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Assessment of poor students subsidy big data is really fair
Assessment of poor students subsidy big data is really fair
Jiangsu University in Zhenjiang, Jiangsu province,recently disqualified 21 students from receiving subsidies intended for impoverished students based on their monthly mobile phone payments, Beijing News reported on May 9.
Another school, Nanjing University of Science and Technology, had previously used students’ monthly consumption habits in the university canteen to determine who needed financial support. What Jiangsu University did, however, is more controversial because phone fees say little about a student’s financial situation.
Schools have turned to using consumption habits as a metric for poverty in an effort to spare families from public embarrassment. In the past, applications for financial support we red is closed for public scrutiny, and some families felt uncomfortable with the possibility that their private finances might be published for all to see.
However, the use of big data , which only applies to how much students spend during a certain period of time, is still unable to identify whether they are from rich or poor families.
In many developed countries, college students do not have to go through these kinds of appraisals to receive subsidies. All they need is evidence of their family’s income and taxes. A fake application is usually easily identified and will become an indelible stain on a student’s record .
Universities that make the switch to a system based on big data face several obstacles. First,they have to be careful not to infringe upon students’ legal interests or selectively collect their information. To bolster their big data systems, some schools are using alumni networks and local governments to get a better idea of each student’s financial background. To further prevent fraudulent applications, the country also needs to keep improving the nation wide cred it investigation system.
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