Libri sul tema "Bias mitigation"

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1

Li, Junfeng. Jian huan qi hou bian hua: Yuan ze, mu biao, xing dong ji dui ce. 8a ed. Beijing Shi: Zhongguo ji hua chu ban she, 2011.

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2

Chen, Junwu. Zhongguo zhong chang qi tan jian pai zhan lüe mu biao yan jiu. 8a ed. Beijing Shi: Zhongguo shi hua chu ban she, 2012.

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3

Hu, Angang. Zhongguo ying dui quan qiu qi hou bian hua. 8a ed. Beijing: Qing hua da xue chu ban she, 2009.

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4

Shi, Xinfeng. Qi hou bian hua yu di tan jing ji. 8a ed. Beijing Shi: Zhongguo shui li shui dian chu ban she, 2010.

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5

Wu, Shaohong. Zhongguo zong he qi hou bian hua feng xian. 8a ed. Beijing: Ke xue chu ban she, 2011.

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6

Yang, Deping. Zhongguo di tan zheng ce xi tong gou jian yan jiu: Zhu ti, gong ju yu bian qian. 8a ed. Beijing Shi: Jing ji ke xue chu ban she, 2016.

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7

Zhenqing, Sun. Feng zhi mu biao xia Zhongguo di tan fa zhan lu jing xuan ze yan jiu: Yi Tianjin wei li. 8a ed. Beijing Shi: Ren min chu ban she, 2016.

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8

Xu, He. Qi hou bian hua xin shi jiao xia de Zhongguo zhan lüe huan jing ping jia: Integrating the Climate Change Issues into Strategic Environmental Assessment in China. 8a ed. Beijing: Ke xue chu ban she, 2013.

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9

Shi, Wenzhen. WTO, qi hou bian qian yu neng yuan. 8a ed. Taibei Shi: Yuan zhao chu ban you xian gong si, 2013.

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10

Li, Jianping. "Tan jin" shi dai: Quan qiu bian nuan, wo men ru he yu huo chong sheng. 8a ed. Beijing: Zhongguo huan jing ke xue chu ban she, 2010.

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11

Xing, Jijun. Di tan jing ji bao gao: Yi ge shi jie xing de yi ti, zheng zai gai bian ni wo de sheng huo. Beijing Shi: Dian zi gong ye chu ban she, 2010.

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12

Xing, Jijun. Di tan jing ji bao gao: Yi ge shi jie xing de yi ti, zheng zai gai bian ni wo de sheng huo. Beijing Shi: Dian zi gong ye chu ban she, 2010.

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13

Qiu, Baoxing. Jian gu li xiang yu xian shi: Zhongguo di tan sheng tai cheng shi zhi biao ti xi gou jian yu shi jian shi fan chu tan. 8a ed. Beijing: Zhongguo jian zhu gong ye chu ban she, 2012.

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14

Wang, Feng. Zhongguo jing ji di tan zhuan xing zhong shi xian tan qiang du mu biao de zheng ce ji xiao ping gu: ZHONGGU JINGJI DITAN ZHUANXINGZHONG SHIXIAN TANQIANGDU MUBIAO DE ZHENGCE JIXIAO PINGGU. 8a ed. Beijing Shi: Jing ji ke xue chu ban she, 2013.

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15

Gong, Wei. Fa zhan quan shi jiao xia de qi hou bian hua guo ji fa yan jiu: Studies on international climate law from the perspective of the right to development. 8a ed. Beijing Shi: Fa lü chu ban she, 2013.

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16

Daier. Qi hou zhan zheng: Jue ding quan ren lei ming yun de zui hou yi chang zhan yi. 8a ed. Taibei Shi: Cai xin chu ban, 2009.

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17

Zhuang, Guiyang. Di tan jing ji: Qi hou bian hua bei jing xia Zhongguo de fa zhan zhi lu = How will China move towards a low carbon economy? 8a ed. Beijing Shi: Qi xiang chu ban she, 2007.

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18

Mi, Hong. Qi hou bian hua yu ren kou an quan: Climate change and population security. 8a ed. Beijing: Zhongguo she hui ke xue chu ban she, 2012.

