Alcove

Science, culture, complexity

Tag: Republican Party

  • An infuriating editorial in Science

    I’m not just disappointed with an editorial published by the journal Science on November 14, I’m angry.

    Irrespective of whether the Republican Party in the US has shifted more or less rightward on specific issues, it has certainly shifted towards falsehoods on many of them. Party leaders, including Donald Trump, have been using everything from lazily inaccurate information to deliberately misleading messages to preserve conservative attitudes wherever that’s been the status quo and to stoke fear, confusion, uncertainty, and animosity where peace and good sense have thus far prevailed.

    Against this backdrop, which the COVID-19 pandemic revealed in all its glory, Science‘s editorial is headlined “Science is neither red nor blue”. (Whether this is a reference to the journal itself is immaterial.) Its author, Marcia McNutt, president of the US National Academy of Sciences (NAS), writes (emphasis added):

    … scientists need to better explain the norms and values of science to reinforce the notion—with the public and their elected representatives—that science, at its most basic, is apolitical. Careers of scientists advance when they improve upon, or show the errors in, the work of others, not by simply agreeing with prior work. Whether conservative or liberal, citizens ignore the nature of reality at their peril. A recent example is the increased death rate from COVID-19 (as much as 26% higher) in US regions where political leaders dismissed the science on the effectiveness of vaccines. Scientists should better explain the scientific process and what makes it so trustworthy, while more candidly acknowledging that science can only provide the best available evidence and cannot dictate what people should value. Science cannot say whether society should prioritize allocating river water for sustaining fish or for irrigating farms, but it can predict immediate and long-term outcomes of any allocation scheme. Science can also find solutions that avoid the zero-sum dilemma by finding conservation approaches to water management that benefit both fish and farms.

    Can anyone explain to me what the first portion in bold even means? Because I don’t want to assume a science administrator as accomplished as McNutt is able to ignore the narratives and scholarship roiling around the sociology of science at large or the cruel and relentless vitiation of scientific knowledge the first Trump administration practiced in particular. Even if the editorial’s purpose is to extend an olive branch to Trump et al., it’s bound to fail. If, say, a Republican leader makes a patently false claim in public, are we to believe an institution as influential as the NAS will not call it out for fear of being cast as “blue” in the public eye?

    The second portion in bold is slightly less ridiculous: “science can only provide the best available evidence and cannot dictate what people should value.” McNutt is creating a false impression here by failing to present the full picture. During a crisis, science has to be able to tell people what to value more or less rather than what to value at all. Crises create uncertainty whereas science creates knowledge that is free from bias (at least it can be). It offers a pillar to lean on while we figure out everything else. People should value these pillars.

    When a national government — in this case the government of one of the world’s most powerful countries — gives conspiracies and lies free reign, crises will be everywhere. If McNutt means to suggest these crises are so only insofar as the liberal order is faced with changes inimical to its sustenance, she will be confusing what is today the evidence-conspiracy divide for what was once, but is no longer, the conservative-liberal divide.

    As if to illustrate this point, she follows up with the third portion in bold: “Science cannot say whether society should prioritize allocating river water for sustaining fish or for irrigating farms, but it can predict immediate and long-term outcomes of any allocation scheme.” Her choice of example is clever because it’s also fallacious: it presents a difficult decision with two reasonable outcomes, ‘reasonable’ being the clincher. The political character of science-in-practice is rarely revealed in debates where reasonability is allowed through the front door and given the power to cast the decisive vote. This was almost never the case under the first Trump administration nor the parts of the Republican Party devoted to him (which I assume is the whole party now), where crazy* has had the final say.

    The choice McNutt should really have deliberated is “promoting the use of scientifically tested vaccines during a pandemic versus urging people to be cautious about these vaccines” or “increasing the stockpile of evidence-backed drugs and building social resilience versus hawking speculative ideas and demoralising science administrators”. When the choice is between irrigation for farms and water for fisheries, science can present the evidence and then watch. When the choice is between reason and bullshit, still advocating present-and-watch would be bullshit, too — i.e. science would be “red”.

    This is just my clumsy, anger-flecked take on what John Stuart Mill and many others recognised long past: “Bad men need nothing more to compass their ends than that good men should look on and do nothing.” But if McNutt would still rather push the line that what seem like “bad men” to me might be good men to others, she and the policies she influences will have committed themselves to the sort of moral relativism that could never be relevant to politics in practice, which in turn would be a blow for us all.

    (* My colloquialism for the policy of being in power for the sake of being in power, rather than to govern.)

