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The Virtues of Science
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.
…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).
Comparative studies have shown that in most countries an increase of around 40 points in the PIAAC numeracy score leads to a wage increase of between 12% and 15% of the reference wage. (Hanushek et al, 2013). But the wage increase is as high as 28% in the United States. So if the reference wage was $20 an hour, a wage increase of 28% would bring that up to $25.60 an hour, or an additional $224 a week for full-time workers.
And one study found that an increase of around 40 points in the PIAAC literacy score was associated with a 6% increase in hourly wages, on average, across several developed countries, including the United States (Kankaraš et al, 2016).
“It took longer for police to respond in 2022, even as the number of calls to police dropped by 38% since 2019. Calls to 911 also sank by 22% in the same period… SFPD chief financial officer Patrick Leung blamed lengthening response times to what he and other city leaders say is an agency-wide staffing crisis... The Police Commission report showed that the number of full duty staffers dropped to 1,537 by the end of 2022, down from 1,872 in 2017. SFPD estimates they need roughly 2,182 staffers to operate efficiently.” - As San Franciscans Make Fewer 911 Calls, SFPD Takes Longer To Respond, by Liz Lindqwister/The San Francisco Standard. March 1, 2023
In previous posts, I focused on the violent crime rates of 20 large cities, ten with Republican mayors and ten with Democratic mayors (here and here). I also looked at clearance rates for violent crimes in 19 of these cities (here), meaning the rate of violent crimes “solved for reporting purposes”, usually by arrest. The pattern I found was clear: the large cities with Republican mayors had lower violent crime rates and higher clearance rates than those with Democrat mayors. Interesting, but a pattern doesn’t establish causality.
“Crime is concentrated in small places, or ‘hot spots,’ that generate half of all criminal events. Hot spots policing focuses police resources and attention on these high crime places…Overall, it is more likely that hot spots policing generates crime control benefits that diffuse into the areas immediately surrounding the targeted locations than displacing crime into nearby locations.” - Hot spots policing of small geographic areas effects on crime
“The ‘No Excuses’ charter school model focuses heavily on high academic expectations, rigid and consistent discipline, extended instructional time, intensive teacher training, and increased parental involvement…No Excuses charter schools, on average, produced larger math and literacy achievement gains for their students than their public school peers—with higher gains for math.” - ‘No Excuses’ charter schools for increasing math and literacy achievement in primary and secondary education