Fallen, Fallen Is Big Science the Great
Big Science has become a dwelling place of demons and a prison of every unclean spirit. And they admit it.
Science, that once-honored bastion of intellectual trade, has become a byword for evil and perversion. Its temples are filled with unprincipled men telling lies. Its objectivity is laughable. And the kings of the earth, who committed acts of immorality and lived sensuously with her, will weep and lament over her when they see the smoke of her burning.
Big Science Has Tolerated and Promoted Systemic Racism
Racism in academia, and why the ‘little things’ matter (Nature). Kevin Laland comes clean and accuses academia.
The explicit racism of my past is now superseded by subtler discrimination. For 30 years, I have struggled with the fact that some founders of my field are still idolized as if their racist and eugenicist views were unimportant.
Racism and harassment are common in field research — scientists are speaking up (Nature). Did you hear that? They are “common” among scientists who are supposed to be doing “research” in the field. What are they really researching?
How racism contributes to ‘a very ivory tower’ (Rice University). A Templeton-funded study finds systemic racial discrimination in both biology and physics institutions, based on surveys of 1,160 scientists.
Notably, many articles about racism in scientific institutions ignore the historical racist and eugenics beliefs and practices that proliferated out of Darwinism. There are a few exceptions, however (see 27 Aug 2020, 17 Aug 2020 and 31 July 2020); Kevin Laland mentions it briefly. Perhaps more will be forthcoming as institutions are being pressured to apologize for their past practices.
Big Science Has Tolerated and Promoted Systemic Sexism
Quick fixes won’t stop sexual harassment in academia, experts say (University of Illinois, via Phys.org). Don’t take any “virtue signaling” from scientists about how noble and righteous they are because they ‘stand for science.’ Listen to U. of I. anthropology professor Kathryn Clancy:
“Academia has the second-highest rate of sexual harassment, after the military,” she said. “We condone and even reward selfishness, rudeness and unhealthy forms of competition. We need brave leaders who are willing to change incentive structures and cherish their brave whistleblowers, caring mentors and collegial staff and faculty.”
Opinion: Use science to stop sexual harassment in higher education (PNAS). Three women are irate about the tolerance of this big problem in the institutions of science. Sexual harassment continues to fester and not be taken seriously.
Sexual harassment abounds in academia. We know this from a 2018 report published by the National Academies of Sciences, Engineering, and Medicine. As members of the committee who authored that report, we have presented its findings to colleges and universities around the country. It has been deeply gratifying to see so many leaders want to address sexual harassment in their institutions. But according to a large body of social science evidence, the strategies that many of these same leaders are pursuing simply don’t work.
Fed-up archaeologists aim to fix field schools’ party culture (Science Magazine). Here’s one field (secular archaeology) that may be too far gone for reform. Traditional cowboys are better behaved than these party animals.
The undergrads can choose from hundreds of field schools, many in remote areas. But Colaninno, who teaches at Southern Illinois University, Edwardsville, knows from former students and information passed privately among others in her whisper network that some field schools have a reputation for faculty who sexually harass with impunity. Many schools are also famed for heavy drinking.
Traditional field schools foster “the archaeology cowboy mentality … working really hard during the day but playing really hard at night—and drinking a ton,” says Katrina Eichner, an archaeologist at the University of Idaho. If directors of these field schools encourage that atmosphere, she adds, “it devolves into a frat party.” Over time, that cowboy culture gets perpetuated across academic generations.
Big Science Is Careless
Challenge to scientists: does your ten-year-old code still run? (Nature). Past claims cannot be replicated because the computer code is obsolete and researchers did not keep accurate records.
We rely on science. Why is it letting us down when we need it most? (Op-Ed by Stuart Ritchie, L.A. Times). This editorial bemoans the horrible reputation that scientists are making for themselves in a subject—science—that most people really want to look up to. Ritchie gives examples and discusses some of the perverse incentives and careless practices that are ruining science’s reputation, which is tragic because of society’s need for accurate, reliable information. He claims that there are many similar cases in addition to the bad examples he discusses.
Science is suffering from a replication crisis. Too many landmark studies can’t be repeated in independent labs, a process crucial to separating flukes and errors from solid results. The consequences are hard to overstate: Public policy, medical treatments and the way we see the world may have been built on the shakiest of foundations.
A-level results: why algorithms get things so wrong – and what we can do to fix them (The Conversation). People’s lives and careers are being ruined by flawed algorithms, argue two computer scientists.
The scale of public anger over the automated downgrading of thousands of students’ A-level results highlights how much social and political power algorithmic decision-making now has. As well as students’ grades, algorithms are now deciding all sorts of things that hugely impact ordinary people’s lives, from loan applications to job interviews to which neighbourhoods are targeted by police.
Too often the outcomes of these decisions are what most people would consider unfair, as was the case for the students whose results were downgraded despite having strong academic records or based on their school’s past performance not their own. How are these algorithms going so wrong, and how can we ensure they produce fairer outcomes in the future?
This shows the bad consequences of uncritical faith in scientists. Those who write algorithms for AI (artificial intelligence) are committing logical blunders about proxies, averages and future trends based on past performance. People are being hurt by misplaced trust in experts who don’t know what they are doing and are removed from the consequences of their decisions. “The kind of social data that is involved in these critical life decisions is inherently unpredictable,” the authors say.
The next post will look more at the fall of Big Science from additional angles.