Quotulatiousness

November 7, 2020

Misunderstanding what is meant by “mineral reserves”

Filed under: Economics, Environment — Tags: , , , — Nicholas @ 05:00

It seems to happen almost as regularly as Old Faithful, as someone blows a virtual gasket over the reserves of this or that mineral “running out” in x number of years. Tim Worstall explains why this is a silly misunderstanding of what the term “mineral reserves” actually means:

“Aerial view of a small mine near Mt Isa Queensland.” by denisbin is licensed under CC BY-ND 2.0

It’s not exactly unusual to see some environmental type running around screaming because mineral reserves are about to run out. The Club of Rome report, the EU’s “circular economy” ideas, Blueprint for Survival, they’re all based upon the idea that said reserves are going to run out.

They look at the usual listing (USGS, here) and note that at the current rate of usage reserves will run out in 30 to 50 years. Entirely correct they are too. It’s the next step which is such drivelling idiocy. For the claim then becomes that we will run out of those metals, those minerals, when the reserves do. This being idiot bollocks.

For a mineral reserve is, as best colloquial language can put it, the stuff we’ve prepared for use in the next few decades. Like, say, 30 to 50 years. That we’re going to run out of what we’ve got prepared isn’t a problem. For we’ve an entire industry, mining, whose job to to go prepare some more for us to use.

[…] A mineral reserve is something created by the mining company. Created by measuring, testing, test extracting and proving that the mineral can be processed, using current technology, at current prices, and produce a profit. Proving that this is not just dirt but is in fact ore.

Mineral reserves are things we humans make, not things that exist.

October 15, 2020

QotD: What the GDP is failing to show (even though it’s there)

Filed under: Economics, Quotations, Technology — Tags: , , , , , — Nicholas @ 01:00

There simply isn’t a technology that has come anywhere close to arriving in the hands of actual users as fast as the smartphone and mobile internet. The next closest competitor is the mobile phone itself. All others running distant third and behind.

Our problem is that we know technological revolutions produce growth. Yet economic growth is limp at best, meagre perhaps a better description. So, there’s something wrong here. Either our basic understandings about how growth occurs are wrong and we [are] loathe to agree to that. Not because too much is bound up in that understanding but because too much of it makes sense. The other explanation is that we’re counting wrong.

[…]

We know that we’ve not quite got new products and their falling prices in our estimates of inflation quite correctly. They tend to enter the inflation indices after their first major price falls, meaning that inflation is always overstated. Given that the number we really look at is real growth – nominal growth minus inflation – this means we are consistently underestimating real growth.

[…]

The more we dig into this the more convinced I am that our only real economic problem at present is counting. Everything makes sense if we are counting output and inflation incorrectly, under-estimating the first, over- the second. If we are doing that – and we know that we are, only not quite to what extent – then all other economic numbers make sense. We’re in the midst of a large technological change, we’ve full employment by any reasonable measure, wages and productivity should be rising strongly. If we’re mismeasuring as above then those two are rising strongly, we’re just not capturing it. Oh, and if that’s also true then inequality is lower than currently estimated too.

The thing is, the more we study the details of these questions the more it becomes clear that we are mismeasuring, and mismeasuring enough that all of the claimed problems, the low growth, low productivity rises, low wage growth, simply aren’t there in the first place. And if they ain’t then nothing needs to be done about them, does it? Except, perhaps, count properly.

Tim Worstall, “Where’s All The Economic Growth? Goldman Sachs Blames Apple’s iPhone”, Continental Telegraph, 2018-07-03.

October 9, 2020

QotD: How to analyze complex multivariate systems for the popular press

Filed under: Media, Quotations, Science — Tags: , , , , — Nicholas @ 01:00

  1. Choose a complex and chaotic system that is characterized by thousands or millions of variables changing simultaneously (e.g. climate, the US economy)
  2. Pick one single output variable to summarize the workings of that system (e.g. temperature, GDP)
  3. Blame (or credit) any changes to your selected output variable on one single pet variable (e.g. capitalism, a President from the other party)
  4. Pick a news outlet aligned with your political tribe and send them a press release
  5. Done! You are now a famous scientist. Congratulations.

Warren Meyer, “Modern Guide to Analyzing Complex Multivariate Systems”, Coyote Blog, 2018-06-25.

