Ricky Bryan Quiñones Fabian, Ruben Aldair Andamayo Alcantara, Abel Jesus Inga Lopez, Jaime Antonio Huaytalla Pariona, J. A. D. Quispe
{"title":"An algorithm to estimate the risk of child labor","authors":"Ricky Bryan Quiñones Fabian, Ruben Aldair Andamayo Alcantara, Abel Jesus Inga Lopez, Jaime Antonio Huaytalla Pariona, J. A. D. Quispe","doi":"10.5267/j.dsl.2022.5.004","DOIUrl":null,"url":null,"abstract":"In developing countries, child labor has become a significant problem with adverse effects in the present and future for society and individuals. There are many causes that obligate children to abandon school and start working. Economic, social, familiar, and personal problems can expel children from school, inhibiting them from living appropriately. Polls like the ENAHO in Peru tried to recollect relevant data as much as possible to explain this problem. With many variables, it is necessary to have a methodology to build an algorithm with enough explanatory power to explain the situation. Therefore, this research elaborated an algorithm through Lasso to proportionate a statistical explanation of child labor. Due to the type of data, the regression was logistic.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision Science Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5267/j.dsl.2022.5.004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
In developing countries, child labor has become a significant problem with adverse effects in the present and future for society and individuals. There are many causes that obligate children to abandon school and start working. Economic, social, familiar, and personal problems can expel children from school, inhibiting them from living appropriately. Polls like the ENAHO in Peru tried to recollect relevant data as much as possible to explain this problem. With many variables, it is necessary to have a methodology to build an algorithm with enough explanatory power to explain the situation. Therefore, this research elaborated an algorithm through Lasso to proportionate a statistical explanation of child labor. Due to the type of data, the regression was logistic.
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