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How a Company You’ve Never Heard of Sends You Letters about Your Medical Condition

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In the summer of 2015, Alexandra Franco got a letter in the mail from a company she had never heard of called AcurianHealth. The letter, addressed to Franco personally, invited her to participate in a study of people with psoriasis, a condition that causes dry, itchy patches on the skin.

Franco did not have psoriasis. But the year before, she remembered, she had searched for information about it online, when a friend was dealing with the condition. And a few months prior to getting the letter, she had also turned to the internet with a question about a skin fungus. It was the sort of browsing anyone might do, on the assumption it was private and anonymous.

Now there was a letter, with her name and home address on it, targeting her as a potential skin-disease patient. Acurian is in the business of recruiting people to take part in clinical trials for drug companies. How had it identified her? She had done nothing that would publicly associate her with having a skin condition.

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When she Googled the company, she found lots of people who shared her bewilderment, complaining that they had been contacted by Acurian about their various medical conditions. Particularly troubling was a parent who said her young son had received a letter from Acurian accurately identifying his medical condition and soliciting him for a drug trial—the first piece of mail he’d had addressed to him besides birthday cards from family members.

Acurian has attributed its uncanny insights to powerful guesswork, based on sophisticated analysis of public information and “lifestyle data” purchased from data brokers. What may appear intrusive, by the company’s account, is merely testimony to the power of patterns revealed by big data.

“We are now at a point where, based on your credit-card history, and whether you drive an American automobile and several other lifestyle factors, we can get a very, very close bead on whether or not you have the disease state we’re looking at,” Acurian’s senior vice president of operations told the Wall Street Journal in 2013.

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Yet there’s some medical information that Acurian doesn’t have to guess about: The company pays Walgreens, which uses a privacy exemption for research, to send recruitment letters to its pharmacy customers on Acurian’s behalf, based on the medications they’re using. Under this arrangement, Acurian notes that it doesn’t access the medical information directly; the customers’ identities remain private until they respond to the invitations.

And that is not the entire story. An investigation by the Special Projects Desk has found that Acurian may also be pursuing people’s medical information more directly, using the services of a startup that advertises its ability to unmask anonymous website visitors. This could allow it harvest the identities of people seeking information about particular conditions online, before they’ve consented to anything.

A letter sent out to a Walgreens customer in Connecticut on Acurian’s behalf. It invited her to visit a generic sounding website for people with pulmonary disease. At the time, she had a prescription from Walgreens for asthma.

If you’re suddenly thinking back on all of the things you’ve browsed for online in your life and feeling horrified, you’re not alone.

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AcurianHealth has created dozens and dozens of generic sounding websites for the trials they’re recruiting for: www.trialforCOPD.com, www.studiesforyourarthritis.com, and www.kidsdepressionstudy.com are a few examples of the many websites they own. The sites all feature stock images of people in distress, sometimes include AcurianHealth’s logo, and include promises of up to $1,000 for participating, depending on the study.

An example of one of the Acurian sites, www.sleepapneastudies.com

Out of view, some of these sites include something else: code from a company called NaviStone—which bills itself as a specialist in matching “anonymous website visitors to postal names and addresses.” So if a person is curious about one of those letters from Walgreens, or follows one of Acurian’s online ads, and visits one of Acurian’s generic disease-specific sites, their identity could be discovered and associated with the relevant condition.

NaviStone says it can send personalized mail to anonymous website visitors with a day or two of their visit.

This tracking function undermines what’s supposedly a formal separation between Walgreens customer data and Acurian’s recruitment. If Walgreens sends out a bunch of letters to customers taking certain medications, and those customers then visit the generic website controlled by Acurian provided in the letter, Acurian can infer its wave of new visitors are taking those medications—and, if NaviStone delivers on its promise to identify visitors, Acurian can see who they are.

