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内容由Citations Needed, Nima Shirazi, and Adam Johnson提供。所有播客内容(包括剧集、图形和播客描述)均由 Citations Needed, Nima Shirazi, and Adam Johnson 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal
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Episode 162: How the "Data-Driven" Label Sanitizes Cruel Austerity Politics

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内容由Citations Needed, Nima Shirazi, and Adam Johnson提供。所有播客内容(包括剧集、图形和播客描述)均由 Citations Needed, Nima Shirazi, and Adam Johnson 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

“Follow The Data” is the name of a Bloomberg Philanthropies podcast that debuted 2016. “How Data Analysis Is Driving Policing,” a 2018 NPR headline read. “Data suggests that schools might be one of the least risky kinds of institutions to reopen,” an opinion piece in The Washington Post told us in the early days of the Covid-19 pandemic.

Over the last 20 or so years, a trend of labeling concepts as “data-driven” emerged. It applied, and continues to apply, to policies affecting everything from education to public health, policing to journalism. Decisions affecting these areas will be more thoughtful, the idea goes, when informed and supported by data. In many ways, this has been a welcome development: The idea that a rigorously scientific collection of information via surveys, observation, and other methods would make policies and media stronger seems unimpeachable.

But this isn’t always the case. While gathering “data” is a potentially beneficial process, the process alone isn’t inherently good, and is too often used to obscure important and requisite value-based or moral questions, assert contested ideological priors and traffic in right-wing austerity premises backed by monied interests. When our media tell us a largely unpopular, billionaire-backed idea like school privatization, “targeted” policing, or tax incentive handouts to corporations have merit they’re backed by “the data,” what purpose does this framing serve? Where does the data come from? Who is funding the data gathering? What data are we choosing to care about and, most important of all, what data are we choosing to ignore?

On today’s episode, we’ll look at the development of the push to make everything data-driven, examining who defines what counts as “data,” which forces shape its sourcing and collection, and how the fetishization of “data” as something that exists outside and separate from politics is more often than not, less a methodology for determining truth and more a branding exercise for neoliberal ideological production and reproduction.

Our guests: Abigail Cartus is an epidemiologist at Brown University. She focuses on perinatal health and overdose prevention in her work at The People, Place & Health Collective, a Brown School of Public Health research laboratory.

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Manage episode 330394568 series 1500148
内容由Citations Needed, Nima Shirazi, and Adam Johnson提供。所有播客内容(包括剧集、图形和播客描述)均由 Citations Needed, Nima Shirazi, and Adam Johnson 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

“Follow The Data” is the name of a Bloomberg Philanthropies podcast that debuted 2016. “How Data Analysis Is Driving Policing,” a 2018 NPR headline read. “Data suggests that schools might be one of the least risky kinds of institutions to reopen,” an opinion piece in The Washington Post told us in the early days of the Covid-19 pandemic.

Over the last 20 or so years, a trend of labeling concepts as “data-driven” emerged. It applied, and continues to apply, to policies affecting everything from education to public health, policing to journalism. Decisions affecting these areas will be more thoughtful, the idea goes, when informed and supported by data. In many ways, this has been a welcome development: The idea that a rigorously scientific collection of information via surveys, observation, and other methods would make policies and media stronger seems unimpeachable.

But this isn’t always the case. While gathering “data” is a potentially beneficial process, the process alone isn’t inherently good, and is too often used to obscure important and requisite value-based or moral questions, assert contested ideological priors and traffic in right-wing austerity premises backed by monied interests. When our media tell us a largely unpopular, billionaire-backed idea like school privatization, “targeted” policing, or tax incentive handouts to corporations have merit they’re backed by “the data,” what purpose does this framing serve? Where does the data come from? Who is funding the data gathering? What data are we choosing to care about and, most important of all, what data are we choosing to ignore?

On today’s episode, we’ll look at the development of the push to make everything data-driven, examining who defines what counts as “data,” which forces shape its sourcing and collection, and how the fetishization of “data” as something that exists outside and separate from politics is more often than not, less a methodology for determining truth and more a branding exercise for neoliberal ideological production and reproduction.

Our guests: Abigail Cartus is an epidemiologist at Brown University. She focuses on perinatal health and overdose prevention in her work at The People, Place & Health Collective, a Brown School of Public Health research laboratory.

  continue reading

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