Models and Applied Computational Science, 2020)
Students desiring to become a valuable good in the labor market are willing to pay a considerable monetary cost to obtain knowledge about their prospective job opportunities, nowadays with a diminishing interest in the obtainment of a diploma. Considering the behavior of the labor market as a domain theory under uncertainty, it is straightforward to expect the presence of contradictions, in the form of salaries unable to be classified due to high inconsistency and variation. We provide an algorithm to verify a labor market domain theory based on a crowdsourcing academic system, in which feedback about possible contradictions is generated as a result of consultations with experts inside of the market and clustered into different contexts. We found that the verification process can be repeated iteratively as long as the students overall tuition is equal or greater than a quantity partially defined by the number of different profiles of the students.