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Walgreens gives itself permission to use customers’ health information for “research” purposes, which would include clinical trials, in its privacy policy. It’s been working with Acurian since at least 2013, and in 2015, Walgreens announced it was “leveraging” its 100 million customer database to recruit patients directly for five major drug companies.

When asked about its partnership with Acurian, Walgreens spokesperson Scott Goldberg pointed me to a Walgreens FAQ page about clinical trials. It states that Walgreens doesn’t share health information with third parties without permission, but that a third party may “receive your information if you contact the web-site and/or toll-free number in the letter to seek more information about the clinical trial.”

The question is whether users will know that one of Acurian’s websites has received their information—even if they haven’t necessarily agreed to submit it. NaviStone, an Ohio-based business spun out from the marketing firm CohereOne last year, claims to be able to identify between 60 and 70 percent of anonymous visitors to the websites that use its services.

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When we contacted the firm last month to ask how it does this, Allen Abbott, NaviStone’s chief operating officer, said by phone that talking about how its technology works is “problematic.”

“A lot of our competitors would love to know how we made it work,” Abbott said. “We have an advantage that we would be silly to reveal.”

We asked whether the company had thought about the privacy implications involved in identifying people visiting a website for sensitive reasons, and whether there were certain customers the company wouldn’t work with.

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“Our business is almost entirely e-commerce, helping retailers sell to their customers,” he said. “There was one site that came into our radar that was adult-related material that we decided not to pursue.”

We then described what Acurian does.

“We don’t work with anyone like that,” he said.

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We explained that the call was because we’d found NaviStone’s code on AcurianHealth sites.

“It’s possible,” he then said. “We have a lot of customers.”

But Abbott insisted that NaviStone had found a “privacy compliant way” to identify anonymous website visitors—again saying he couldn’t describe it because it was a proprietary technology.

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When we analyzed the NaviStone code on Acurian’s sites, we found one way that NaviStone’s technology works: It collects information as soon as it is entered into the text boxes on forms, before the person actually agrees to submit it. When we typed a test email address in the “Join Us” page on Acurian’s site, it was immediately captured and sent to the company’s servers, even if we later chose to close the page without hitting the “Send” button on the form.

In fact, the information was collected before we got to the part of the form that said, “Your privacy is important to us. By selecting this box, you agree to our Privacy Policy and Terms of Use, and agree that we contact you by phone using automated technology or other means using the information you provided above regarding research studies.”

“If I haven’t hit send, what they seem to be doing almost seems like hacking,” said Lori Andrews, a law professor at the Chicago-Kent School of Law. “It’s similar to a keystroke tracker. That could be problematic for them.”

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Ryan Calo, a law professor at the University of Washington, said this clearly violates a user’s expectation of what will happen based on the design of the site. “It’s not that they lied to you with words, but they’ve created an impression and violated that impression,” said Calo who suggested it could violate a federal law against unfair and deceptive practices, as well as laws against deceptive trade practices in California and Massachusetts. A complaint on those grounds, Calo said, “would not be laughed out of court.”

When we followed up with NaviStone’s Abbott by email, he insisted that the company doesn’t send any data to Acurian.

“We don’t send any email for Acurian, or pass along any email addresses to them or use their email addresses in any way or manner,” said Abbott by email. “If we are indeed inadvertently collecting email addresses, we will fix immediately. It’s not what we do.”

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But when the Special Projects Desk reviewed dozens of other companies’ websites that were using NaviStone’s code, they were also collecting email addresses. After a month of repeated inquiries to NaviStone and to many of the sites using its code, NaviStone last week stopped collecting information on the site of Acurian and most of its other clients before the “Submit” button was pressed.

“Rather than use email addresses to generate advertising communications, we actually use the presence of an email address as a suppression factor, since it indicates that email, and not direct mail, is their preferred method of receiving advertising messages,” said Abbott by email. “While we believe our technology has been appropriately used, we have decided to change the system operation such that email addresses are not captured until the visitor hits the ‘submit’ button.”

Asked about its partnerships with Walgreens and NaviStone, Acurian declined to be interviewed.

