I often find myself disagreeing with academics, and particularly academic philosophers, about the value of journalism. Many of the philosophers I know look down on journalism; ordinary reportage seems philosophically jejune to them, and the arguments one finds in editorial writing tend to be weak on precision and rigor. There’s something to that, but I think it could with equal validity be said that academics lack the robust sense of reality and common sense that some of the best journalists tend to have. Sent out into the field, the average philosopher (or data-oriented social scientist) would, I think, quickly fall prey to some version of Meno’s paradox: not knowing what to look for at the outset of the inquiry, and not grasping the significance of what one encountered along the way. By contrast, journalists solve that apparent paradox every day–just without any sense that it is one.
I’ve known a lot of philosophers and a lot of journalists over the years, and have worked pretty closely with both. Each profession has its own set of assets and liabilities, but I think philosophers tend to be unnecessarily dismissive of the sheer detailed prosaic facticity that journalists tend to prize. Journalists want to know what actually happened–who, what, where, when, how (but generally not why). Philosophers tend to regard these merely contingent details as trivial. They tend to think in thought-experiments where the object of inquiry is why, and who, what, where (etc.) are independent variables that you can “play around with” at will. Such details don’t much matter, except as values of the variables you’re varying.
Thought experiments have their place, but believe it or not, life is not a thought experiment, and not all thought experiments are all that relevant to life as it’s actually lived by the actual people who actually live it. People on the ground have to make decisions on the ground in real time, given the evidence and resources available to them at the relevant time, and given the expected consequences as they see them at that time. They don’t have the luxury to sit in front of a computer, work out n! permutations of what might be the case, and work through them all after taking a refresher course in Bayesian probability theory. It would be a wonderful world if they could, but they can’t. A theorist who writes as though they can has no idea what the real world looks, feels, or is like. He’s not interested in the real world. He’s interested in a confabulated world of his own making, where he controls the values of all the relevant variables, and gets to dress people down because they don’t.
Which brings us back to journalism. If you want to do applied applied ethics–the ethics of figuring out what to do at a given time, in real time, at real places, with real people in them–then the purely descriptive details matter, both evaluatively and prescriptively. You can’t avert your eyes from them, change the subject, or “bracket” them by relying on thought experiments or on qualifications like “ceteris paribus,” “prima facie,” or “ex hypothesi.” And discovering and/or recording them is no trivial matter, and no easy skill to acquire. Anyone who doubts this should try to describe the events at an accident or crime scene that they’ve just witnessed, or be cross-examined in an interrogation or inquest of some kind, or for that matter, figure out what’s really happened when it appears prima facie that your spouse has been unfaithful to you. The ambiguities involved are the stuff of high art and deep controversy–better captured in novels, films, and historiography than in philosophy or social science.
Put another way, it’s one thing to put data through SPSS or Excel once someone else has gathered it for you, and another to gather it yourself from the field. Social scientists routinely do the former, but journalists (or their functional equivalents) often do the latter, at least for naturalistic experiments. Don’t knock data collection until you’ve done it.*
In one of several extremely dumb essays he’s written on the coronavirus, Jeffrey Tucker offers up a standard dogma on this subject: data analysis is a scientific enterprise, but “data in general rely on collection, which is itself an unscientific enterprise” (“An Epistemic Crisis,” Coronavirus and Economic Crisis, p. 174). Well, “scientific” or not, data collection is where inquiry has its direct encounter with that inconvenient thing, reality. So data collection matters more than you might think, assuming that the data you want to analyze is data connected to the real world. Do it wrong, and you get the wrong results.
To that end, here are two items from NJ.com, a consortium website that compiles stories from regional papers in New Jersey.
The first is a useful rejoinder to the complacent belief that now that New York and New Jersey have “flattened the curve,” all is well in our hospitals; on this view, the crisis has passed, and health workers are just twiddling their thumbs for lack of patients and lack of work to do.
