Earlier this week, someone asked me if I would help get the word out about a book they thought should be banned from our public school libraries. “Pornographic,” I believe was the accusation. I didn’t endorse the message, but it did leave me wondering: what makes a book bannable? And what impact do all of these cries for censoring books actually have?

Links to resources:

• American Library Association (ALA)
• ALA Office for Intellectual Freedom (OIF)
• Banned Books Lists, 2001-2020

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If you happened to have listened to the episode last week, I was talking about when to take our masks off. You may remember me saying something like “these assumptions may change” or “take them off after your entire household is vaccinated.”

Well...assumptions changed. Let's go visit Battle Station: Omicron.

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After a year and a half of shutdowns, quarantines, and other public drama, we're still waiting for a collective answer to the question that affects us the most in our daily lives: When can I take off this mask?

Bad Data doesn't have a definitive answer for you on that one, but can provide at least one person's assumptions and position on when. 

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Take a brief trip through history as we look back 1, 10, 50, and 100 years at how diseases, vaccines, politics, and technology have evolved and impacted our lives.

"The past does not repeat itself, but it rhymes." -Mark Twain

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(NOTE: this is a clean / non-explicit version of the original Episode 6.)

Among the thousands of various local government positions up for grabs, nearly 400,000 students are at risk of having their school boards turned upside-down by one political action committee. Don’t believe me? Let’s follow the money.

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Among the thousands of various local government positions up for grabs, nearly 400,000 students are at risk of having their school boards turned upside-down by one political action committee. Don’t believe me? Let’s follow the money.

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There is so much data orbiting each of us. And it all carries on a life of its own, propelled by some kind of digital momentum. But your absolute final piece of data - your cause of death - is riddled with errors...and always has been. Why?

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This week's (shorter-than-usual) episode walks through some quick mental math on what "normal" looks like in a year, what that costs us in dollars and souls, and what we earn in return.

As always, check out the Bad Data dashboards at: https://baddatapod.com/category/dashboards

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This week, the FDA and CDC both approved third booster shots for the Pfizer COVID vaccine (Comirnaty). They did it in different ways, though, with slightly different schedules for who should be eligible. Bad Data hosts a conversation with Dr. J.J. De Simone, a statistician and data scientist, about what it all means.

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Behind every sexy data journalist making fancy infographics, supporting every data scientist and their mystical machine learning algorithms, there is an underappreciated data engineer. Somebody that keeps the data-lights on at night.

In this episode, we explore the messy underbelly of public COVID data dashboards and try to compare what's going on between school districts in Kansas, California, Arizona, Texas, Louisiana, and others. (hot tip: ¯\_(ツ)_/¯ )

Resource Links:

• Johnson County, KS Public School COVID Dashboard
• Blue Valley School District COVID Dashboard
• Multi-State Public School COVID Benchmark Dashboard

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