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“As a general policy based on our confidentiality agreements with our business partners, I hope you will understand that Acurian does not discuss its proprietary business strategies,” said Randy Buckwalter, a spokesperson for PPD, the corporate parent of Acurian, by email.

Buckwalter told us Acurian would provide a fuller response to what is reported here, but never provided it.

Kirk Nahra, a partner at the law firm Wiley Rein who specializes in health privacy law, said there’s nothing really wrong with Walgreens sending out letters to customers on Acurian’s behalf. “But that second situation, where I go to look at the website and at that point they have some way of tracking me down, their ability to track me down at that point is troubling,” Nahra said.

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Nahra said there was a potential legal issue if the company fails to disclose this in its privacy policy, and that it could lead to a class action lawsuit. Acurian’s privacy policy only talks about getting information from “data partners” and collecting expected information from website visitors, such as IP addresses—which can be used to track someone from website to website, which is why it’s a good idea to use technology that obscures your IP address, such as Tor or a VPN.

The ability to identify who is sick in America is lucrative. Acurian offers a collection of case studies to potential customers in which it discloses what it bills: $4.5 million for recruiting 591 people with diabetes; $11 million for 924 people with opioid-induced constipation; $1.4 million for 173 teens with ADHD; and $6 million for 428 kids with depression.

Acurian claims to have a database of 100 million people with medical conditions that could be of interest to drug companies, and it says that all of those people have “opted-in” to be contacted about trials. In addition to internet complaints suggesting otherwise, the Federal Trade Commission has received more than 1,000 complaints over the last 5 years from consumers who say the company has contacted them without consent; some complainants also wanted to know how the company had found out about their medical conditions.

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Acurian has also faced a slew of class-action lawsuits in Florida, Texas, and California from plaintiffs who say the company had illegally robocalled them about clinical trials, placing multiple automated calls to their home without getting their permission first, a violation of federal law. Acurian denied wrongdoing in court filings, saying its calls are not commercial in nature and that the plaintiffs had opted in, but settled all the suits out of court.

Alexandra Franco certainly didn’t opt in to be contacted for clinical trials. She doesn’t have psoriasis or any prescriptions for a skin condition. When she looked back at her browsing history, it appeared that the only website she visited as part of her search was the mobile version of WebMD.com.

“While Acurian had purchased display advertising from WebMD in 2010, we have never hosted a program for them in which personal information was collected or shared,” said WebMD in a statement. “Under our Privacy Policy we do not share personal information that we collect with third parties for their marketing activities without the specific consent of the user. In this case, it appears that the user did not even provide any personal information to WebMD.”

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“Doing a search on your mobile device means you are incredibly re-identifiable,” said Pam Dixon of the World Privacy Forum, referring to the fact that a mobile device provides more unique identifiers than a computer typically does.

Franco doesn’t understand exactly how Acurian got her information, but said that the letter was sent to her home addressed to “Alex Franco,” a version of her name that she only uses when doing online shopping. When she sent an inquiry to Acurian, the company told her it got her name from Epsilon, a data broker, “based on general demographic search criteria.”

“Epsilon specializes in compiling mailing lists based on generally available demographic information like age, gender, proximity to a local clinical site and expressed interests,” said the company in an email. “We sincerely regret any distress you may have experienced in thinking your privacy may have been compromised, and we hope this letter has assured you that nothing of the kind has occurred.”

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Franco didn’t feel particularly assured. Epsilon lets consumers make a request to find out what information the data broker has on them; in response to her request, Epsilon told Franco by letter that it has her home address and information about her likely income, age, education level, and length of residence, as well as whether she has kids—none of which would seem to indicate dermatological issues.

At the end of our investigation, we still don’t know exactly how Franco was identified as possibly having a skin condition. Given the many players involved and the fact that we can’t see into their corporate databases means we can only make reasonable assumptions based on the outcome.

