國立虎尾科技大學 |

Why Automated Data Is Biased : = The Politics of Air Quality Data in China.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Why Automated Data Is Biased :/
其他題名:	The Politics of Air Quality Data in China.
作者:	Liu, Guoer.
面頁冊數:	1 online resource (171 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
Contained By:	Dissertations Abstracts International86-03B.
標題:	Public administration. -
電子資源:	click for full text (PQDT)
ISBN:	9798384041863

Why Automated Data Is Biased : = The Politics of Air Quality Data in China.
Liu, Guoer.

Why Automated Data Is Biased :The Politics of Air Quality Data in China. - 1 online resource (171 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: B.

Thesis (Ph.D.)--University of Michigan, 2024.

Includes bibliographical references

Why do biases exist in government-produced data, even when the collection of that data is automated? I argue that these biases are not an outcome of agents' manipulation for personal gains, but an equilibrium that emerges from the strategic interaction between policymakers and agents, both benefiting from this arrangement. Particularly in authoritarian contexts, the accuracy of automated data can be compromised by the risk of uncovering information that undermines the regime's legitimacy. This tension between accuracy and favorability aligns the interests of political actors across and within the government hierarchy, transforming automation technology intended for objective monitoring into an instrument that obscures reality. Focusing on China's expansion of automatic ambient air quality monitoring from 2012 to 2022, I develop a game-theoretical model and present empirical evidence demonstrating how political actors strategically deploy the physical infrastructure essential for automated data collection. This analysis demonstrates that such strategic deployments compromise data accuracy even before the collection process begins. Departing from the classic principal-agent approach to biased data, this analysis emphasizes that political principals may actually implicitly endorse and propagate automated data that, while inaccurate, portrays the regime positively. This research contributes to our understanding of automated data more broadly: as technology and society progress, politically motivated data biases adapt and evolve, rather than disappear. Automatically generated data is yet another sleek end product of complex and sometimes messy upstream political processes.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798384041863Subjects--Topical Terms:

562473
Public administration.
Subjects--Index Terms:

Biased government dataIndex Terms--Genre/Form:

554714
Electronic books.

Why Automated Data Is Biased : = The Politics of Air Quality Data in China.
LDR:03175ntm a22004337 4500 001 1152696
005 20241209114634.5
006 m o d
007 cr mn ---uuuuu
008 250605s2024 xx obm 000 0 eng d
020 $a 9798384041863
035 $a (MiAaPQ)AAI31631049
035 $a (MiAaPQ)umichrackham005663
035 $a AAI31631049
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Liu, Guoer. $3 1479765
245 1 0 $a Why Automated Data Is Biased : $b The Politics of Air Quality Data in China.
264 0 $c 2024
300 $a 1 online resource (171 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
500 $a Advisor: Gallagher, Mary;Shipan, Charles.
502 $a Thesis (Ph.D.)--University of Michigan, 2024.
504 $a Includes bibliographical references
520 $a Why do biases exist in government-produced data, even when the collection of that data is automated? I argue that these biases are not an outcome of agents' manipulation for personal gains, but an equilibrium that emerges from the strategic interaction between policymakers and agents, both benefiting from this arrangement. Particularly in authoritarian contexts, the accuracy of automated data can be compromised by the risk of uncovering information that undermines the regime's legitimacy. This tension between accuracy and favorability aligns the interests of political actors across and within the government hierarchy, transforming automation technology intended for objective monitoring into an instrument that obscures reality. Focusing on China's expansion of automatic ambient air quality monitoring from 2012 to 2022, I develop a game-theoretical model and present empirical evidence demonstrating how political actors strategically deploy the physical infrastructure essential for automated data collection. This analysis demonstrates that such strategic deployments compromise data accuracy even before the collection process begins. Departing from the classic principal-agent approach to biased data, this analysis emphasizes that political principals may actually implicitly endorse and propagate automated data that, while inaccurate, portrays the regime positively. This research contributes to our understanding of automated data more broadly: as technology and society progress, politically motivated data biases adapt and evolve, rather than disappear. Automatically generated data is yet another sleek end product of complex and sometimes messy upstream political processes.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Public administration. $3 562473
650 4 $a Environmental science. $3 1179128
650 4 $a Political science. $3 558774
653 $a Biased government data
653 $a Automated data
653 $a Air pollution China
653 $a Air quality
653 $a Political processes
655 7 $a Electronic books. $2 local $3 554714
690 $a 0615
690 $a 0768
690 $a 0501
690 $a 0617
690 $a 0474
710 2 $a University of Michigan. $b Political Science. $3 1183106
710 2 $a ProQuest Information and Learning Co. $3 1178819
773 0 $t Dissertations Abstracts International $g 86-03B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31631049 $z click for full text (PQDT)