The story above happens to be about Hackensack University Medical Center in Hackensack, New Jersey, about fifteen minutes from my university. I don’t know how true it is of other places. Some of what it says dates back a few weeks (to the third week of April), and some fast-forwards to the present. Since things have calmed down a great deal since the worst part of the surge in April, there is intense pressure, understandably, to deal with the backlog of non-COVID cases waiting to be treated. Intuitively, you’d think that now that the surge has passed, things can hurry up and get back to normal.
“We have made so much progress in the last two weeks by consistently discharging more patients than we are admitting each day,’’ said Mark Sparta, president and chief executive officer of Hackensack University Medical Center, noting the facility has discharged more than 1,100 patients and ICU volumes have declined by more than 25 percent.
I agree that dealing with the non-COVID backlog is a high priority matter–the highest priority matter. To some extent, hospitals are (gradually) starting to work on it. But there are three impediments here to moving any faster than they already are.
One is that people are (reasonably) afraid to go to the hospital for fear of being infected by COVID patients. Another is that physicians and administrators are (reasonably) anxious about admitting them for the same reason. And a third is that while COVID cases are on the decline, there is no certainty about what that means. In the absence of certainty, caution is warranted. A standard figure holds that hospitals need 25-30% spare ICU capacity to be ready for another surge. But that figure is easier to talk about than bring about, and given that we’re starting to “open up,” and nursing home patients are now starting to pour in, no hospital wants to be caught short-handed because it prematurely brought non-COVID patients in for elective procedures.
Discussion of this topic is not advanced by simply noting that cases or hospitalizations are on a steady decline. The relevant issue is not a simple decline in cases, but spare availability of emergency/intensive/critical care resources relative to particular regions, where “resources” includes EMS services, and EMS personnel, as well as beds, equipment and personnel throughout emergency departments, ICUs and critical care units in hospitals–given the possibility of a second surge. There are a lot of variables to juggle there, and a lot of unavoidable unknowns.
It’s worth remembering that for all of the happy-face stories you may have seen about how the hospitals weren’t overrun in New York or New Jersey, in fact they were overrun at the peak of the surge. The difficult question is whether they still qualify as overrun. During the peak of the surge, anywhere up to nine north Jersey hospitals were at some point overrun, and put on divert status. This despite the facts that:
- all of these hospitals had stopped taking non-emergency non-COVID patients;
- all had physically expanded their facilities to admit the expected influx of COVID patients;
- all had converted non-critical care space (even office space) to critical or intensive care space;
- all had put personnel on crisis schedules (prohibiting anyone from calling out for any reason but medical disability);
- all had forced non-specialists to come in and be trained to handle COVID patients on pain of losing their jobs (diverting specialists to train them);
- some had called military physicians in for assistance;
- many had called in out-of-state practitioners for assistance;
- the State had set up military field hospitals in Secaucus and Edison to handle patient overflow;
- the State had to call on FEMA’s EMS service, parking 100 out-of-state ambulances at the Meadowlands to respond to emergency calls in north Jersey;
- EMS services had turned 911 calls away at the point of service and were told not to bring non-resuscitated arrest patients into the hospital, essentially leaving them to die;
- hospitals had been forced to beg for ventilators from wherever they could be found;
- health care workers went without PPE, and were eventually supplied PPE by citizen- volunteers who stepped up to provide it;
- health care workers had to rely on citizen-volunteers for meals; and
- for awhile many health care workers who tested COVID positive had nowhere to live.**
There’s no way to live through a situation this abnormal and then revert to the mean of business-as-usual normality within a week or two or three. It will take time. And this isn’t to factor in the emotional well-being of the practitioners themselves: the across-the-board fatigue, disillusionment, anger, and grief they’ve experienced, a large topic of its own.
Add to that the following obvious consideration from the story:
The morning goes on, another routine day amid a crisis that now feels all too familiar.
But Sugalski is haunted by the terrifying question that keeps popping into his mind: When is the second wave coming?
“I’m still worried,” Sugalski says, “about another spike.”
