At its core, demography is the act of counting people. But it’s also important to study the forces that are driving population change, and measure how these changes have an impact on people’s lives. For example, how does immigration affect U.S. population growth? Do Americans feel that children are better off with a parent at home, in an era when most women work? How is the rise of the young-adult Millennial generation contributing to the rise of Americans with no stated religion? For this year’s Population Association of America (PAA) annual meeting, here is a roundup of some of Pew Research Center’s recent demography-related findings that tell us how America and the world are changing.
A new Pew Research Center survey shows the extent to which America is a nation of ongoing learners:
73% of adults consider themselves lifelong learners.
74% of adults are what we call personal learners – that is, they have participated in at least one of a number of possible activities in the past 12 months to advance their knowledge about something that personally interests them. These activities include reading, taking courses or attending meetings or events tied to learning more about their personal interests.
63% of those who are working (or 36% of all adults) are what we call professional learners – that is, they have taken a course or gotten additional training in the past 12 months to improve their job skills or expertise connected to career advancement.
An oldie, but goodie.
Over at Montclair Socioblog, Jay Livingston discusses a recent study showing that some Americans don’t think that their votes make any difference in how they’re governed. Those of us who care about politics often respond to this kind of pessimism with the old adage that every vote counts, but are they wrong?
Livingston suggests that they’re not.
Faith, by definition, is the belief in something despite insufficient knowledge to be certain of its veracity. Some beliefs require small leaps of faith (the example that the Sun will rise tomorrow), as the body of evidence supporting that prediction is overwhelming, while others – the existence of dark matter, the inflationary origin of our Universe, or the possibility of room-temperature superconductivity — may still be likely, but may also reasonably turn out to be wrongheaded. Yet in every case, there are two key components that make the prediction scientific:
1. The prediction, or the belief that the outcome can be accurately predicted, is predicated on the existence of quality evidence.
2. As the evidence changes — as we obtain more, newer and better evidence — and as the full suite of evidence expands, our predictions, postdictions and entire conceptions of the Universe change along with it.
There is no such thing as a good scientist who isn’t willing to both base their scientific belief on the full suite o
A common misconception among nonstatisticians is that p-values can tell you the probability that a result occurred by chance. This interpretation is dead wrong, but you see it againand again and again and again. The p-value only tells you something about the probability of seeing your results given a particular hypothetical explanation — it cannot tell you the probability that the results are true or whether they’re due to random chance.
Cobb’s concern was a long-worrisome circularity in the sociology of science based on the use of bright lines such as P < 0.05 : “We teach it because it’s what we do; we do it because it’s what we teach.” This concern was brought to the attention of the ASA Board.
This is an oldie-but-goodie… but needs a re-posting sometimes…
"To drive this point home I have pulled a few excerpts from Max Weber’s writing on bureaucracy but I have replaced a few nouns (in bold) so that his references to human organizations are replaced by algorithms, blockchains, and other technologies. With just these few noun changes a 19th century German sociologist of modern statecraft turns into the next great TED talk…"