It’s the online privacy nightmare come true: a company you’ve never heard of scraping up your data trails and online bread crumbs in order to mine some of the most sensitive information about you. Acurian may try to justify the intrusion by saying it’s in the public interest to develop new drugs to treat illnesses. But tell that to the person shocked to get a letter in the mail about their irritable bowels.

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Yes, we found that person. Bret McCabe complained about it on Facebook. He got the letter in 2012 after regularly buying both anti-diarrhea medicine and laxatives at Walgreens and Rite-Aid for a family member dealing with chronic pain issues.

“The creep factor of the specificity is what I found particularly grating,” said McCabe by phone. “It’s one thing to get spam about erectile dysfunction or refinancing your car loan but in this case, it seemed like they specifically knew something about me. It was meant for me and me only.”

The privacy scholar Paul Ohm has warned that one of the great risks of our data-mined society is a massive “database of ruin” that would contain at least one closely-guarded secret for us all, “a secret about a medical condition, family history, or personal preference... that, if revealed, would cause more than embarrassment or shame; it would lead to serious, concrete, devastating harm.”

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Acurian has assembled one of those databases. As with all big databases, the information doesn’t even have to be accurate. So long as it gets enough of its letters to the right people, the recruitment company doesn’t need to care if its collection efforts misidentify Franco as a psoriasis patient or otherwise incorrectly link people, by name, to medical conditions they don’t have.

This is the hidden underside of the browsing experience. When you’re surfing the web, sitting alone at your computer or with your smartphone clutched in your hand, it feels private and ephemeral. You feel freed to look for the things that you’re too embarrassed or ashamed to ask another person. But increasingly, there is digital machinery at work turning your fleeting search whims into hard data trails.

The mining of secrets for profit is done invisibly, shrouded in the mystery of “confidential partnerships,” “big data,” and “proprietary technology.” People in databases don’t know that dossiers are being compiled on them, let alone have the chance to correct any mistakes in them.

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This story was produced by Gizmodo Media Group’s Special Projects Desk.

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notadoctor
37 days ago
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People mining
Oakland, CA
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satadru
13 days ago
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Don't use pharmacies at Walgreens.
New York, NY

Watson Mill - circle library, part 4

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Continuing work on the circle library.  With the ladder moved to the front wall, I now have 8 3/4" of library wall space not including the two vertical end boards that will close it on the sides.  I marked the final position of the center circle.  This gives me a bit of shelf space to the right but allows me more room on the left to play.  The left will be more visible anyway.   To build the shelves, I cut 1/8" wide channels in the plywood wall using the Dremel Trio.

Since I didn't trust the wall edges to be straight, I used a fence board clamped in place.

You can plunge cut with the Trio, which is a great feature.  You can start anywhere along your line.

The bit made a channel slightly too narrow, so I tapped the fence board with a rubber mallet for a second run, widening the final channel to the proper width needed to fit the 1/8" shelves.

The top channel is rough because there was something catching the bit in the wood and it was close to the edge.  Once the ceiling is in, I will add trim to enclose the top space to keep it from being a dust-catcher space that's difficult to clean, so the rough cut didn't matter much.  These might not be square to the floor or ceiling after the build is in place, but they are reasonably parallel to one another.

The channels provide a sturdy hold for each shelf cut from 1/8" basswood.  I started with 1" wide basswood strips and cut them down to end up with a roughly 3/4" deep shelf.   I hand cut the angles around the circle supports.  Not easy.  :\

The two end boards are slightly deeper than the shelves.  For the top, I cut a piece of 1/4" strip wood for stability for the eventual final trim. I still need to cut the support piece for the bottom of the circle, but I am tapped out for the night. :D

The space under the bottom shelf will be enclosed by trim or baseboard in the end, and I left a bit of clearance on the bottom for flooring thickness.

Next up, covering the plywood back between the shelves and cutting the mirror for the center.

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notadoctor
65 days ago
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skittone
65 days ago
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This is so, SO COOL. I love all of her work and I'm so glad she blogs the process.

