The Columbia Journalism Review has been assembling a national map showing “news deserts” around the United States. It’s utterly fascinating. In some states, like Nebraska, nearly half the state does not have a daily newspaper (or hasn’t reported one). How does that impact voting? Civic engagement? The sharing of local and beyond-local information among fellow citizens? What questions are raised when you look at it?
Angie Oehrli, Tyler Hoff, and I shared a poster at ALA in which we selected some of the many data literacy strategies we’ve been working on with our team and discussed their application in helping people gain comprehension strategies to suss out fake news.
A screenshot of our poster is below. You can view a low-resolution version of our poster (<1MB in file size) here or the whopping full-resolution version (79MB!) here.
As an added bonus, our side project of creating the new 8-book series Data Geek for Cherry Lake Publishing got to show off a bit. This series, inspired by the the themes of this project (but not supported with grant funds), got its premiere at ALA!
In fact, we’ll be giving out a series set to someone after each of the eight sessions at our second 4T Virtual Conference on Data Literacy. This free event (free SCECH for Michigan educators) is coming up July 20-21. And we have another special prize for all attendees that we’re keeping under wraps for now, but we know you’ll want one! Visit our conference page to register.
Thanks to all who attended our session — we enjoyed the conversation!
(Note: this post first appeared at the Active Learning blog.)
First things first. You may have heard of the opioid crisis, but what is an opioid? I was surprised that when I went looking for a list of which prescription drugs are classed as opioids, it was somewhat tricky to find (my hypothesis is that some people know there’s an opioid crisis but don’t know that drugs like Percocet, morphine,OxyContin, and Vicodin are opioids, leading me to suspect that part of the problem is that some patients don’t realize that the drug they just got is an opioid).
Here’s what WebMD says:
OK, now that we’ve got that background knowledge, let’s look at how visualizations about opioid prescriptions and fatalities in Michigan can yield some fascinating (albeit sobering) insights.
Julie Mack, with some graphics by Scott Levin, has a sobering article in MLive showing how opioid death has spiked in past years. In many counties, there were more opioid prescriptions written in 2015 than there were residents. (Of course, if opioids are dosed one month at a time, one resident’s year-long prescribed use would count as 12, right?)
One thing that really jumped out to me was the power of visualization via the two state maps at the bottom of the article.
The first colors counties according to which have higher rates of opioid prescriptions being written. Keep an eye on the Detroit area (southeastern corner).
Now take a look at the second one, ranking counties according to number of deaths per 100K residents:
Are you still keeping an eye on Detroit? Notice how the death rate is highest in that area even though the prescription rate is among the lowest. (I do wish that instead of min/max, there were intervals marked instead, perhaps correlating the color scale according to the national death rates from opioids or something.)
This map helps us instantly see that there isn’t a natural mapping of higher prescription rates to higher death rates. As a result, it’s easy to have questions arise. Imagine discussing this with students:
- How is the death rate higher even if the prescription rate is lower? Where are the drugs coming from?
- Based on what you see here, which counties should the state of Michigan’s public health services target for interventions? Which kinds of interventions would be suitable given the prescription and death rate maps?
- What recommendations would you make for your own county?
- What additional information would you need to be able to answer these questions?
Looking for datasets? You might like exploring USAFacts.org, the philanthropical project from former Microsoft chief executive Steve Ballmer.
From The New York Times:
He sought to “figure out what the government really does with the money,” Mr. Ballmer said. “What really happens?”
In late April. he launched a public database developed with economists, professors, and others.
The database (USAFacts) is perhaps the first nonpartisan effort to create a fully integrated look at revenue and spending across federal, state and local governments.
Want to know how many police officers are employed in various parts of the country and compare that against crime rates? Want to know how much revenue is brought in from parking tickets and the cost to collect? Want to know what percentage of Americans suffer from diagnosed depression and how much the government spends on it? That’s in there. You can slice the numbers in all sorts of ways …
In an age of fake news and questions about how politicians and others manipulate data to fit their biases, Mr. Ballmer’s project may serve as a powerful antidote. Using his website, USAFacts.org, a person could look up just about anything … At the very least, it could settle a lot of bets made during public policy debates at the dinner table.
“I would like citizens to be able to use this to form intelligent opinions,” Mr. Ballmer said. “People can disagree about what to do — I’m not going to tell people what to do.” But, he said, people ought to base their opinions “on common data sets that are believable” …
“You’ve got to look at federal, state and local together,” Mr. Ballmer said …
With an unlimited budget, he went about hiring a team of researchers in Seattle and made a grant to the University of Pennsylvania to help his staff put the information together. Altogether, he has spent more than $10 million between direct funding and grants …
For Mr. Ballmer, the experience has been worth every cent simply for the surprises that he has discovered …
“How many people work for government in the United States?” he asked … “Almost 24 million. Would you have guessed that?”