 

 

 

 

 

August 28, 2020

National “cheater density” for popular online games

Filed under: Business, China, Gaming, Technology — Tags: , — Nicholas @ 05:00

Richard Currie summarizes the findings of Ruby Fortune’s cheater research (note that there’s no data on China because reasons):

Ever torn your keyboard from the desk and flung it across the room, vowing to find the “scrub cheater” who ended your run of video-gaming success? Uh, yeah, us neither, but a study into the crooked practice might help narrow down the hypothetical search.

The research, carried out by casino games outfit Ruby Fortune, has produced a global heatmap of supposed cheater density.

According to the website, this was done by analysing “search trend and search volume data to reveal where in the world is most likely to cheat while playing online multiplayer video games”. The report looks at the frequency of search engine queries for the most-played video games and measures them against searches for related cheat codes, hacks and bots, to show which country has the highest density of cheaters, and which cheat categories are the most popular in each location.

[…]

There is a massive hole in the data, however, thanks to the Great Firewall of China, which has a terrible reputation for ruining the experience of online games.

If there was any doubt that the Middle Kingdom would otherwise take Brazil’s crown, consider that Dell once advertised a laptop for the market by saying it was especially good for running PUBG plugins to “win more at Chicken Dinner”, a reference to the “Winner winner chicken dinner” message that comes up on a victory screen.

Data from the Battle Royale granddad’s anti-cheat tech provider, BattlEye, has also suggested that at one point 99 per cent of banned cheaters were from China.

August 16, 2020

This is a “hockey stick” graph you can believe

Filed under: Economics, Health, History — Tags: , , , , , — Nicholas @ 03:00

Brian Micklethwait says this graph, unlike the more famous (debunked) “hockey stick”, shows one of the most important moments in human history:

If that graph, or another like it, is not entirely familiar to you, then it damn well should be. It pinpoints the moment when our own species started seriously looking after its own creature comforts. This was, you might say, the moment when most of us stopped being treated no better than farm animals, and we began turning ourselves into each others’ pets.

Patrick Crozier and I will be speaking about this amazing moment in the history of the human animal in our next recorded conversation. That will, if the conversation happens as we hope and the recording works as we hope, find its way to here.

I’m not usually one for podcasts, in the same way that I’m not an audiobook user: I find I’m unable to do other things while listening to the spoken word, and it’s always far faster to read a text than to have it read to you. In this particular case, I might try to make an exception, and give up hope of doing anything else productive while I listen.

August 8, 2020

Andrew Sullivan – “[T]he Kendi test: does the staff reflect the demographics of New York City as a whole?”

Filed under: Business, Media, Politics, USA — Tags: , , , , — Nicholas @ 05:00

In his latest Weekly Dish, Andrew Sullivan looks at an earnest diversity initiative of The Newspaper Guild of New York:

I’m naming this after Ibram X. Kendi because his core contribution to the current debate on race is the notion that “any measure that produces or sustains racial inequity between racial groups” is racist. Intent is irrelevant. I don’t think many sane people believe A.G. Sulzberger or Dean Baquet are closet bigots. But systemic racism, according to Kendi, exists in any institution if there is simply any outcome that isn’t directly reflective of the relevant racial demographics of the surrounding area.

The appeal of this argument is its simplicity. You can tell if a place is enabling systemic racism merely by counting the people of color in it; and you can tell if a place isn’t by the same rubric. The drawback, of course, is that the world isn’t nearly as simple. Take the actual demographics of New York City. On some measures, the NYT is already a mirror of NYC. Its staff is basically 50 – 50 on sex (with women a slight majority of all staff on the business side, and slight minority in editorial). And it’s 15 percent Asian on the business side, 10 percent in editorial, compared with 13.9 percent of NYC’s population.

But its black percentage of staff — 10 percent in business, 9 percent in editorial — needs more than doubling to reflect demographics. Its Hispanic/Latino staff amount to only 8 percent in business and 5 percent in editorial, compared with 29 percent of New York City’s demographics, the worst discrepancy for any group. NYT’s Newsroom Fellowship, bringing in the very next generation, is 80 percent female, 60 percent people of color (including Asians), and, so far as I can tell, one lone white man. And it’s why NYT‘s new hires are 43 percent people of color, a definition that includes Asian-Americans.

