To date, a whopping two million digital documents have been annotated
I wonder how many annotations have been scribbled in the margins of physical books.
Alternatively, I wonder how many digital "annotations" exist only as fleeting thoughts captured by a notes app, removed from the context that created them. The ability to couple thoughts to context is why annotation is powerful.
horizontal oppression is symmetrical (sexism + ableism = ableism + sexism) b
Commutative
that the purpose of games is to exercise the brain, and you exercise the brain by challenging it to identify patterns. Games give players an opportunity to practice and understand patterns in a safe context, where stakes are not as high as in the real world.
Share with [[Sarah]], relevant to teaching
Furthermore, Bhattacharya and Packalen construct a model that demonstrates just how devastating the emphasis on citations and h-index can be in disincentivizing real scientific exploration. Because, while citations are one important metric in science, actual scientific progress depends on a steady flow of exploratory tinkering and new ideas.
More dangers of bibliometrics. Also reminds me of John Cormendy's retracted paper about career success in astrophysics
Twenge and I later re-ran Orben and Przybylski’s SCA on the same datasets (teaming up with researchers Kevin Cummins and Jimmy Lozano.) When we used Orben and Przybylski's assumptions, we replicated their results exactly, obtaining associations that were equivalent to correlation coefficients less than r = .05. But when we limited the analysis to social media for girls, we found relationships that were many times larger, equivalent to correlation coefficients of roughly r = .20.1
Why Bayesians always stress "check your priors" (which is good advice not limited to bayesian analysis). Question your assumptions and then question those questions.
We posted the Google doc online in February 2019 and invited comments from critics and the broader research community. Each section ends with a request to tell us what we have missed. One of the first comments we got was that some researchers doubted that the mental illness epidemic was real. That led us to create a second Google doc titled: Adolescent mood disorders since 2010: A collaborative review. (I described it in my Feb. 8 Substack post.)
Gotta love that community based science
What we see in this second case is that social media creates a cohort effect: something that happened to a whole cohort of young people, including those who don’t use social media. It also creates a trap—a collective action problem—for girls and for parents. Each girl might be worse off quitting Instagram even though all girls would be better off if everyone quit.
Feels similar to a "Prisoner's Dilemma" problem. Or perhaps a tragedy of the commons
Nearly all of the research––the “hundreds of studies” that Hancock referred to––have treated social media as if it were like sugar consumption. The basic question has been: how sick do individuals get as a function of how much sugar they consume? What does the curve look like when you graph illness on the Y axis as a function of daily dosage on the X axis? This is a common and proper approach in medical research, where effects are primarily studied at the individual level and our objective is to know the size of the “dose-response relationship.”
I wonder what the graph would look like if we considered the prevalence of sickle cell trait and harms, at a population level.