“Then people say, ‘Those damn bureaucrats!’” Mr. Ballmer exclaimed …“Well, let’s look at that. People who work in schools, higher ed, public institutions of education — they are government employees.” And they represent almost half of the 24 million, his data shows.
(As a statistical benchmark, the entire U.S. population, including retirees, children and teens, and the unemployed, totals 325,000,000 … so 24 million is, even as a ballpark figure, around 10% of the total U.S. population.)
“And you say, O.K., what are the other big blocks?” Mr. Ballmer continued. “Well, active-duty military, war fighters. Government hospitals. Really? I didn’t know that.”
Suddenly, he explained, the faceless bureaucrats who are often pilloried as symbols of government waste start to look like the people in our neighborhood whom we’re very glad to have.
“Now people might not think they’re government employees, but your tax dollars are helping somehow to pay 24 million people — and most of these people you like,” Mr. Ballmer said …
Mr. Ballmer said he wanted the project to be completely apolitical. He has given money to candidates on both sides of the aisle …
One rule Mr. Ballmer said his team made early on was to use only government data — no outside providers — to avoid accusations of bias. But this created its own challenges.
For example, Mr. Ballmer, said: “You know it’s not legal to know how many firearms that are in this country? The government is not allowed to collect the number.”
There is data for the number of firearms manufactured, licenses, inspections, “along with other data, but not a total,” he said. “I can’t show it! I’m shocked! But the N.R.A. apparently has lobbied in such a way government can’t report the data.”
Take it for a spin at https://www.usafacts.org .
Thank you to Carli Spina and School Library Journal for featuring the work of our project alongside that of Eleanor Tutt and her team at Carnegie Library of Pittsburgh and Catherine d’Ignazio and Samantha Viotty of Emerson College’s Engagement Lab. From Spina’s article:
Data is all around us, from the output of your Fitbit to interactive maps that track voters to the latest visualization of the New York Times front page. With the rise of mobile devices and wearable technology, data is more available to general audiences, and the amount being generated has also exploded …
One reason data literacy is vital is that “[i]n what some are calling a ‘post-truth world,’ students seem to focus on numbers a lot,” says Jo Angela Oehrli, learning librarian/children’s literature librarian at the University of Michigan Libraries. Students believe that if a number is connected to information, “it has to be a fact. But numbers are manipulated all of the time….We want students to have a tool kit of questions that they can use to question the data that is out there.”
To this end, Oehrli and Kristin Fontichiaro, clinical associate professor at the University of Michigan School of Information, have been leading an IMLS-funded project called Supporting Librarians in Adding Data Literacy Skills to Information Literacy Instruction. Through data literacy programs and data science training, librarians can ensure that students develop the skills to question and interpret data in the news or that they generate through their day-to-day activities. They might even set some students on the path toward a career in the expanding field of data science …
There are many resources that support teaching data literacy, no matter your background …
All of these tools can serve as the basis of a larger conversation about the role of data in public discussions, such as the way that schools use student data to make curriculum decisions or how local governments track traffic data to make decisions about signage and stoplights, and what questions students should ask when they encounter data and visualizations in their daily lives.
For those who want to go even further, the University of Michigan initiative Supporting Librarians in Adding Data Literacy Skills to Information Literacy Instruction has brought together a group of data and curriculum design experts to create professional development resources for librarians.
The team has also written two books due out this fall, Creating Data Literate Students, which collects chapters by the curriculum experts on teaching data literacy in the classroom, and Data Literacy in the Real World: Conversations and Case Studies (both Maize Books), which will collect approximately 40 case studies about data literacy. The duo is also presenting a poster about their work, “Real Strategies to Address Fake News: Librarians, Data Literacy, and the Post-Truth World,” at the 2017 ALA Annual Conference this month.
The overarching message from all and other data initiatives? Don’t be scared by it. The goal is that “high school librarians will start to feel comfortable talking about data literacy issues with their students and fellow teachers,” Oehrli says.
“So many librarians were humanities majors with little exposure to data, and so many classroom teachers think of data in terms of test scores,” adds Fontichiaro. “By focusing on high-impact strategies, we want librarians and teachers to feel empowered by data, not victimized by it. Our early efforts show that a little knowledge has significant impact.”
You can read the entire article here. By the way, you can catch Catherine and Sam’s presentation on the easy-to-use data analysis tools at http://databasic.io if you tune into the closing keynote of the 4T Data Literacy Conference on Friday, July 21. Check out the schedule and register here!
Have you ever wondered why individual stores want you to download your app or why there is free Wifi in stores? It’s all part of a sophisticated plan to learn more about you, where you are, what you are interested in, and how stores can increase loyalty and spending in their brick-and-mortar and online portals.
