Asking a common sense question is a thought crime now. Asking a question about Covid-19 or the government’s response is to deny the authority of experts. This is apparent on social media!
Twitter censors anything construed as a “Denial of expert guidance“. Thus, questions inspired by cited peer reviewed literature are not permitted on Twitter. To ask a question is to deny expert guidance – you are thereby guilty of thought crimes!
I stopped using Twitter a while ago so no big loss.
Satirist JP Sears has a funny commentary on this – thou shalt not question anything – hah hah.
Asking questions that might cast doubt on conventional wisdom is a thought crime. “Experts” including the CDC and WHO, have, many times over the past few months, made inconsistent, contradictory and incoherent statements. How does their erroneous content fit with in Twitter guidelines?
The issue goes beyond Twitter; anyone who notes an oddity, an observation or has a question about an unclear expert or government pronouncement is committing a thought crime.
Per Twitter (and popular view today), it is a thought crime to ask questions. In this environment, we must adhere to the “officials” and the “experts”. To ask questions is to doubt their authority.
A month ago I received push back for sharing hopeful “good news” items about vaccines in development, declining trends in new cases in my state, and so forth. I was perplexed why good news was considered heretical. How odd!
Amid a world filled by news media fear mongering, often weeks out of date or focused solely on the most fearful interpretations, many people are overcome with anxiety.
They appear to seek out ever more scary news as a way to validate their anxiety. That’s the only explanation I could think of to explain resistance to good news. But I am not an expert. Pointing out positive news or potentially positive news is “bad” – it is a thought crime against conventional wisdom and devalues the “experts”.
Update: Yes, that is the case: “Confirmation bias is the idea that we will actively seek out, remember, and favor information that confirms something we already believe.” People are intentionally seeking the scariest possible news stories about Covid-19. The news media is more than happy to provide daily scary news interpretations. I’ve read several today that were so wrong and misleading as to be fake news – but at least they were scary! Fear is one of the most powerful motivators used in propaganda messaging. This further persuades people to adopt the common conventional wisdom – and to denigrate those who question any aspect of it.
Anyone may have a viewpoint on say, computer hardware or software. But some fields, like health care – are off limits to the laity. Only those who wear the right robes may make comments or ask uncomfortable questions.
Asking questions, noting oddities, peculiarities, inconsistencies, posting hopeful information – saying anything having to do with Covid-19 other than quoting official government experts – is a thought crime, a commission against the zeitgeist.
If you are confused, it is your fault – not that the experts have provided poor explanations and communications to the public.
Consequently, I have marked all of my nearly one hundred or so Covid-19 related posts as private so as not to commit more thought crimes!
The only posts I am leaving are those that primarily intersect with technology or business topics:
links to “expert” views on Neil Ferguson’s Covid Sim model code (I wrote my own extensive review but marked it private because how dare I criticize his code)
Summary of Covid-tracking apps (intersects with tech I’ve worked with)
Business topics like why is the stock marketing going up? How will we pay for economic stimulus packages? How will this effect the travel industry?
Summarizes possible impacts to the U.S. and economic issues. CDC is planning for possible school and business closure mandates, summer Olympics could be canceled, and hoping the disease, like many, subsides during warm summer conditions.
The total number of COVID-19 cases climbed above 80,200 as of Tuesday with deaths climbing to at least 2,704.
I have followed several “FIRE” blogs from people who save aggressively (generally a good thing) and “retire” at 30 or 40. I admire them for practicing frugality (something we have practiced too). I am now retired, albeit, at the age when many people have retired (old dude, ok?)
I too noticed that most FIRE practitioners did not retire, exactly, but often took advantage of their near financial independence to work independently, on their own schedule – instead of the usual corporate rat race. That’s not bad thing either – in fact, it sounds like a great opportunity for many!
But there are some hidden “gotcha” expenses that may be lurking for FIRE adherents in the near future …
On December 18, 2019, my Internet web hosting provider announced they are shutting down in February 2020. I am now in process of relocating my 5 web sites to a new web host (and once this is done, a 6th site located elsewhere will also be relocated).
