Critique of Hastings’ Presentation

Reconciling Institutional Biases with Evidence-based Research Regarding COVID-19

Advice for Critiquing Presentations:

  • Keep criticisms short and simple.
  • Provide one criticism at a time and ask for a response
    • Designed to prevent the presenter from an irrelevant counterattack on something else you’ve said.
  • For example,
    • Here’s one of your arguments:
      • Two studies conclude there’s no benefit to wearing masks.
        • A meta-analysis
        • Danish randomized control group studies
      • Therefore wearing masks is not supported by the scientific evidence
    • Fallacy of hasting generalization: generalizing from two studies to “the scientific evidence.”
      • What’s your response?
    • First study doesn’t support your conclusion because …
      • What’s your response?
    • Second study doesn’t support your conclusion because …
      • What’s your response?

Critique of Hastings’ Argument Regarding Masks

  • Hastings argues that the recommendation by Covid experts to wear masks is largely unsupported by scientific evidence. He cites two studies to support his claim. But the two studies are irrelevant to his claim.
    • One study is a meta-analysis of 67 randomized control group studies.
      • The analysis, however, is largely irrelevant to the efficacy of masks against Covid. As the study notes:
        • “There were no included studies conducted during the COVID-19 pandemic.”
        • The “studies were conducted in the context of lower respiratory viral circulation and transmission compared to COVID-19.”
    • The other study, a randomized controlled study, is also largely irrelevant.
      • Danish Study Doesn’t Prove Masks Don’t Work Against the Coronavirus factcheck.org
        • “As a result, the most that can be said is that this particular study, under the conditions at the time in Denmark, didn’t find that the face mask intervention had a large protective effect for wearers — not that masks provide no protection at all or don’t offer benefits to others.”
      • “Objective: To assess whether recommending surgical mask use outside the home reduces wearers’ risk for SARS-CoV-2 infection in a setting where masks were uncommon and not among recommended public health measures.”

Critiquing a Persuasive Essay

  • Three key questions:
    • What is the central thesis?
    • What’s the argument for the thesis?
    • Does the argument establish the thesis?

Central Thesis

  • What is Hastings’ central thesis?
  • On his last slide, Hastings says
  • Hastings also has two slides on bias, suggesting he thinks the reason many expert recommendations are not supported by scientific evidence is bias, e.g. groupthink.
  • Putting these together, Hastings’ central thesis is:
    • Many institutional/expert recommendations regarding Covid are largely unsupported by scientific evidence because of bias.

Argument

  • What is Hastings’ argument for the central thesis?
    • An argument is a piece of reasoning, from premises to a conclusion
    • Roughly,
      • Argument = Facts + Reasoning
    • View Arguments
  • People usually don’t state their arguments explicitly. They’ve got to be reconstructed.
  • Reconstructing Hastings’ Argument
    • Hastings supports his central thesis by citing eight expert opinions which he claims are largely unsupported by scientific evidence. 
      • The opinions appear on four slides titled “Comparing expert opinion vs. scientific evidence in COVID-19 pandemic (Edicts vs Evidence)”
    • But there’s got to be more to his argument. To support the central thesis, the argument has to say something about
      • bias
      • how to get from eight opinions to many opinions.
  • Hastings’ Argument, Reconstructed:
    1. Eight particular institutional/expert recommendations regarding Covid are largely unsupported by scientific evidence.
      • Regarding lockdowns, testing, closing schools, wearing masks, and so on.
    2. Bias is the only plausible explanation for expert recommendations unsupported by scientific evidence.
    3. Eight recommendations regarding Covid constitute many recommendations.
    4. Therefore, many institutional/expert recommendations regarding Covid are largely unsupported by scientific evidence because of bias.

