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Media Literacy Is About Where To Spend Your Trust. But You Have To Spend It Somewhere. | Hapgood
"A lot of approaches to online media literacy highlight “debunking” and present a large a portion of cases where students debunk tree octopuses and verifiably false things. And show students how they are manipulated, etc.

And this is good in the right amounts. There’s a place for it. It should comprise much of your curriculum.

But the core of media literacy for me is this question of “where you spend your trust.” And everything has to be evaluated in that framework.

There’s not an option to not trust anyone, at least not an option that is socially viable. And societies without trust come to bad ends. Students are various, of course, but what I find with many students is they are trust misers — they don’t want to spend their trust anywhere, and they think many things are equally untrustworthy. And somehow they have been trained to think this makes them smarter than the average bear.

A couple stories will illustrate the problem. I was once working with a bunch of students and comparing Natural News (a health supplements site which specializes in junk science claims) and the Mayo Clinic, one of the most respected outfits out there. OK, I say, so what’s the problem with taking advice from Natural News?

Well, says a student, they make their money selling supplements, and so they have an incentive to talk down traditional medicine.

I beam like a proud papa. Good analysis!

“And,” the student continues, “the Mayo Clinic is the same way. They make money off of patients so they want to portray regular hospitals as working.”

Houston, we have a problem.

I was in an upper division class another time and we were looking at an expert in a newspaper cited for his background in the ethnobiology of issues around the study of birds. I did what I encourage students to do in such cases: as a sanity check, make sure that the person being quoted as an academic expert has a publication record in the relevant area, preferably with a cite or two. (There are other varieties of expertise, of course, but in this case the claimed expertise was academic).

The record comes up. This guy’s top article on birds, biologists, and indigenous knowledge has something like 34 citations in Google Scholar. “So what do you think?” I ask them.

“Eh,” they say. “Not great.”

This was, mind you, not a room full of published ethnobiologists. And the ethnobiologist quoted in the article was not claiming to overturn the fundamental insights of ethnobiology, or anything requiring extraordinary evidence.

So 34 other experts had considered this person’s niche work worth talking about but hey, we’re still not sure this guy’s worth listening to on a subject we know nothing about and in which he is making rather moderate claims…

Hrmm.

Another class, looking at Canadian paper the National Post, noted that while it was a “real” paper with a real staff, the Wikipedia page on it noted a controversy about some wrong information they published in 2006, where the editor had to actually pen an apology. “So kind of half-and-half, right?”

I’ve referred to this before as trust compression, the tendency for students to view vastly different levels of credibility of sources all as moderately or severely compromised. Breitbart is funded by the Mercers, who are using it directly to influence political debate, but the Washington Post is also owned by Jeff Bezos who donated to Democrats. So it’s a wash. And yes, we have the word of an expert in a subject where she has multiple cites against the word of a lobbying group but neither one is perfect really. Everyone’s got an agenda, nobody knows everything, and there’s not 100% agreement on anything anyway.

You see this in areas outside of expertise as well, incidentally. With quotes I often ask students (and faculty!) to source the quote and then say if the quote was taken out of context. The answer? You’ll always get a range from “completely taken out of context” to “somewhat taken out of context”. That upper register of “Nope, that quote was used correctly” is something you really have to coax the students into.

I don’t quite know how to square this with the gullibility often on display, except to say that very often that gullibility is about not being able (or willing) to distinguish gradations of credibility.

This should scare you, and it has to be at the core of what we teach — to teach students they need to decompress their trust, get out of that mushy middle, and make real distinctions. And ultimately, put their trust somewhere. Otherwise we end up with what Hannah Arendt so accurately described as the breeding ground of totalitarianism:
In an ever-changing, incomprehensible world the masses had reached the point where they would, at the same time, believe everything and nothing, that everything was possible and that nothing was true… Mass Propaganda discovered that its audience was ready at all times to believe the worst, no matter how absurd, and did not particularly object to being deceived because it held every statement to be a lie anyhow…

I do believe this insight — that trust has to be spent somewhere and that our problem is not gullibility, but rather the gullibility of cynics — has to be at the core of what we teach and how we teach it. You have some trust, and you have to be willing to spend it somewhere. So enough of the “this isn’t great either”, enough of the “eh”. What’s your best option for spending that trust? Why?