But notice how this new goal obviously doesn’t reflect New York City’s demographics in many other ways. It draws overwhelmingly from the college educated, who account for only 37 percent of New Yorkers, leaving more than 60 percent of the city completed unreflected in the staffing. It cannot include the nearly 19 percent of New Yorkers in poverty, because a NYT salary would end that. It would also have to restrict itself to the literate, and, according to Literacy New York, 25 percent of people in Manhattan “lack basic prose literary skills” along with 37 percent in Brooklyn and 41 percent in the Bronx. And obviously, it cannot reflect the 14 percent of New Yorkers who are of retirement age, or the 21 percent who have yet to reach 18. For that matter, I have no idea what the median age of a NYT employee is — but I bet it isn’t the same as all of New York City.

Around 10 percent of staffers would have to be Republicans (and if the paper of record nationally were to reflect the country as a whole, and not just NYC, around 40 percent would have to be). Some 6 percent of the newsroom would also have to be Haredi or Orthodox Jews — a community you rarely hear about in diversity debates, but one horribly hit by a hate crime surge. 48 percent of NYT employees would have to agree that religion is “very important” in their lives; and 33 percent would be Catholic. And the logic of these demographic quotas is that if a group begins to exceed its quota — say Jews, 13 percent — a Jewish journalist would have to retire for any new one to be hired. Taking this proposal seriously, then, really does require explicit use of race in hiring, which is illegal, which is why the News Guild tweet and memo might end up causing some trouble if the policy is enforced.

And all this leaves the category of “white” completely without nuance. We have no idea whether “white” people are Irish or Italian or Russian or Polish or Canadians in origin. Similarly, we do not know if “black” means African immigrants, or native black New Yorkers, or people from the Caribbean. 37 percent of New Yorkers are foreign-born. How does the Guild propose to mirror that? Ditto where staffers live in NYC. How many are from Staten Island, for example, or the Bronx, two places of extremely different ethnic populations? These categories, in other words, are incredibly crude if the goal really is to reflect the actual demographics of New York City. But it isn’t, of course.

My point is that any attempt to make a specific institution entirely representative of the demographics of its location will founder on the sheer complexity of America’s demographic story and the nature of the institution itself. Journalism, for example, is not a profession sought by most people; it’s self-selecting for curious, trouble-making, querulous assholes who enjoy engaging with others and tracking down the truth (at least it used to be). There’s no reason this skillset or attitude will be spread evenly across populations. It seems, for example, that disproportionate numbers of Jews are drawn to it, from a culture of high literacy, intellectualism, and social activism. So why on earth shouldn’t they be over-represented?

And that’s true of other institutions too: are we to police Broadway to make sure that gays constitute only 4 percent of the employees? Or, say, nursing, to ensure that the sex balance is 50-50? Or a construction company for gender parity? Or a bike messenger company’s staff to be reflective of the age demographics of the city? Just take publishing — an industry not far off what the New York Times does. 74 percent of its employees are women. Should there be a hiring freeze until the men catch up?

July 15, 2020

QotD: State and private charity

Filed under: Economics, Government, Quotations — Tags: , , , — Nicholas @ 01:00

Some social and political analysts regard private help as a bad thing. They speak of the “problem” of food banks, and of America’s “miserly” support for poorer countries. In fact food banks are a solution, not a problem. Private generosity has leapt into the breach to help tide people over temporary problems. The great majority of food bank users do so only once.

Similarly with US aid to poorer countries. The United States is regularly berated for being very low on the list of aid givers, but this only applies to government-to-government aid. Once the private contributions made by Americans to people in poorer countries are counted in, the US rises to the top. In fact US private help is better spent, usually going to people to spend in towns and villages in the local economy, rather than on gold palaces and white elephant steel mills in the desert.

Part of this mismatch arises from the fact that these analysts seem to wear spectacles that admit only light of a political wavelength and ignore private generosity. The latest victim of this myopia is the “bank of mom and dad.” It is assumed to be a bad thing that young people should turn to mom and dad to help out with deposits and mortgages.

“Richard”, “Is Private Help a Bad Thing? – Political Spectacles of the Left”, Continental Telegraph, 2018-04-02.

June 19, 2020

The economy isn’t all huge corporations and government

Filed under: Britain, Business, Economics — Tags: , , , — Nicholas @ 03:00

Paul Sellers reminds us that the economy is far more than just the big names that get mentioned in the financial pages:

An example of the kind of one-man businesses Paul is talking about.