In other words: what if we have to do what we just did all over again? It’s a real possibility. And what if things are worse the second time around than they were the first? How many iterations of this kind of damage will our health care system be able to withstand before it breaks? If it does break, how helpful will it be that we’ve “opened up the economy”? Can we run an economy without a functioning health care system?
Nor is the issue confined to the mid-Atlantic states, or those states plus Detroit, Chicago, Atlanta, Miami, LA, etc.. Our medical system was a wreck before the pandemic. And the worst part of the wreckage was in flyover country, not the coasts. Both reported cases and deaths are lagging indicators relative to actual infection rates and potential mortality in this pandemic. So the fact that reported deaths and reported cases are (relatively) low in flyover country doesn’t tell you what the summer will bring. The outlook for flyover country is unclear, but it is not obviously good.
To put the point bluntly: if you’re not asking basic logistical questions about how we’re going to handle a second spike or surge, you’re fundamentally out of touch with reality.*** But a lot of academics are. I had an argument the other day with a conservative sociologist who just couldn’t process the idea that things ever really got all that bad in New York and New Jersey. And even if they were bad then, things are fine now, so what’s the big deal? People who don’t take reality in the first time around can’t be trusted to take it in the second. If you haven’t yet figured out how bad things got here, I’m not sure you ever will.
Ever since Thomas Nagel’s pioneering paper “What Is It Like to Be a Bat?” philosophers have been sensitized to the importance of what could be called the phenomenology of internal experience–what it’s like to be or undergo something unusual. In my experience, journalists (as well as novelists and poets) tend to be better at capturing and appreciating what things are like than philosophers or social scientists.
To that end, I highly recommend this photo essay, “24 Hours in Crisis,” about a day of life in New Jersey. It’s prize-winning material, fully as valuable as anything you’ll read this year in Mind, Nous, Ethics, or Philosophy and Public Affairs. It’s heartbreaking and beautiful, and for those of us who live in New Jersey, it’s a poignant reminder of the familiar places that the pandemic has now transformed or placed out of reach. I’ve never read anything that so perfectly captures the flavor of life in Jersey. An acquired taste, to be sure, but one worth savoring once you’ve acquired it.
*Yes, I’ve done it. I did field work for the U.S. History Assessment of the National Assessment for Educational Progress in 2001, and for the paper that Gary Alan Fine and I did on the 9/11 celebration rumors in Paterson, New Jersey.
For an excellent discussion of “scientific” complacency about data collection in a specifically epidemiological context, see Peter Kramer’s Ordinarily Well: The Case for Antidepressants. Kramer offers a cogent critique of the armchair demand by academic psychologists that clinicians rely exclusively on gold-standard methodological techniques in making clinical decisions in the consultation room (e.g., either double-blind random controlled drug trials or non-prescription). The book also contains a useful critique of supposedly sophisticated psychological research that relies on dubious but under-scrutinized methods of data collection. Much that Kramer says can be applied to hand-waving criticisms of the methodological failings of epidemiology in the COVID-19 crisis.
**In the interests of time, I have not documented every single claim in this bulleted list, but suffice it to say that each one has been documented somewhere in the public record.
***For a good early discussion that asks the right questions but makes extremely understated assumptions, see Moghadas et al, “Projecting hospital utilization during the COVID-19 outbreaks in the United States,” Proceedings of the National Academy of Sciences 117:16 (April 21, 2020), submitted March 4, 2020, posted online March 19, 2020). Given their parameters, the authors’ predictions were borne out, at least in the New York-New Jersey area. But the parameters themselves (described in the penultimate paragraph of p. 9125) far too optimistically assume effective isolation of COVID patients within hospitals, and ignore asymptomatic and pre-symptomatic transmission. They also make “overall projections at a national level,” ignoring what we now know is the spatially heterogeneous nature of the disease vector. But the general approach is sound, and correctly indicates “the inadequacy of critical care capacity to handle the burgeoning outbreak.”