RT @jaketapper: another tweetstorm worth reading tonight ----> twitter.com/samswey/status…

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another tweetstorm worth reading tonight ----> twitter.com/samswey/status…

I thought I understood racism and mass incarceration. But nothing prepared me for what I saw in Baton Rouge, Louisiana. (1/x)


Posted by samswey on Friday, May 19th, 2017 4:16pm


13563 likes, 12477 retweets

Posted by jaketapper on Saturday, May 20th, 2017 12:16am
Retweeted by SwiftOnSecurity on Saturday, May 20th, 2017 1:31am


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notadoctor
67 days ago
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The deficit model of STEM recruitment

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As we train the next generation of STEM professionals, we use a filter that selects against marginalized folks, on account of their ethnicity, income, gender, and other aspects of identity. This, I hope you realize, is an ethical and pragmatic problem, and constrains a national imperative to maintain competitiveness in STEM.

When we are working for equity, this usually involves working to remediate perceived deficiencies relative to the template of a well-prepared student — filling in gaps that naturally co-occur with the well-established inequalities that are not going away anytime soon. These efforts at mitigation are bound to come up short, as long as they’re based on our current Deficit Model of STEM Recruitment.

You might be familiar with the phrase “deficit model” in terms of science communication with the public. The “Information Deficit Model,” in a thimble, is about learning what the audience doesn’t know and then teaching stuff to fill in the gaps. When it comes to public outreach and informal science education, it doesn’t really work. Let me give an example.

Let’s say you meet someone who thinks global climate change isn’t a result of carbon pollution. You take a few minutes to explain the science, but out some graphs, and get them to read all of the evidence for anthropogenic climate change laid out crystal clear at the NASA Climate site. In the end, your pal won’t point out any technical errors, but also, won’t be convinced. It might seem bizarre, but you can give someone all of the facts in the world, and many folks won’t adjust their world view to accommodate these facts. The same story could be told for vaccines, evolution, the quality of education available in your public school district, and Russian manipulation of the White House. Even for more prosaic topics, like how osmosis works or what causes seasons, the deficit model doesn’t work that well in the long run.

For another example, here’s a story of mine about a guy who insisted that a snake was an ant. It’s funny, but also tragic. There’s no shortage of scholarship about how and why the deficit model is a recipe for failure in science communication.

We use another deficit model when we are working to diversify STEM, but this is something that doesn’t get much discussion.

When we recruit and select candidates for admission into graduate STEM programs, we look at what people have to offer, in terms of their talents, accomplishments, and potential. It’s standard to look at grades, scores, publications, and experiences. This approach, whether you look at it as a matter of addition or subtraction, involves identifying deficits and seeing whether holes need to be fixed and if we can fix them.

If a student is applying to your lab with a low-ish GPA and not as many publications as other students, you might think, “Well, there are legitimate reasons why their grades are lower than other students, and they haven’t had an opportunity to publish based on the opportunities available to them.” Which is a reasonable mindset. Some programs are committed to bringing in first-generation students and from underrepresented groups who have these “deficiencies,” though many are fighting over the small number of marginalized students who have managed to build a portfolio that rises above these structural disadvantages. When high-prestige institutions boast of their diversity, that’s typically a consequence of investment into finding and attracting people who fit their demographic desires but also lack the perceived quantitative and qualitative “deficits.”

This can fix the diversity problem for a single institution, but across the system, doesn’t move the needle whatsoever, it just takes these students away from other institutions that aren’t going to recruit them. The only way to change the system is to recruit students who, otherwise, would not be recruited. The underlying socioeconomic and cultural inequities that result in lower average metrics for members of underrepresented groups are not going to change overnight, so if we recruit the students from all groups who are most highest achieving — or least deficient — then we will continue to perpetuate our inequities.

The failure of this deficit model of STEM recruitment — rejecting individuals who fail to impress on the basis of their grades, scores, and such — is that there is no clear evidence that these metrics are cause success in STEM! Wherever you might see a correlation, there are more parsimonious causal explanations involving social capital.