This post you are reading right now is on the new web host, however, the final appearance of this page and some other key items still need to be updated. These final fixes will occur over the next week or so. For example, this web site is presently using a self signed SSL certificate and access (https) results in a security alert that the SSL connection cannot be verified, or in some browsers, images are missing or the page formats incorrectly. This will be fixed, in due course.
A weather event is not climate. The coldest ever October temperature in the lower 48 states was recorded in Peter Sinks, Utah on October 28th, at -45 degrees F (-43 degrees C). Peter Sinks is located in the mountains north of Logan, Utah
Professor Cliff Mass, professor of atmospheric sciences says:
Now several folks are talking about this event being associated with global warming. CA Governor Newson said this in a press conference. This is simply not true.
But what message is the public hearing? That this event is due to “global heating” even though science does not say that about this event.
The winds were due to a very cold air mass descending south from Canada, which causes high pressure relative to areas further south. This cold air led to 3 low temperature records in my town, one at -3 degrees F. Spokane, WA experienced its coldest October on record.
This cold air mass, in turn causes strong winds to flow from the high in the north and north east towards California. This is a common event in the fall. If you read the California fires story, above, you will learn of many associated causes of the fires (including more people, building more homes in wild land areas, and PG&E’s historical lack of electrical line maintenance, and uninsulated power lines in close proximity to trees.)
Warmer air, like in California, is often associated with nearby very cold air masses. That’s just how weather systems work.
Model-land is a hypothetical world in which our simulations are perfect, an attractive fairy-tale state of mind in which optimising a simulation invariably reflects desirable pathways in the real world. Decision-support in model-land implies taking the output of model simulations at face value (perhaps using some form of statistical post-processing to account for blatant inconsistencies), and then interpreting frequencies in model-land to represent probabilities in the real-world.
The following is something I see nearly every day in the media – where the model output is presented as the real world (even when the real world is different):
As a trivial example, when writing about forecasts of household consumption, energy prices, or global average surface temperature, many authors will use the same name and the same phrasing to refer to effects seen in the simulation as those used for the real world. It may not be the case that these authors are actually confused about which is which, the point is that readers of conclusions would benefit from a clear distinction being made, especially where such results are presented as if they have relevance to real-world phenomena and decision-making.
For what we term “climate-like” models, the realms of sophisticated statistical processing which variously “identify the best model”, “calibrate the parameters of the model”, “form a probability distribution from the ensemble”, “calculate the size of the discrepancy” etc., are castles in the air built on a single assumption which is known to be incorrect: that the model is perfect.
It is not clear why multi-model ensembles are taken to represent a probability distribution at all; the distributions from each imperfect model in the ensemble will differ from the desired perfect model probability distribution (if such a thing exists); it is not clear how combining them might lead to a relevant, much less precise, distribution for the real-world target of interest.
WordPress just updated their software to version 5.0, providing a new user interface for editing.
However, on some of my sites, I can no longer publish anything nor update existing posts. Others are also reporting this problem. The symptom is you received a “Publishing failed” error when you attempt to publish a new post, or “Updating failed” when you try to edit and update an old post.
FIX FOR THE WORDPRESS UPDATING FAILED ERROR –> Install the Classic Editor plug in and use that to edit your posts. I can edit and post new content using the Classic Editor – just not using the new Blocks editor.
On at least one of my sites, the “Categories” feature has simply disappeared.
There appear to be numerous problems with the WordPress 5.0 update and I recommend that all WordPress users DO NOT UPDATE TO VERSION 5.0 AT THIS TIME.
My mistake for having updated 4 of my 5 blogs before I discovered that the WP 5.0 update is badly broken.
Long ago I used the literal cardboard Google Cardboard to hold my phone as a VR viewer. The Cardboard eventually fell apart (as expected).