Independents in micro-businesses are few and far between and often hard to discover, despite the internet’s ever-increasing web of enterprises. The backbone of British industry is made up of small, independent people striving to retain a measure of individualism, independence and entrepreneurialism in their lives. Statistics from 2019 show that in Britain there were 5.82 million small businesses responsible for 99.3% of the total business output in the UK.

Small businesses here comprise those with 0-49 employees and digging deeper still into what might at first seem more irrelevant than relevant is that the niche that small businesses fill in the real world of enterprise. Over 76% of businesses are operated by one-man bands; single-person enterprises who operate alone comprise almost 4.5 million men and women. With an additional 1.15 million micro-business (1-9 employees) around 95% of businesses here operate on a strength of under just 10 people. So over 99% of small to medium business enterprises, that’s zero to 249 employees, but only 0.6% have a workforce of 50-249 employees. Less than 4% are small businesses with 10-49 staff members and get this, over 95% operate as micro-businesses with 0-9 employees. What does this tell you about businesses output? What it tells me is how little of this is newsworthy by the mass media manufacturing companies (Like BBC News and ITV, Sky and so on) who constantly tell us about how many this massive company or that massive company is laying off and how little this really affects our economy because the little guys still get out into their little micro-shops and make what cannot work work.

June 2, 2020

QotD: Economic inequality

Filed under: Economics, Quotations — Tags: , — Nicholas @ 01:00

Economic inequality […] is both highly moralized (right-thinking people agree it’s the root of all evil) and intellectually devilishly complex, far more than people acknowledge. For example, if “the bottom fifth” earns the same proportion of income in 1980 and 2010, it doesn’t mean anyone’s income stagnated: these “fifths” are different people, and they earn a fifth of different totals. Also, it’s not clear that inequality (as opposed to poverty) is a moral abomination, or that reducing it is progress. As Walter Scheidel argues in The Great Leveler (another superb book of 2017), the most effective ways of reducing inequality are epidemics, massive wars, violent revolutions and state collapse.

Steven Pinker, “Twenty Questions with Steven Pinker”, Times Literary Supplement, 2018-02-18.

May 31, 2020

QotD: Measuring what can be measured

Filed under: Quotations — Tags: — Nicholas @ 01:00

There are things that can be measured. There are things that are worth measuring. But what can be measured is not always what is worth measuring; what gets measured may have no relationship to what we really want to know. The costs of measuring may be greater than the benefits. The things that get measured may draw effort away from the things we really care about. And measurement may provide us with distorted knowledge – knowledge that seems solid but is actually deceptive.

Jerry Z. Muller, The Tyranny of Metrics, 2018.

May 24, 2020

QotD: The “balance of trade”

Filed under: Economics, Quotations — Tags: , , — Nicholas @ 01:00

Joseph Schumpeter [wrote in] History of Economic Analysis (1954):

    The first thing to observe about this concept [of the balance of trade] is that it is in fact an analytic tool. The balance of trade is not a concrete thing like a price or a load of merchandise.

Yes (although it is even more accurate to describe the balance of trade as an accounting convention). If, for example, it had been decided to record purchases and sales of real estate on the current account rather than on the capital account, the size of each country’s current-account deficit or surplus would be different even though absolutely nothing real in the national or global economy would be changed. And yet to hear any of the many protectionists bemoan their country’s trade- or current-account deficit is to hear people who typically mistake this accounting convention for a concrete thing. Such complaints almost always reflect utter misunderstanding of so-called “trade balances.”

Don Boudreaux, “Bonus Quotation of the Day…”, Café Hayek, 2018-01-21.

May 9, 2020

Lies, damned lies, and even-more-damned statistics

Filed under: Government, Health, Science — Tags: , , , — Nicholas @ 05:00

David Warren does not trust “the numbers” (and I think he’s quite right to doubt):

At some point — but it is seldom a discrete moment in space or time — the weight of the anecdotal in science, or that of the circumstantial in law, becomes overwhelming. This is the opposite of a statistical fact, in part because there are no statistical facts. I am reminded of this whenever the “scientific” control freaks of statistics lay down some law, indifferent to the Law in nature. The difference between 999,999 and one million is, in any imaginable situation, not a difference at all. Where it is made the basis for a decision, that decision is arbitrary, and not infrequently, cruel. By contrast, such differences as those between pregnant and not pregnant, dead and not dead, are unchallengeably significant. They are in the realm of meaning.

