SoylentNews is people
SoylentNews
from the I-don't-want-knowledge-I-want-certainty dept.
Jeremy P. Shapiro, a professor of psychology at Case Western Reserve University, has an article on The Conversation about one of the main cognitive errors at the root of science denial: dichotomous thinking, where entire spectra of possibilities are turned into dichotomies, and the division is usually highly skewed. Either something is perfect or it is a complete failure, either we have perfect knowledge of something or we know nothing.
Currently, there are three important issues on which there is scientific consensus but controversy among laypeople: climate change, biological evolution and childhood vaccination. On all three issues, prominent members of the Trump administration, including the president, have lined up against the conclusions of research.
This widespread rejection of scientific findings presents a perplexing puzzle to those of us who value an evidence-based approach to knowledge and policy.
Yet many science deniers do cite empirical evidence. The problem is that they do so in invalid, misleading ways. Psychological research illuminates these ways.
[...] In my view, science deniers misapply the concept of “proof.”
Proof exists in mathematics and logic but not in science. Research builds knowledge in progressive increments. As empirical evidence accumulates, there are more and more accurate approximations of ultimate truth but no final end point to the process. Deniers exploit the distinction between proof and compelling evidence by categorizing empirically well-supported ideas as “unproven.” Such statements are technically correct but extremely misleading, because there are no proven ideas in science, and evidence-based ideas are the best guides for action we have.
I have observed deniers use a three-step strategy to mislead the scientifically unsophisticated. First, they cite areas of uncertainty or controversy, no matter how minor, within the body of research that invalidates their desired course of action. Second, they categorize the overall scientific status of that body of research as uncertain and controversial. Finally, deniers advocate proceeding as if the research did not exist.
Dr. David "Orac" Gorski has further commentary on the article. Basically, science denialism works by exploiting the very human need for absolute certainty, which science can never truly provide.
(Score: 0) by Anonymous Coward on Friday November 15 2019, @06:55AM
Very fair point! Yeah, I think the argument for using averages is certainly logical with such a small sample of decade points. I just downloaded the CSV for the aforementioned data set here [nasa.gov].
I created 4 sets of averages:
1980-1989 = 0.246
1990-1999 = 0.385
2000-2009 = 0.59
2010-2018 = 0.785
For your convenience if you'd like to double check my work the cell codes I used were:
=AVERAGE(B103:B112)
=AVERAGE(B113:B122)
=AVERAGE(B123:B132)
=AVERAGE(B133:B141)
And so we get:
2000 = +.139
2010 = +.205
2018 = +.195
Total = 0.539
And that definitely is a much bigger number. The problem is that it again falls *far* outside the prediction expectation (0.9) and even outside their entire range (0.6 - 1.5). So we still end up having to get back into the 'adjustment' arguments as per above.
And yeah no idea what's going on with Wiki's 2010-2019 range. It's extremely wrong. Kind of expect as much from that site though. Just checked the history. Looks like IP 50.66.163.181 randomly changed the table back February, and nobody bothered to verify it. Thanks, Canada. Wikipedia: the idea that doesn't work in theory only in practice. Until the internet gets stupid. And then it simply becomes the idea that doesn't work.