Joseph Turow’s The Aisles Have Eyes: How Retailers Track Your Shopping, Strip Your Privacy, and Define Your Power (Yale University Press, 2017) is a wake-up call for consumers and an insight into how Big Data is transforming shopping experiences for stores and shoppers alike … often without the shopper’s awareness. Under the guise of offering you special discounts, loyalty points, or other customer-facing rewards, the behind-the-scenes data sets are staggeringly large.
Don’t be put off by the book’s academic publisher; the content is compelling, and the writing is reader-friendly. Highly recommended.
Ironically, when I went looking online for a book cover for this post, I discovered that you can buy the book at Wal-Mart, the corporation many say has the most sophisticated set of customer and inventory data anywhere.
Interested in how to combat Fake News? Check out Library Journal’s upcoming workshop series June 6 – 20, featuring our project team member Angie Oehrli!
Libraries are one of the few institutions that most Americans still trust. In polarized times, they can serve as nonpartisan, non-judgmental sources of accurate information—and, just as important, help users learn to evaluate the information they encounter every day. Claims of “fake news” have vaulted once-dry information literacy into the spotlight. To seize the teachable moment, this online course will offer up-to-date tools and effective tactics to enable patrons to critically assess sources, facts, and context.
Over the course of three weeks, participants will listen in on live keynote sessions and receive personal attention and resources from a dedicated advisor in an online coaching environment. Participate in online discussion groups, where you can share and gather resources and best practices and with peers from across the country.
We’re flashing back this week to Jodi Kantor’s New York Times story on Uber from a few weeks ago to bring up an example of how we might discuss ethics and data use, one of this year’s themes, with our students. A short sample from the article:
“The whole thing is like a video game,” said Eli Solomon, a veteran Uber and Lyft driver in the Chicago area, who said he sometimes had to fight the urge to work more after glancing at his data.
Sometimes the so-called gamification is quite literal. Like players on video game platforms such as Xbox, PlayStation and Pogo, Uber drivers can earn badges for achievements like Above and Beyond (denoted on the app by a cartoon of a rocket blasting off), Excellent Service (marked by a picture of a sparkling diamond) and Entertaining Drive (a pair of Groucho Marx glasses with nose and eyebrows).
Of course, managers have been borrowing from the logic of games for generations, as when they set up contests and competition among workers. More overt forms of gamification have proliferated during the past decade. For example, Microsoft has used the approach to entice workers to perform the otherwise sleep-inducing task of software debugging.
But Uber can go much further. Because it mediates its drivers’ entire work experience through an app, there are few limits to the elements it can gamify. Uber collects staggering amounts of data that allow it to discard game features that do not work and refine those that do. And because its workers are contractors, the gamification strategies are not hemmed in by employment law.
Kevin Werbach, a business professor who has written extensively on the subject, said that while gamification could be a force for good in the gig economy — for example, by creating bonds among workers who do not share a physical space — there was a danger of abuse. “If what you’re doing is basically saying, ‘We’ve found a cheap way to get you to do work without paying you for it, we’ll pay you in badges that don’t cost anything,’ that’s a manipulative way to go about it,” he said.
For some drivers, that is precisely the effect. Scott Weber said he drove full time most weeks last year, picking up passengers in the Tampa area for both Uber and Lyft, yet made less than $20,000 before expenses like gas and maintenance. “I was a business that had a loss,” said Mr. Weber, who is looking for another job. “I’m using payday loans.”
Still, when asked about the badges he earns while driving for Uber, Mr. Weber practically gushed. “I’ve got currently 12 excellent-service and nine great-conversation badges,” he said in an interview in early March. “It tells me where I’m at.”
To explore this with students, you might ask:
- What are the ethical principles underlying Uber’s practice toward drivers?
- What ethical principles do you assume that your future employer might have?
- How does this article impact your interest in using Uber (and how might your age — if you are not old enough to have a driver’s license — affect your answer)?
- How does gamification motivate you?
- Do you think drivers know Uber is gamifying its app with them? How do you feel about that?
If you’re like me, you’re watching the both sides of the Congressional healthcare debates sling statistics, money, and tweets at one another. So I found last month’s mapped visualization by Axios to be mesmerizing in the way that it did one thing very well: show how the rate of uninsured Americans shifted under Obamacare/the Affordable Care Act. It doesn’t discuss issues of federal costs, personal expenses, or caliber of coverage, but it does a great job of showing one shifting variable over time: percentage of people with some sort of health insurance versus those with none at all.
The screengrab below shows a static image, but click through to the Axios site so you can see the interactive GIF and see the colors change across time.
Then ask yourself some data viz questions:
- Axios’ graphic measures by county. How might this look different if it measured by state?
- How does the color palette influence how you feel about the data? Would more emotional colors like blood-red impact your interpretation?
- Can you track back to the original data source (a division of the U.S. Census) and try out these questions?