I have said it before and I will say it again, career politicians are not that intellectually adept. I mean, one can look back at their resumes and see striking similarities:
- Failed lawyer who couldn’t make it in the private sector.
- Failed businessperson who couldn’t make it in the private sector.
- Narcissist personality with terrible interpersonal communication skills – which are cancer in the private sector.
What this creates is a ruling class of people in government that are reactionary, immature, and tend to promote poor decision-making skills with no substance. Similarly, you see the same characteristics in students who are not engaged in courses as an educator. You see reactionary work in a rushed assignment that is cobbled together with no coherence. You see immature characteristics as they are the ones that ironically come with excuses about family or stress two hours before an exam or assignment due date – even when the assignment was handed out 4 weeks in advance. You see poor decision-making in time management such as severe procrastination, lack of study habits, and zero accountability to change even when grades reflect poorly.
Now, I know some might be saying “But Carson, maybe certain people are not cut out for academics”. I agree, so long as you agree certain people are not cut out for politics. With that said, students in academia are largely there for the right reasons and to make a one-to-one comparison of an academic to a politician is irresponsible and an insult to a first-year undergrad. However, with these characteristics so widespread in politics, it begs the question, are politicians in their positions for the right reasons? From my experience following politics from now – back to the student council in elementary school, politics were popularity contests. The loudest mouth in the room got the positions in government in a profession that is largely based on pathos with little concern for logic and ethics. I mean are there as many scandals in your office building that are present inside of government? Your business would be shut down within days if there was this level of unethical treachery.
To avoid a continuous rant about politicians, I am indeed ramping up to a point here. Regardless of how dumb politicians are, they are the ones who make policy decisions; as in, they are the ones who make the rules we follow on a day-to-day basis. That is why rigorous, effective data is now more important than ever as it runs downstream to policy influence. We have seen it in many instances, from covid to the war in Ukraine, to the current battle with affirmative action, and even the battle in Ontario right now between the government and teachers’ unions. Poor ideas beget poorer actions and outcomes have it be teachers with students or the government with its people. After all, governments engaged in the world’s biggest monkey-see-monkey-do with covid after China and Italy. But a pandemic is not the only thing that does this, it is a characteristic of our society.
Why do people, especially politicians, gravitate to bad data? Is it because good data is largely dry without many juicy, sensationalist details? There is some truth to this as in graduate school you are taught to do research and provide evidence, but also pump up the pathos a little bit so it has a better chance for publication – such as a catchy title, or a true but misdirected sentence in your conclusion to make people read more and want other academics to build on your research. Most researchers have heard of p-hacking which is an unethical research procedure that misrepresents data to find statistical significance with no underlying effect.
We saw this with masks as an individual study showing that they work for covid and are amplified in scientific journals and mainstream media, only to be discredited because of poor data analysis, bad methodology, or inflated significance findings. One can look at the Missouri Hairdresser Study that showed 139 clients being serviced by 2 hairstylists with covid and wearing masks as per city ordinance. The researchers concluded that out of the 67 that decided to be tested, all 67 were identified to have negative covid tests. What do you see wrong with this information? First, 67/139 is only 48%, meaning masks did not have a success rate of 100%, they only had a success rate of 48%. But we are not done there, as the study did not take into account seroprevalence and seasonality of respiratory viruses – failing to recognize May in Missouri with more air circulation covid is not spread as easily being aerosolized. What we can surmise is the potential that 51% had covid while wearing the masks during a time with low viral spread – that questions the study even further.
Second, you can see from the title “Absence of Apparent Transmission of SARS-CoV-2 from Two Stylists After Exposure at a Hair Salon with a Universal Face Covering Policy” playing up the scientific truism that masks stop transmission when implemented through a universal face covering policy which is now shown to be untrue. This is an example of poor data that was amplified through the media and accepted by the Center for Disease Control (CDC) in implementing policies for mask use. It is one thing when poor data is called out, there is plenty of that out there, it is when poor data is amplified by poor institutions to make poor policies with poor outcomes.
Another example is the use of the flawed ACLU study to ‘confirm’ systemic racism exists in the federal prison system via crack cocaine charges. There is no difference between crack cocaine and regular cocaine biologically, but the study omits different variables that need to be addressed in this field. What the study does not represent is that there are varying criminal justifications based on previous criminal activity and additional felonies at the time of arrest; for example, a word search of ‘prior convictions’ showed 0 results in the entire document. There is a discussion of felony convictions related to drugs, but not other variable felony convictions of rape and murder and other violent crimes which do have a racial disparity. Simply put, a gang member with previous convictions of burglary, sexual assault, and a weapons charge with crack cocaine is going to get more time in jail than a businessman with powder cocaine coming out of a nightclub regardless of race.
But again, this study fuels notions of systemic disparities when it does not tell the whole story. In turn, this narrative espoused in this document was – and still is – used to justify affirmative action within institutions. Again, there are worthwhile studies that can be done to discuss the torrid experience of African-Americans from slavery to Jim Crow, but it needs to be an efficient analysis such as Thomas Sowell and his observance of the fatherless home and the downfall of the African-American family.
Poor Data implies Poor Policies
Not Poor Data (Good Data) implies Not Poor Policies (Good Policies)
P → Q
¬P → ¬Q
The axiom above may be simplistic, but it is logically true. Not good data will lead to no good policy – so a remedy would be to have good data leading to good policy, leading to good outcomes. Now, this is easier said than done as we live in the era of post-truth and massive ignorance of facts and logic, but don’t worry, you can call this out. When you see bad data influence bad policies and they are universally bad with misleading – or outright lies – to confirm a presupposition that has no logical basis. You can delineate two outcomes:
- Unintelligent and scared
- Willfully ignorant and malicious
They’re no other options, either you’re dumb or a bad person. Consider this in the future as more and more stories similar are coming to the forefront and the past two years did not show any slowing down. Be prepared and arm yourself with logic and reason.
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