The real drawback comes from our reliance on the Deficit Model of STEM Recruitment to prepare students from underrepresented groups to compete for space in the academy.

To avoid talking about this in abstract terms, let’s return briefly to the discussion about the lack of institutional diversity among the folks receiving NSF graduate fellowships (which I first discussed here). The upshot is that underrepresented minority (URM) students are disproportionately found in low-prestige regional public universities, such as my own, and that these students are getting an absurdly small piece of the pie. Instead, what we have is a larger scale version of the university-level phenomenon, of institutions supporting the fraction of URM students that have numbers on the par with their white competitors at higher-prestige institutions. Which won’t move the needle, because it’s won’t bring new people into the game who otherwise wouldn’t be in the game.

As I raised these concerns, all kinds of folks were like “whoah hold on wait a moment this is fair, it just reflects the composition of the applicant pool!” and I was like “Yeah, precisely, that’s the problem.”

At this moment, the standard approach to fixing this diversity problem is the Deficit Model — to fix the holes in the records of the applicants.

And so, I am told every day that my job is to fix holes in the applications of the students training in my lab, much like one would tell a CalTrans worker to fix potholes. I need to get my students to author first authored pubs so they can compete against undergrads from big labs where their names can readily get added to papers. I need to get my students tutoring to pull up their test scores and their grades so that they might have the same GPA and scores as well-heeled students who go to a school with far more resources, don’t work 30 hours per week, and come from a family that invested great resources into this sort of achievement for the past 20 years. I’m told I need to train my students how to act so that they fit in, so that other scientists can choose to view them as potential peers.

In other words, I need to fix my students so that they conform to the template that the system uses to identify future scientists. This template, though, is rigged against them.

This pretty much makes me sick, but yet, if I want my students to succeed, then this is what the system requires of me. If I’m training students to do great science, then that might mean that their grades would suffer. If I’m doing what it takes to get a students’ name on a paper, that might mean that I’m cutting corners on actual mentorship and developing the capacity of my students to work independently.

As a professor of URM students in an underfunded regional public university, the impossible is asked of me every day: I’m being asked to groom my students so that on paper, they look as if they are competitive to white students from wealthy universities on the basis of the template developed to evaluate these wealthy white students. What does success look like for me? When one of my amazing students squeaks through the system, given the benefit of the doubt, even though their numbers don’t match up. I’ve done pretty well at this, because I have no choice if I’m going to help my students, but the system as a whole is still failing my students.

Herein lies the problem with the Deficit Model of STEM Recruitment: No matter what kind of effort and resources are applied, there is no way that the average URM applicant from a regional public university is going to develop a record as competitive as the average non-URM candidate from a prestigious and well-funded small liberal arts college or major research institution. 

As long as we compare URM and first-generation students with metrics that have been used to evaluate students who have been handed more advantages in life, then we are always going to perpetuate the inequities we are trying to eliminate. At best, we can shrink the gap. However, after any efforts are applied to shrink that gap, then the wealthy institutions will invest even more into increasing that gap.

Let’s take another quick look at the NSF graduate fellowships. It turns out that, this year, they did a pretty good job of awarding fellowships. Grad students in STEM are 11% URM, but 25% of the fellowships went to URM students. That’s pretty darn good, right? Well, yes, and no. Why do I not think this is 100% peachy? Because take a look at the undergraduate institutions of the students that are landing these fellowships. They are, overwhelmingly, coming from higher-prestige institutions that have relatively low rates of minority enrollment, compared to less-prestigious institutions with less funding. In other words, fellowships are going to minority students, but they’re going to students who had already cracked the code of making their way into prestigious academic institutions. Would these students be going to a strong graduate program without this fellowship? That’s an important question to ask, and I don’t know the answer. Regardless, the underclass of talented students who didn’t make their way into prestigious universities — which is an environment that has much higher URM enrollment — remains nearly shut out of this kind of federal support. And please don’t fool yourself into thinking that students enrolled at at UCLA or Harvard or Pomona College are there because they are smarter or better or work harder than the students at my university.

