Viewing entries in
Scientific Encounters
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? …
“During the COVID-19 pandemic, Sweden was among the few countries that did not enforce strict lockdown measures but instead relied more on voluntary and sustainable mitigation recommendations. While supported by the majority of Swedes, this approach faced rapid and continuous criticism. Unfortunately, the respectful debate centered around scientific evidence often gave way to mudslinging. However, the available data on excess all-cause mortality rates indicate that Sweden experienced fewer deaths per population unit during the pandemic (2020–2022) than most high-income countries and was comparable to neighboring Nordic countries through the pandemic. An open, objective scientific dialogue is essential for learning and preparing for future outbreaks.” - The Swedish COVID-19 approach: a scientific dialogue on mitigation policies, Björkman et al, 2023
“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.
Of course, causes rarely work like that in the real world, which is why scientists speak such in such convoluted terms. To say “x partly accounts for a portion of y given certain assumptions and conditions and only at high levels of x” lacks the emotional bunch of “x causes y” but that’s often how the world works.
So when people say x is the cause, or the ultimate cause, or the root cause, of some phenomenon: doubt and try to disconfirm the proposition - with a Wason test.
Andre Perry and David Harshbarger of the Brookings Institute have already crunched those numbers. To quote:
…approximately 11 million Americans (10,852,727) live in once-redlined areas, according to the latest population data from the Census Bureau’s American Community Survey (2017). This population is majority-minority but not majority-Black, and, contrary to conventional perceptions, Black residents also do not form a plurality in these areas overall. The Black population share is approximately 28%, ranking third among the racial groups who live in formerly redlined areas, behind white and Latino or Hispanic residents…While still a tremendously large population, the approximately 3 million Black residents in redlined areas account for just 8% of all non-Latino or Hispanic Black Americans.
Proximate cause (direct cause): Occurs immediately prior to the [outcome of interest]; directly results in its occurrence and, if eliminated or modified, would have prevented the undesired outcome
Root Cause: One of multiple factors (events, conditions or organizational factors) that created the proximate cause and subsequent undesired outcome. Typically multiple root causes contribute to an undesired outcome [my italics].
Root Cause Analysis: A method primarily used to identify the underlying cause of an incident or issue, and more effectively mitigate or prevent future similar incidents.
— So the question for this post is: how would we know whether the historical practice of redlining created a causal pathway that led directly to the current Black-White homeownership gap in the US? In other words, was redlining one of multiple factors responsible for the proximate causes of the Black-White homeownership gap?
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..
In other words, I’ll address how politicians and elected officials might be able to persuade the public and powerful interests to go along with disagreeable policies that promise plenty of short-term pain and almost no immediate payoff, all for an eventual yet somewhat uncertain greater good.
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.
…self-management interventions significantly and positively impacted all challenging behaviors assessed (i.e., on-task behavior, prosocial behaviors, disruptive behaviors, and following directions) and academic outcomes (i.e., achievement and work completion).
The Biden administration has proposed some cuts in Medicare spending…But these savings amount to just $24 billion a year over the next decade: clearly inadequate, considering that Medicare spending is projected to increase an average of nearly $100 billion a year over the same period. What else can be done to rein in those costs?