Who gets to be an expert?

Faculty Advisor
experts, evaluation
Abstract (summary)
In the past few months we have been flooded with graphs, models, and vocabulary about the spread of the virus. Here is a not-so-brief list of some of the words that appeared in newspapers, Twitter, and on Facebook in the first 30 days of the pandemic: Confirmed cases, presumptive cases, number of tests, number of positive tests, proportion of positive tests, log(2) scale, log(10) scale, exponential growth, linear growth, lagged effects, number of hospitalizations, number of patients on ventilators, number of ICU patients, deaths from COVID, deaths from COVID in hospitals compared to at home, time since the 10th confirmed case, percentage change, skewness, asymptomatic patients, deaths per million, deaths per 100,000, cases per million, infection rates, testing rates, percentage of positive rates, proportion of cases who have recovered, lag-corrected epidemiological curves, jurisdictional sampling, empirical vs. experimental results, modeling, r-nought, effective retransmission rate, false positives, false negatives, excess deaths, 7-day rolling average, contact tracing, community spread, social distancing, self-isolation, self-quarantine, flattening the curve. If you want to be an expert in infectious disease, these words are just the start of what you need to know. For the rest of us there are three choices: Learn all of these words and how to interpret the graphs associated with them, choose wisely which experts to follow, or ignore all of them and use “common sense.”
Publication Information
Maguson, D. & McGrath, J. (2020). Who gets to be an expert? CYC On-line, 258, 33-37. https://cyc-net.org/cyc-online/aug2020.pdf
Item Type
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