Even if we keep giving support to URM students from prestigious institutions, we’ll always be playing a game of catchup. But let’s not be silly, we know that the entitled will keep their privileged access to resources for the common good. When we rely on metrics that are designed to evaluate people who succeed in the very system that they’ve developed, we’re enabling majoritarian rule.

When we evaluate students who have experienced systemic disadvantages using the metrics of those who don’t experience these systemic disadvantages, there will always be a deficit that we cannot fill, no matter what handicap we try to apply.

Whatever the system invents or develops something to help out the students who experience systemic biases and disadvantages, students with more social capital and money will be able to take advantage of those developments as well. There is no way that prestigious institutions would going to sit idly by if folks from non-prestigious institutions would equal them in access to publicly funded resources. We will not ever see the day that high-potential STEM students from universities like mine will will be getting funded admission to graduate programs at the same rate as high-potential students from Caltech or Harvey Mudd. But if such a magical day would ever come to pass, it would be to the outrage of many people at these prestigious places because it would mean that their status would have lost its currency. (Even allowing in a slightly higher proportion of minorities at a place like Harvey Mudd is causing some faculty to go apoplectic and say that the “quality of the students” is declining. Imagine how these people would react if brown people at “low quality” institutions ever got access to the same resources as their own “high quality” students? It’s okay for the disadvantaged to get support, but the elite want to make sure their students always a couple tiers higher. Just take a look at how people allocate their charitable giving to universities to see how this dynamic plays out.)

How can we possibly identify people who are prepared to succeed without using metrics that are part of the deficit model? Instead of finding the people who are least lacking, we can identify the people who have the goods. We can do this by getting to know people as actual human beings. If a student spends a substantial amount of time working with you, then you’ll know whether they have what it takes to succeed. A recruitment weekend won’t be enough, but maybe a few weeks in the lab is. Maybe a whole summer. We have spent many years trying to fix the system so that we can give a fair chance to people who deserve one, and we still keep coming up short. If we just continue with these minor tweaks, we won’t be getting anywhere.

If you want to truly diversify, then we need to stop trying to fill in the holes based on perceived deficiencies. Instead, we need to focus on training complete scientists. We need to fundamentally change our mindset about what a successful student looks like in a way that doesn’t reflect systemic inequities — and then enact a training and recruitment agenda based on that mindset. We can continue investing our time and resources trying to get URM students to look more competitive against white students from private universities. But it’s doing a disservice to my students who want to be trained to become scientists, not to become what white people in charge think scientists should look like.

It’s dispiriting to see students consistently undervalued because of metrics that do not represent their worth or their capability. And the efforts to diversify STEM are kneecapped by disproportionate investment into people who came to the game with the benefit of higher resources. This isn’t because these more privileged students are prepared to become better scientists, but because the system is run by folks with the same background and are assessing potential in a way that students with fewer opportunities will always come up short.

I was chatting with a friend who was looking over the files of two undergraduate applicants. One went to a prestigious school, had multiple publications, did an REU in a prestigious faculty, and high test scores and grades. The other student was a first-gen URM student from a school that I hadn’t heard of, with had a strong letter of recommendation from a faculty member they worked with, but didn’t have the pubs and the fancy pedigree. How do you compare these two? That’s a challenge we have to meet, and it’s not an easy one. And ending that conversation with, “We have to be sure to be fair to the student who is working hard and doing very well, we can’t punish someone for being presented with opportunities” is not a mechanism for change.