Later, I replaced that with a Samsung Gear VR headset as at the time, it was the only headset I could find with a diopter adjustment. All other headsets were unusable by anyone who must wear reading glasses. The Gear VR kinda worked as a Cardboard viewer as I did not have a Samsung phone and the Gear VR only works, officially, with Samsung phones. But with emphasis on “kinda” worked – this enabled testing the VR waters, so to speak.
A week ago, I finally got a Daydream compatible headset to use with my Pixel 2 – and no surprise – the Daydream Controller refuses to pair with my phone.
How on earth can VR achieve any market share success when it is a pain to set up? Is there VR gear that is usable?
Separately, I used the Fulldive VR viewer as it does not require a controller to make selections. Unfortunately, after a bit of VR 360 Youtube viewing, I experienced nausea. 30 minutes after discontinuing using the VR viewer I am still feeling ill. Oddly enough, I can watch 3D videos all day and have no such troubles.
I think the problem is a combination of VR motion but also low resolution and focusing issues that cause eye strain.
Trying to get the Controller to work, I reset the Controller by pressing and holding the Home and App buttons simultaneously. I can then pair the controller with my phone using the Android Bluetooth menu and the controller shows in the Bluetooth devices list.
However, when I run the Daydream app, it says no controller is paired and attempts to pair it with the controller always fail. Well, except two times it began the pairing process but failed.
I have paired a Bluetooth mouse with the phone and I can use that to select user interface items, but the mouse lacks the accelerometers in the controller for use in gaming and other actions.
The Daydream Youtube viewing experience is not great – the user interface seems clumsy and more often than not I end up exiting the Daydream app and have to remove the phone from the headset and get it reset back in to Daydream. The resolution provided by a phone is also inadequate – I think the visible pixels contribute to the feeling of nausea.
Shooting VR stills or video is fairly straight forward. But the viewing experience is not very good – yet.
Consequently, I’m not inclined to buy a dedicated VR headset ($400 and up). VR has been around a long time but with difficult to use viewers and poor user interfaces, this tech needs further development.
Update – the vendor of my Daydream compatible headset is sending me a replacement Daydream Controller. Hope it works!
NPR makes an assertion that 1984 is when personal computers in the home emerged and that parents only bought personal computers for their sons. The first assertion is false and the second assertion is made without any supporting evidence. The latter assertion provides no meaningful explanation for women in computer science prior to the mid-1980s nor that most young women today have a personal computer but still are, apparently, not going into computer science.
The above NPR report is one that makes you think you have just learned something but in fact, fails to explain anything.
Here is a chart I made showing the percent of homes with a PC, from 1984 to 2012. Data provided by the US Census up through 2012. Data was not collected every year so some years have no data.
You can see that home PCs went from 8% in 1984 to 15% in 1989. Both are small values. This does not explain why fewer women students pursued computer science after the mid-1980s, contrary to the NPR report’s claim.
In roughly the last 20 years, access to personal computers, by gender and age, is widespread but there was no upsurge in computer science enrollment by women which would be expected if the NPR thesis were true.
Another issue is to understand what is being measured. Most discussions of “women in STEM” are referring to “women in computer science” or sometimes “women in computer science and engineering” – and are mistakenly presented as a proxy for women in science. Many STEM metrics specifically omit degrees in (especially) the health sciences as “STEM” when they are also science-based degrees.
Women represent about 90% of all nursing (and elementary school teaching) jobs – fields that employ far more people than are employed in the computer sciences. In terms of overall degrees in science, technology, engineering and math, women graduates were just barely above 50% (last I checked NSF data – It depends on how you define “STEM”). Women are way above 50% in terms of overall 4 year college degree graduates and have been since the early 1980s. 49.8% of medical school students are women and are 78% of veterinary school students.
This shows the same information as trend line over time:
But there is no concern – and instead, silence – about diversity and balance in fields outside of computer science. There is a problem in computer science but unsound assertions, as described in the NPR report, do not lead to useful solutions.
Business, Tech, Energy, Transporation, Thinking
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