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19

Kang, Xiao. Qi hou bian hua quan qiu zhi li yu Zhongguo jing ji zhuan xing: Guo ji gui fan guo nei hua de shi jiao = Global Governance of Climate Change and China's Economic Transition : From the Perspective of Internalization of International Norms. 8a ed. Guangzhou: Shi jie tu shu chu ban gong si, 2014.

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20

Zhao, Chunming. Di tan jing ji huan jing xia Zhongguo dui wai mao yi fa zhan fang shi zhuan bian yan jiu: The study on transformation of China's foreign trade development mode at low-carbon economic environment. 8a ed. Beijing Shi: Ren min chu ban she, 2014.

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21

Wang, Ru. Di tan jing ji shi jiao xia de di fang zheng fu zheng ji zhi biao ti xi yan jiu: Performance Index System of Local Governments in view of Low Carbon Economy. 8a ed. Beijing Shi: Guo jia xing zheng xue yuan chu ban she, 2012.

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22

Wang, Ke. Ji yu CGE de ji shu bian hua mo ni ji qi zai qi hou zheng ce fen xi zhong de ying yong: Technological change simulation and its application in climate change policy analysis based on a CGE model. 8a ed. Beijing: Zhongguo huan jing ke xue chu ban she, 2011.

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23

Whitesmith, Martha. Cognitive Bias in Intelligence Analysis. Edinburgh University Press, 2020. http://dx.doi.org/10.3366/edinburgh/9781474466349.001.0001.

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Abstract (sommario):
Belief, Bias and Intelligence outlines an approach for reducing the risk of cognitive biases impacting intelligence analysis that draws from experimental research in the social sciences. It critiques the reliance of Western intelligence agencies on the use of a method for intelligence analysis developed by the CIA in the 1990’s, the Analysis of Competing Hypotheses (ACH). The book shows that the theoretical basis of the ACH method is significantly flawed, and that there is no empirical basis for the use of ACH in mitigating cognitive biases. It puts ACH to the test in an experimental setting against two key cognitive biases with unique empirical research facilitated by UK’s Professional Heads of Intelligence Analysis unit at the Cabinet Office, includes meta-analysis into which analytical factors increase and reduce the risk of cognitive bias and recommends an alternative approach to risk mitigation for intelligence communities. Finally, it proposes alternative models for explaining the underlying causes of cognitive biases, challenging current leading theories in the social sciences.
24

Kenski, Kate. Overcoming Confirmation and Blind Spot Biases When Communicating Science. A cura di Kathleen Hall Jamieson, Dan M. Kahan e Dietram A. Scheufele. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190497620.013.40.

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Abstract (sommario):
This chapter focuses on two biases that lead people away from evaluating evidence and scientific studies impartially—confirmation bias and bias blind spot. The chapter first discusses different ways in which people process information and reviews the costs and benefits of utilizing cognitive shortcuts in decision making. Next, two common cognitive biases, confirmation bias and bias blind spot, are explained. Then the literature on “debiasing” is explored. Finally, the implications of confirmation bias and bias blind spot in the context of communicating about science are examined, and an agenda for future research on understanding and mitigating these biases is offered.
25

Mink, John. Forecasting with Out-Liars: Mitigating Blame, Bias, and Apathy in Your Planning Process to Drive Meaningful and Sustainable Financial Improvements. Mindstir Media, 2021.

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26

Sandis, Elizabeth. Early Modern Drama at the Universities. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192857132.001.0001.

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Abstract (sommario):
This is the first history of Oxford and Cambridge drama in the Tudor and Stuart period. It guides the reader through the theatrical experiences of students at university in early modern England, following them on the journey from schoolboys to scholars to graduates in the workplace. Early Modern Drama at the Universities is structured to make the subject as accessible as possible, mitigating the difficulties of this sizeable and complex body of evidence. The hundreds of plays we have inherited from Oxford and Cambridge are steeped in Classical culture, and the academic establishment’s bias against print culture means that most evidence remains in manuscript form. Opening up these plays to a wider readership, this study carves three main roads into the corpus, introducing key institutions, intertexts, and individuals. For the first time we can see the extent to which institutional culture made the drama what it is: pedagogically-inspired, homosocial, and self-reflexive. Early Modern Drama at the Universities argues that it was primarily on a college level that students lived, worked, and proved themselves to the community, and that if we are to understand university drama as a whole, we must create it from the building blocks of individual college histories.

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