You can’t measure what you can’t see, and when you are using these classic methods of assessing research potential, then you are literally overlooking a person because they hadn’t had the opportunity to excel. We already have so many Educational Opportunity Programs, funding programs that target URM students, and initiatives designed to prepare less advantaged students to become competitive. But no matter what we do, as long as we’re measuring students with this Deficit Model, there will always be this gap, because those with the advantages are always going to be leveraging those advantages to their opportunity. We’re working to shrink that gap, but others are working to expand that gap. And those expanding the gap will always have more resources, because it’s the resources themselves that generate the gap.

The deficit model of science communication shares a problem with the deficit model of STEM recruitment. No matter how hard to you try to fill in that gap, folks are going to make up their own minds using their own criteria. No matter how damn much you invest into filling in the “deficits” presented by URM students from a regional public university, they’re always going to get undervalued because the system is designed to value people who go through life with a greater set of opportunities.

Instead of doing everything we can to fill in the gaps, we need to find constructive forward-looking approaches, ones that will open the minds to welcome information that might otherwise go against the biases that we’ve grown up with. Using the deficit model buys into biases and reinforces them. It could be downright counterproductive.

For equity in STEM recruitment, we need to stop using the metrics that facilitate the systemic bias against marginalized students. What, precisely, could such a system of developing, recruiting, and evaluating scientists look like? I have a some ideas, and have written about them in some posts I’ve linked to here, but really, it’s not being done as far as I know, so I don’t know what it looks like. I realize it has to be radically different from what we’re doing now.

That’s a conversation that I’d like our scientific community to have in depth, because that’s the only way we can really move forward.






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notadoctor
86 days ago
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Oakland, CA
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expectsomuch: pinkphilosopher: moonblossom: deluxetrashqueen: Honestly, Rick Rolling is the best...

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expectsomuch:

pinkphilosopher:

moonblossom:

deluxetrashqueen:

Honestly, Rick Rolling is the best practical joke ever. Like, there’s nothing offensive or mean  spirited about it. It’s just like “Oops you thought there would be something else here but it’s ‘Never Gonna Give You Up’.” which isn’t even a bad song. It’s fairly enjoyable to listen to. There’s no jumpscares, no screaming, no ill will. Just Rick Astley telling you he’s never going to give you up. I think that’s great. “You fell into my trap! Here, listen to this completely benign song that will have no negative effect on you.” 

I wish this were true. There’s a really good article about the problems inherent with rickrolling here.

Very interesting. I never thought about that and now I feel bad.

Most people don’t know about this.

Heavy.

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notadoctor
86 days ago
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I got got.
Oakland, CA
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2 public comments
bibliogrrl
86 days ago
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this is my FAVORITE
Chicago!
mmunley
86 days ago
Beautiful
jepler
87 days ago
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Meta
Earth, Sol system, Western spiral arm
digdoug
86 days ago
Hook, line and sinker.

Climate change is shifting cherry blossom peak-bloom times

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Kyoto Cherry Blossom Chart

Records of when the cherry blossoms appear in Kyoto date back 1200 years. (Let’s boggle at this fact for a sec…) But as this chart of peak-bloom dates shows, since the most recent peak in 1829, the cherry blossoms have been arriving earlier and earlier in the year.

From its most recent peak in 1829, when full bloom could be expected to come on April 18th, the typical full-flowering date has drifted earlier and earlier. Since 1970, it has usually landed on April 7th. The cause is little mystery. In deciding when to show their shoots, cherry trees rely on temperatures in February and March. Yasuyuki Aono and Keiko Kazui, two Japanese scientists, have demonstrated that the full-blossom date for Kyoto’s cherry trees can predict March temperatures to within 0.1°C. A warmer planet makes for warmer Marches.

Temperature and carbon-related charts like this one are clear portraits of the Industrial Revolution, right up there with oil paintings of the time. I also enjoyed the correction at the bottom of the piece:

An earlier version of this chart depicted cherry blossoms with six petals rather than five. This has been amended. Forgive us this botanical sin.

Gotta remember that flower petals are very often numbered according to the Fibonacci sequence.

Tags: Fibonacci sequence   global warming   infoviz   mathematics
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notadoctor
106 days ago
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