Viewing entries tagged
The Virtues of Science
“…despite ample proof to the contrary*, many polls still show voters think Trump would still have an edge over Harris on handling the economy. We can chalk that up at least in part to short-term memory loss of the Trump administration’s chaos, along with [post-pandemic] inflation…” - Hayes Brown/MSNBC Opinion Writer/Editor September 29, 2024 [my italics]
The University of Michigan’s Consumer Sentiment Index (CSI) is regarded as one of the leading indicators of consumer confidence in the United States. The CSI survey asks consumers about their own personal finances, as well as their views on the state of the US economy. As measured by the CSI, consumer confidence typically drops right before recessionary periods, whereas rising consumer confidence predicts increased consumer spending and economic growth. This pattern is clear in the following chart...
Does that mean science writers should avoid expressing opinions regarding the significance of whatever they’re writing about? No, but they should do so in the spirit of science: with an abundance of caution and plenty of hedging. Above all, they need to take care not to mislead or exaggerate.
Evidence is information that serves to support or counter a proposition about reality. If objective reality exists, then we can get closer to its truth through the gathering and evaluation of evidence. Evaluating evidence is a kind of interrogation. For example, one could “interrogate” opinion pieces, news analyses, and science stories with questions like…
If we made such questioning a habit, the better we’d get at glimpsing bits of the world as it is, rather than how we want or expect it to be.
In another study, participants who reported trust in science were more likely to believe and disseminate false claims that contain scientific references than false claims that do not. The study authors conclude that ‘trust in science, although desirable in many ways, makes people vulnerable to pseudoscience” (O'Brien, Palmer, et al., 2021).
“Occasionally, scientific ideas (such as biological evolution) are written off with the putdown “it’s just a theory.” This slur is misleading and conflates two separate meanings of the word theory: In common usage, the word theory means just a hunch, but in science, a theory is a powerful explanation for a broad set of observations.” - from How Science Works
There actually have been people and movements that were more broadly antiscience than today’s this-or-that skeptics: what we used to call “new age” types, e.g., members of religious cults and believers in the occult. In his oft-cited 1993 book Science and Anti-Science, Gerald Holton mentions “interest in astrology” as indicative of antiscience beliefs, as least as “conventionally” understood (his word).
So the author defines antiscience as the rejection of mainstream scientific views and their replacement with unproven or deliberately misleading theories. What does that even mean? Science is a process that moves forward by questioning received wisdom. Does “rejection” encompass doubt or criticism? At what point would a theory be considered “proven”? . And why all the ad hominen verbiage (“deliberating misleading”, “nefarious”)? Can’t people just disagree without being accused of bad faith?
The inspiration for this post came from reading a bunch of articles on how to combat “antiscience”. Each one cautioned against trying to reason or debate scientific issues with people who hold antiscience views. Rather, one should try to relate to their emotions and social needs, e.g., be warm, tell stories, find common ground, establish a connection. Above all, don’t acknowledge their ideas have any merit.
And I thought: don’t any of these authors know about the “persuasive backfire effect”? Here’s a brief review…
“Antiscience is a set of attitudes that involve a rejection of science and the scientific method. People holding antiscientific views do not accept science as an objective method that can generate universal knowledge...Lack of trust in science has been linked to the promotion of political extremism and distrust in medical treatments…for some, rejecting scientific consensus or public health guidance serves as an expression of political allegiance or skepticism towards perceived authority figures.” Wikipedia
Hmm…
“Science is broadly understood as collecting, analyzing, publishing, reanalyzing, critiquing, and reusing data.” Wikipedia,
In other words, science is a process. More specifically, science is a self-correcting process for deepening our understanding of the world. It is a process that comes with safeguards to minimize error. Data is the direct outcome of that process.
What would you consider the “science” in these scenarios? What science would you trust? What leads you to trust one science claim and not another? If the credibility of the source, how do you determine the credibility of a source? …
“It is an increasingly familiar experience. A request for help to a large language model such as OpenAI’s ChatGPT is promptly met by a response that is confident, coherent and just plain wrong. In an AI model, such tendencies are usually described as hallucinations. A more informal word exists, however: these are the qualities of a great bullshitter… The fundamental problem is that language models are probabilistic, while truth is not.” - AI models make stuff up. How can hallucinations be controlled? The Economist February 28, 2024
“If a Buddhist Newton had been sitting under that tree, he would have seen the apple falling and, reaching for Enlightenment, experienced each moment of its descent as a thing pure in itself. Only a restless Western Newton would say, “Now, what story can tell us best what connects those apple-moments from branch to ground? Sprites? Magnets? The mysterious force of the mass of the earth beneath it? What made the damn thing fall?” That’s a story we tell, not a moment we experience.” - Adam Gopnik, What Meditation Can Do for Us, and What It Can’t: Examining the science and supernaturalism of Buddhism.
Actually, “findings” is too strong a word. The data is all self-report and thus subject to desirability bias. The homeless individuals in the study know the researchers want the intervention to be successful. They form relationships with the “phone buddies” who ask them all these questions. I imagine some participants would hesitate to tell the whole truth and nothing but.
In previous posts I’ve explored the relation between violent crime and incarceration rates in the US, which got me wondering: how much do incarceration rates reflect violent crime rates in other countries? Hence, this exploration - and I stress ‘exploration’, because good data is hard to come by and cross-country comparisons can be misleading. For example, countries may not define criminal offenses the same way or have different levels of unreported crime. But iffy data can still reveal real patterns, provided the numbers aren’t not too far off. With that hope in mind, I decided to check out the data and see what patterns I could find.
This post includes excerpts from a Campbell systematic review of surveys and studies on the impact of school-based law-enforcement strategies, followed by a few observations of my own.
The gap in Black-white homeownership rates recently reached 30.1% in the U,S. Per Jung Hyun Choi of The Urban Institute, three factors explain around 80% of this gap: difference in Black-white income (31%), marital status (27%), and credit scores (22%).
The inspiration for this post was reading No, seriously. Root Cause is a Fallacy, by Will Gallego, especially:
Let’s start with some understanding behind the appeal of root cause. The thinking is that you want to get to the underlying problem, starting at where it begins, rather than treating the downstream effects. I can appreciate resolving deeper underlying issues rather than “treating the symptoms” when problems large or small crop up. Our systems are complex. It’s very tempting to look at a singular part in an effort to simplify our understanding and achieve resolution..
Reducing class size is seen as a way of improving student performance. But larger class sizes help control education budgets. The evidence suggests at best a small effect on reading achievement. There is a negative, but statistically insignificant, effect on mathematics, so it cannot be ruled out that some children may be adversely affected.