I am reminded of this hourly or better, these days, when consulting the news. All readers of the mass media (accurately described by Trump as “fake news”) are being covered, constantly, by the vomit of statistics — few with any context, and many knowingly false. They “look scientific,” which is to say, they answer to the moron’s conception of science. In “disciplines” like economics, today, and throughout the other social sciences, the participants sleepwalk. Nobel prizes are given out for numerical sludge, presented to the purpose of selling one destructive “policy” or another, that will be imposed on real, live, particular human beings. The same is true of the “mathematical biology” that has disinformed all our public health “professionals.”

The Red Chinese Batflu, now transforming our world, is a spectacular case in point. Not only the epidemiological projections, but even the counts of dead and wounded, are taken on faith — from people who are characteristically faithless. Information on prevention and cures is hostage to the work of statisticians. “Double blind tests,” which would be absolutely immoral — wicked — on human subjects facing life or death — are demanded by our medical apes.

May 5, 2020

The perverse incentives of the Wuhan Coronavirus outbreak

Filed under: Economics, Government, Health, Media — Tags: , , , — Nicholas @ 03:00

David Warren has clearly taken his cynical pills today:

The daily count of deaths from the Red Chinese Batflu is among the prized, scare-mongering features of our mass media. I am among those who consider these numbers to be significantly overstated, for a reason that Nikolai Gogol would understand. Each corpse is worth cash to some public authority, usually from a higher authority; and as always, finally from the taxpayers. Each also saves money for government programmes, that can be reallocated to the purchase of new votes. As the corpse providers from this virus are very old, and suffering from other life-threatening conditions, in almost every case, this statistical inflation is easy to perform. Death certificates are issued for any who died with “Covid-19,” whether or not they died from it, and more are then added of those who were never tested. Anything respiratory will do. It’s all judgement calls — on which side of the bread is buttered.

Compare if you will the Hong Kong Flu of 1968 and 1969. I was just reading a memoir, from down that memory hole. The death toll was actually higher then, than ours is now, and from within a smaller population; the victims included children and the young. Yet there were no interruptions in economic life; no public emergency theatricals; and at the height of the second wave of that scourge, we had events like Woodstock. (Those were the days, my friend.)

A neat way to correct for all our “judgement calls” might be to look at overall death rates, and see if they have risen or fallen. It is too early to get a clear view, but soon it may be too late, for vested interests will have tampered with them. All my life I have been learning to trust statistics, less — especially from those who dress in labcoats and affect that earnest look. Sometimes an exception must be considered, however. An unpredictable minority may be honest; some others might get numbers right by mistake.

April 12, 2020

QotD: The Gini coefficient

Filed under: Economics, Government, Politics, Quotations, USA — Tags: , , , , — Nicholas @ 01:00

At least for now, most progressives acknowledge that markets and economic growth are necessary. But progressives in academia contend that growth has proved itself secondary to equality efforts — something to be exploited, rather than appreciated. Not just nationally, but worldwide, policymakers and the press regard the subordination of growth to equality to be a benign practice, as in the recent line in the Indian periodical Mint: a policy aimed at “reducing inequality need not hurt growth.”

The redistributionist impulse has brought to the fore metrics such as the Gini coefficient, named after the ur-redistributor, Corrado Gini, an Italian social scientist who developed an early statistical measure of income distribution a century ago. A society where a single plutocrat earns all the income ranks a pure “1” on the Gini scale; one in which all earnings are perfectly equally distributed, the old Scandinavian ideal, scores a “0” by the Gini test. The Gini Index has been renamed or updated numerous times, but the principle remains the same. Income distribution and redistribution seem so crucial to progressives that French economist Thomas Piketty built an international bestseller around it, the wildly lauded Capital.

Through Gini’s lens, we now rank past eras. Decades in which policy endeavored or managed to even out and equalize earnings — the 1930s under Franklin Roosevelt, the 1960s under Lyndon Johnson — score high. Decades where policymakers focused on growth before equality, such as the 1920s, fare poorly. Decades about which social-justice advocates aren’t sure what to say — the 1970s, say — simply drop from the discussion. In the same hierarchy, federal debt moves down as a concern because austerity to reduce debt could hinder redistribution. Lately, advocates of economically progressive history have made taking any position other than theirs a dangerous practice. Academic culture longs to topple the idols of markets, just as it longs to topple statutes of Robert E. Lee.