If everything is compromised, then everything can be ignored, and filtering is simply a matter of choosing what you want to hear. And students will economize that lesson in a heartbeat. In fact, I’m worried they already have, and it’s up to us to change that."
medialiteracy  mikecaulfield  internet  web  media  authority  trust  hannaharendt  trustworthiness  online  journalism  bias  expertise  gullibility  propaganda  2018 
8 hours ago by robertogreco
#NotOKGoogle search suggestions: 2018 edition • Medium
Jonathan Albright:
<p>I’m at a loss to understand how this could *still* be happening. The quality and reliability of Google’s search suggestions have actually devolved in the past year. It almost reads like these input signals are coming out of Reddit, Twitter and other online and social news forums.

Here's February 20, 2018. Below are some examples of what kids are likely to see when they begin to type in or use Google to look up a controversial topic. Why does this matter? It matters because this is information pollution at the most critical interface: search. Google is the knowledge portal for most of the world.

When toxic information — suggestions like the ones seen below — get in the way of people actively fact checking and truth-seeking, it’s a major problem.

<img src="https://cdn-images-1.medium.com/max/1600/1*RunXLUNW3_lcgzNfLNLywg.png" width="100%" />

<img src="https://cdn-images-1.medium.com/max/1600/1*LovYe2O8mxjUg8onyzQGjw.png" width="100%" />

<img src="https://cdn-images-1.medium.com/max/1600/1*kJK7uohPKhnZcBX4sgnIZw.png" width="100%" />

We’re at a critical juncture in social cohesion & the role of tech in society. The walls have been breached; platforms are now getting vandalized in broad daylight.</p>

Note also that those are searches relating to American topics. But as Carole Cadwalladr has shown at the Guardian (a year ago, and again when Albright showed these) you get just as bad outside the US.
search  google  bias 
2 days ago by charlesarthur
what even is a "community engineer" even???
i'll be completely frank with you - as a woman, the day your title no longer includes "engineer" or something of that sort, the perception of what you do changes and it's hard to build that back up. as someone who has worked in two systemically sexist fields (academia, web development), i 100% am behind the idea that job titles are a social construct designed to strengthen the glass ceiling, full stop. so it is imperative that as long as i'm doing a job that involves building web applications, even if not on the core product, i have the title of engineer or developer.
community  engineering  gender  bias  feminism 
2 days ago by spaceninja
7 Tips For Negotiating Your Salary
Find out how you can successfully negotiate your salary, starting with your first job, with these tips from Levo founder Caroline Ghosn.
salary  negotiation  hiring  interviews  culture  work  gender  bias  feminism 
2 days ago by spaceninja
Men have no clue how much they talk
Men think conversation as equal when women talk 15% of the time.
Men think women dominate when they talk just 30%.
gender  feminism  bias  discrimination  culture 
2 days ago by spaceninja
Matthew Reidsma : Auditing Algorithms
Talks about libraries, technology, and the Web by Matthew Reidsma.
code4lib  code4lib-2018  algorithms  bias  search  libraries  technology 
4 days ago by malantonio
Scale-free networks are rare – Arxiv Vanity
A central claim in modern network science is that real-world networks are typically “scale free,” meaning that the fraction of nodes with degree
k
follows a power law, decaying like
k

α
, often with
2
<
α
<
3
. However, empirical evidence for this belief derives from a relatively small number of real-world networks. We test the universality of scale-free structure by applying state-of-the-art statistical tools to a large corpus of nearly 1000 network data sets drawn from social, biological, technological, and informational sources. We fit the power-law model to each degree distribution, test its statistical plausibility, and compare it via a likelihood ratio test to alternative, non-scale-free models, e.g., the log-normal. Across domains, we find that scale-free networks are rare, with only 4% exhibiting the strongest-possible evidence of scale-free structure and 52% exhibiting the weakest-possible evidence. Furthermore, evidence of scale-free structure is not uniformly distributed across sources: social networks are at best weakly scale free, while a handful of technological and biological networks can be called strongly scale free. These results undermine the universality of scale-free networks and reveal that real-world networks exhibit a rich structural diversity that will likely require new ideas and mechanisms to explain.
articles  information_theory  math  bias 
5 days ago by gmisra

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