Argument Assessment

  • Hastings’ argument fails to establish the central thesis:
    • Premise 1
      • I focus on masks, but briefly discus two other cases.
      • Hastings fails to show that the recommendation to wear masks is largely unsupported by the scientific evidence. See below
      • He also fails to show that recommendations for lockdowns and more testing are largely unsupported by the scientific evidence. See below
    • Premise 2
      • The second premise is required because Hastings presents no actual cases of bias, e.g. Fauci was biased when he said X.
      • The premise is false because bias isn’t the only reason an expert opinion might be unsupported by scientific evidence. Another reason is being honestly mistaken.
    • Premise 3
      • The third premise is required to generalize from eight opinions to many opinions.
      • The premise is unsupported. Hastings gives no reason for thinking the generalization is true.
Masks
  • Hastings argues that the recommendation by Covid experts to wear masks is largely unsupported by scientific evidence. He cites only two studies, both largely irrelevant.
    • One study is a meta-analysis of 67 randomized control group studies.
      • The analysis, however, is largely irrelevant to the efficacy of masks against Covid. As the study notes:
        • “There were no included studies conducted during the COVID-19 pandemic.”
        • The “studies were conducted in the context of lower respiratory viral circulation and transmission compared to COVID-19.”
    • The other study, a randomized controlled study, is also largely irrelevant.
      • Danish Study Doesn’t Prove Masks Don’t Work Against the Coronavirus factcheck.org
        • “As a result, the most that can be said is that this particular study, under the conditions at the time in Denmark, didn’t find that the face mask intervention had a large protective effect for wearers — not that masks provide no protection at all or don’t offer benefits to others.”
      • “Objective: To assess whether recommending surgical mask use outside the home reduces wearers’ risk for SARS-CoV-2 infection in a setting where masks were uncommon and not among recommended public health measures.”
  • Compare Hastings’ assessment of the scientific evidence (i.e. two largely irrelevant studies) with a recent assessment by factcheck.org
    • The Evolving Science of Face Masks and COVID-19, March 2, 2021 factcheck.org
      • Efficacy of masks depends on the quality and number of masks worn, how tightly they fit, the setting in which mask is worn.
      • Scientific studies of masks include
        • Lab-based Studies
        • Randomized Controlled Studies
        • Observational Studies
  • Four things of note about factcheck’s assessment:
    • Factcheck’s assessment supports the thesis that wearing masks is largely supported by scientific evidence, not largely unsupported.
    • The assessment cites more than just two studies
    • The experts in the assessment base their opinions on the scientific evidence.
    • The assessment provides no evidence the scientists are biased.
  • Hastings’ argument
    • The scientific evidence regarding wearing masks comprises studies A and B.
    • Studies A and B do not support wearing masks.
    • Therefore the scientific evidence does not support wearing masks.
Correlation and Causation
  • Beware drawing a causal conclusion from a statistical correlation.
    • The angular velocity of a wind turbine is correlated with wind speed. Therefore, wind turbines make the wind blow.
Lockdowns
  • Hastings argues that
    • lockdowns and shelter at home orders will reduce overall COVID deaths
  • is not supported by the scientific evidence because
    • U.S. states with higher lockdown policies are correlated with higher COVID death rates and higher case fatality rates, all other variables being equal
  • Hastings’ reasoning seems to be:
    • The correlation supports the thesis that lockdowns increase Covid deaths.
    • Therefore the correlation does not support the thesis that lockdowns reduce Covid deaths.
  • The more likely explanation of the correlation is that the authorities instituted more lockdowns because of the higher Covid death rates.
  • If so, the correlation provides no evidence against the efficacy of lockdowns.
  • Hastings’ Argument
    • If lockdowns were supported by scientific evidence, then higher state lockdowns would not be correlated with higher state COVID death rates.
    • Higher state lockdowns are correlated with higher state COVID death rates.
    • Therefore lockdowns are not supported by scientific evidence.
Ecological Fallacy
  • wikipedia.org/wiki/Ecological_fallacy
    • An ecological fallacy (also ecological inference fallacy[1] or population fallacy) is a formal fallacy in the interpretation of statistical data that occurs when inferences about the nature of individuals are deduced from inferences about the group to which those individuals belong.
  • britannica.com/science/ecological-fallacy
    • Ecological fallacy, also called ecological inference fallacy, in epidemiology, failure in reasoning that arises when an inference is made about an individual based on aggregate data for a group.
  • FPP page 148-149
    • Ecological correlations are based on rates or averages. They are often used in political science and sociology. And they tend to overstate the strength of an association. So watch out. 
    • Ecological correlations tend to overstate the strength of association.
    • Correlation in 1993 between average state income and average state education = 0.64.  But the correlation between individual income and individual education in 1993 = 0.44.
  • wikipedia.org/wiki/Ecological_fallacy#Robinson’s_paradox
    • A 1950 paper by William S. Robinson computed the illiteracy rate and the proportion of the population born outside the US for each state and for the District of Columbia, as of the 1930 census.[6] He showed that these two figures were associated with a negative correlation of −0.53; in other words, the greater the proportion of immigrants in a state, the lower its average illiteracy. However, when individuals are considered, the correlation was +0.12 (immigrants were on average more illiterate than native citizens). Robinson showed that the negative correlation at the level of state populations was because immigrants tended to settle in states where the native population was more literate. He cautioned against deducing conclusions about individuals on the basis of population-level, or “ecological” data.
  • data.covid.umd.edu/
    • percent staying home
    • percent of deaths among covid cases
  • Randomized Controlled Study
    • Subjects who stay home 100
      • no covid cases
      • no covid deaths
    • Subjects who don’t stay home 100
      • 50 covid cases
      • 20 covid deaths
    • P-value is close to zero
  • State A = 100 people
    • 70 Stay Home
    • 30 Don’t Stay Home
      • 30 cases of covid
      • 15 covid deaths
    • So 70% stay at home
    • Covid death rate is 15/30 = 50%
    • 70/50
  • State B = 100 people
    • 35 Stay Home
    • 65 Don’t Stay Home
      • 20 covid cases
      • 5 covid deaths
    • So 35% stay home
    • Covid death rate = 5/20 = 25%
    • 35/25
  • Correlation by state between
    • percentage of people who stay home
    • percentage of covid deaths
  • Correlation[{70, 50}, {35, 25}] = 1
More Testing
  • Hastings argues that
    • more COVID testing will reduce total COVID deaths
  • is not supported by the scientific evidence because
    • Increased testing rate is correlated with increased COVID mortality rate in the top 20 most populous countries. (See following linear regression graph)
  • Hastings’ reasoning seems to be:
    • The correlation supports the thesis that more testing increases Covid deaths.
    • Therefore the correlation does not support the thesis that more testing reduces Covid deaths.
  • The more likely explanation of the correlation is that the authorities increased testing because of the higher Covid death rates.
  • If so, the correlation provides no evidence against the efficacy of testing.