But progressives have their metrics wrong and their story backward. The geeky Gini metric fails to capture the American economic dynamic: in our country, innovative bursts lead to great wealth, which then moves to the rest of the population. Equality campaigns don’t lead automatically to prosperity; instead, prosperity leads to a higher standard of living and, eventually, in democracies, to greater equality. The late Simon Kuznets, who posited that societies that grow economically eventually become more equal, was right: growth cannot be assumed. Prioritizing equality over markets and growth hurts markets and growth and, most important, the low earners for whom social-justice advocates claim to fight. Government debt matters as well. Those who ring the equality theme so loudly deprive their own constituents, whose goals are usually much more concrete: educational opportunity, homes, better electronics, and, most of all, jobs. Translated into policy, the equality impulse takes our future hostage.

Amity Shlaes, “Growth, Not Equality”, City Journal, 2018-01-21.

April 8, 2020

If the Wuhan Coronavirus panic feels oddly familiar … there’s a good reason for it

Warren Meyer explains why his skepticism about the dangers of the Wuhan Coronavirus epidemic kicked in quickly because it followed a very familiar pattern:

I have been skeptical about extreme global warming and climate change forecasts, but those were informed by my knowledge of physics and dynamic systems (e.g. feedback mechanics). I have been immensely skeptical of Elon Musk, but again that skepticism has been informed by domain knowledge (e.g. engineering in the case of the hyperloop and business strategy in the case of SolarCity and Tesla). But I have no domain knowledge that is at all relevant to disease transfer and pathology. So why was I immediately skeptical when, for example, the governor of Texas was told by “experts” that a million persons would die in Texas if a lock-down order was not issued?

I think the reason for my skepticism was pattern recognition — I saw a lot of elements in COVID-19 modelling and responses that appeared really similar to what I thought were the most questionable aspects of climate science. For example:

  • We seem to have a sorting process of “experts” that selects for only the most extreme. We start any such question, such as forecasting disease death rates or global temperature increases, with a wide range of opinion among people with domain knowledge. When presented with a range of possible outcomes, the media’s incentives generally push it to present the most extreme. So if five folks say 100,000 might die and one person says a million, the media will feature the latter person as their “expert” and tell the public “up to a million expected to die.” After this new “expert” is repetitively featured in the media, that person becomes the go-to expert for politicians, as politicians want to be seen by the public to be using “experts” the public recognizes as “experts.”
  • Computer models are converted from tools to project out the implications of a certain set of starting hypotheses and assumptions into “facts” in and of themselves. They are treated as having a reality, and a certainty, that actually exceeds that of their inputs (a scientific absurdity but a media reality I have observed so many times I gave it the name “data-washing”). Never are the key assumptions that drive the model’s behavior ever disclosed along with the model results. Rather than go on forever on this topic, I will refer you to my earlier article.
  • Defenders of alarmist projections cloak themselves in a mantle of being pro-science. Their discussions of the topic tend to by science-y without being scientific. They tend to understand one aspect of the science — exponential growth in viruses or tipping points in systems dominated by positive feedback. But they don’t really understand it — for example, what is interesting about exponential growth is not the math of its growth, but what stops the growth from being infinite. Why doesn’t a bacteria culture grow to the mass of the Earth, or nuclear fission continue until all the fuel is used up? We are going to have a lot of problem with this after COVID-19. People will want to attribute the end of the exponential growth to lock-downs and distancing, but it’s hard to really make this analysis without understanding at what point — and there is a point — the virus’s growth would have turned down anyway.
  • Alarmists who claim to be anti-science have a tendency to insist on “solutions” that have absolutely no basis in science, or even ones that science has proven to be utterly bankrupt. Ethanol and wind power likely do little to reduce CO2 emissions and may make them worse, yet we spend billions on them as taxpayers. And don’t get me started on plastic bag and straw bans. I am willing to cut COVID-19 responses a little more slack because we don’t have the time to do elaborate studies. But just don’t tell me lockdown orders are science — they are guesses as to the correct response. I live in Phoenix where it was sunny and 80F this weekend. We are on lockdown in our houses. I could argue that ordering everyone out into the natural disinfectant of heat and sunlight for 2 hours a day is as effective a response as forcing families into their houses (initial data, though it is sketchy, of limited transfer of the virus in summertime Australia is interesting — only a small portion of cases are from community transfer. By comparison less than a half percent of US cases from travel).
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