  • Science shouldn’t animate the need for social welfare

    This is an interesting discovery:

    First, it’s also a bad discovery (note: there’s a difference between right/wrong and good/bad). It is useful to found specific interventions on scientific findings – such as that providing pregnant women with iron supplements in a certain window of the pregnancy could reduce the risk of anaemia by X%. However, that the state should provide iron supplements to pregnant women belonging to certain socio-economic groups across the country shouldn’t be founded on scientific findings. Such welfarist schemes should be based on the implicit virtues of social welfare itself. In the case of the new study: the US government should continue with cash payments for poor mothers irrespective of their babies’ learning outcomes. The programme can’t stop if any of their babies are slow learners.

    Second, I think the deeper problem in this example lies with the context in which the study’s findings could be useful. Scientists and economists have the liberty to study what they will, as well as report what they find (see third point). But consider a scenario in which lawmakers are presented with two policies, both rooted in the same ideologies and both presenting equally workable solutions to a persistent societal issue. Only one, however, has the results of a scientific study to back up its ability to achieve its outcomes (let’s call this ‘Policy A’). Which one will the lawmakers pick to fund?

    Note here that this isn’t a straightforward negotiation between the lawmakers’ collective sensibilities and the quality of the study. The decision will also be influenced by the framework of accountability and justification within which the lawmakers operate. For example, those in small, progressive nations like Finland or New Zealand, where the general scientific literacy is high enough to recognise the ills of scientism, may have the liberty to set the study aside and then decide – but those in India, a large and nationalist nation with generally low scientific literacy, are likelier than not to construe the very availability of scientific backing, of any quality, to mean Policy A is better.

    This is how studies like the one above could become a problem: by establishing a pseudo-privilege for policies that have ‘scientific findings’ to back up their promises. It also creates a rationalisation of the Republican Party’s view that by handing out “unconditional aid”, the state will discourage the recipients from working. While the Republicans’ contention is speculative in principle, in policy and, just to be comprehensive, in science, scientific studies that find the opposite play nicely into their hands – even in as straightforward a case as that of poor mothers. As the New York Times article itself writes:

    Another researcher, Charles A. Nelson III of Harvard, reacted more cautiously, noting the full effect of the payments — $333 a month — would not be clear until the children took cognitive tests. While the brain patterns documented in the study are often associated with higher cognitive skills, he said, that is not always the case.

    “It’s potentially a groundbreaking study,” said Dr. Nelson, who served as a consultant to the study. “If I was a policymaker, I’d pay attention to this, but it would be premature of me to pass a bill that gives every family $300 a month.”

    A temporary federal program of near-universal children’s subsidies — up to $300 a month per child through an expanded child tax credit — expired this month after Mr. Biden failed to unite Democrats behind a large social policy bill that would have extended it. Most Republicans oppose the monthly grants, citing the cost and warning that unconditional aid, which they describe as welfare, discourages parents from working.

    Sharing some of those concerns, Senator Joe Manchin III, Democrat of West Virginia, effectively blocked the Biden plan, though he has suggested that he might support payments limited to families of modest means and those with jobs. The payments in the research project, called Baby’s First Years, were provided regardless of whether the parents worked.

    Third, and in continuation, it’s ridiculous to attach the approval for policies whose principles are clear and sound to the quality of data originating from scientific studies, which in turn depends on the quality of theoretical and experimental instruments scientists have at their disposal (“We hypothesized that infants in the high-cash gift group would have greater EEG power in the mid- to high-frequency bands and reduced power in a low-frequency band compared with infants in the low-cash gift group.”). And let’s not forget, on scientists coming along in time to ask the right questions.

    Fourth, do scientists and economists really have the liberty to study and report what they will? There are two ways to slice this. 1: To clarify the limited context in which this question is worth considering – not at all in almost all cases, and only when a study uncovers the scientific basis for something that isn’t well-served by such a basis. This principle is recursive: it should preclude the need for a scientific study of whether support for certain policies has been set back by the presence or absence of scientific studies. 2: where does the demand for these studies originate? Clearly someone somewhere thought, “Do we know the policy’s effects in the population?” Science can provide quick answers in some cases but not in others, and in the latter, it should be prevented from creating the impression that the absence of evidence is the evidence of absence.

    Who bears that responsibility? I believe that has fallen on the shoulders of politicians, social scientists, science communicators and exponents of the humanities alone for too long; scientists also need to exercise the corresponding restraint, and refrain from conducting studies in which they don’t specify the precise context (and not just that limited to science) in which their findings are valid, if at all. In the current case, NYT called the study’s findings “modest” – that the “researchers likened them in statistical magnitude to moving to the 75th position in a line of 100 from the 81st”. Modest results are also results, sure, but as we have come to expect with COVID-19 research, don’t conduct poor studies – and by extension don’t conduct studies of a social-science concept in a scientific way and expect it to be useful.