Using Big Data on the Benchmark Institution of Discretion in Administrative Penalty of Drug industry

DOI

10.2991/assehr.k.211220.233How to use a DOI?

Keywords

drug industry; administrative penalty; discretion benchmark; exemption clause

Abstract

In this paper, natural semantic recognition technology is used to deeply mine the data, meanwhile Regular Expression is also used to achieve text segmentation, text transformation, word segmentation, part-of-speech tagging, and delete stop words, so as to improve the accuracy of data. From the administrative penalty decision perspective, two obvious legal problems in applying the discretionary benchmark of administrative penalty cases in the drug industry were found, namely, the compliance problem and the exemption problem. On the one hand, different applicable scales and low explanatory rates cause discretionary benchmarks compliance issues; on the other hand, under the background of the replacement of old and new laws, due to the lack of normative exemption clause, some law enforcement officials will choose to directly escape the discretionary benchmark and impose a mitigated punishment below the statutory penalty based on the consideration of the cheapness of law enforcement.

Copyright

© 2021 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Ning Ma
AU  - Xu Mengna
PY  - 2021
DA  - 2021/12/24
TI  - Using Big Data on the Benchmark Institution of Discretion in Administrative Penalty of Drug industry
BT  - Proceedings of the 2021 4th International Conference on Humanities Education and Social Sciences (ICHESS 2021)
PB  - Atlantis Press
SP  - 1375
EP  - 1379
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.211220.233
DO  - 10.2991/assehr.k.211220.233
ID  - Ma2021
ER  -