20 Years of #BikeMS

So, it was 20 years ago this summer that #BikeMS brought me back into cycling. Ted & Michelle Hopfner hooked me into their FedEx BikeMS team, and the rest, as they say, is history.

Since then there have been a ton of stories, riding in every imaginable weather, being joined by my Wife and Daughter, and meeting amazing, beautiful, human beings.

But why? Why have I spent many winters (especially as I've gotten older) doing painful things on an indoor cycling trainer? Why have I ridden literally thousands of miles in training and events? Why have I endured sunburn, windburn, saddle sores, cramps, exhaustion, and sometimes absolute frickin' misery?

Because Multiple Sclerosis is a horrible <expletive> disease, that has caused far more suffering to friends and family than I have ever suffered.

Multiple Sclerosis is an autoimmune disorder where the immune system attacks the myelin surrounding nerves in the brain and central nervous system. The effect is a lot like having the insulation in a complex wiring system stripped away in random locations, creating short circuits and open circuits.

Pain, numbness, vision issues, brain fog, emotional effects, paralysis, difficulty with basic body functions like eating and breathing are all possible symptoms that can come and (sometimes) go at almost any time.

This year, the symptoms of MS took Lynne Metro, a dear lady who welcomed Marcy's brother Jeff, and us into her already huge family. She will be missed. May her memory be for a blessing.

#BikeMS is the largest charity cycling event series in the world, and it has made a huge difference. When I started 20 years ago, MS was considered "idiopathic," which is Doctor-speak for "We have no idea what causes this." Today, we know that it is an autoimmune disorder, and have begun to identify the exact biochemical mechanisms and triggers. This knowledge had brought treatments, and will, we hope lead to a cure.

That progress has been funded by events like BikeMS, by people like you who have sponsored cyclists like me. Sponsorships are tax-deductible, and every penny goes to support research and services for those afflicted.

I'll update this blog with event and training updates. For those willing to sponsor me, the simplest way is to donate at this link:

https://events.nationalmssociety.org/index.cfm?fuseaction=donordrive.participant&participantID=580889

If you want to sponsor me in some other way (cash, check, whatever) you can reach out to me at chris(dot)kotting(at)gmail(dot)com.

A cyclist thinking about chain wear.

Probably one of the most quietly contentious discussions in cycling is chain wear.

(Other areas of contention, such as chain lubrication and doping in the pro peloton are more contentious, but not nearly so quiet.)

In an attempt to limit my written meanderings to those areas where I can provide more light than heat, I offer answers to some common questions about chain wear.

Q: What is "chain stretch"?

A: A very inaccurate term for a common issue.  Chains to not "stretch", at least not in the same way that Lycra does.  They do, however, elongate, or change functional dimension, as a result of wear.

In a modern bicycle chain, there are two places that wear occurs:

1. Between the side plates and the pins.
2. Between the rollers and the "shoulder" on the side plate that they ride on.  (In older chains, the roller rides on the pin.  However, in every modern chain I've seen, the roller rides on shoulders formed on the inner side plates.)

As the side plates pivot around the pin, there is wear between the side plate and the pin.  This wear enlarges the hole in the side plate, and reduces the diameter of the pin. This creates an effectively "longer" chain.

As the roller pivots around the pin, it wears on the side plates, allowing slop in the roller's position.

These two factors cause the chain to mesh with the chainrings and rear cog(s) less precisely. Less precision means that the load on the chain is borne by fewer teeth, increasing the wear on the chainrings and rear cog(s).

Chains are relatively inexpensive, chainrings and rear cassettes are relatively expensive, so it is worthwhile to replace the chain early.

Q: How do you know when a chain is worn out?

A: There are a few different tests:

• Use a good ruler. Measure 12" from the center of a pin on the chain. If the center of the pin 12" away is past the 12" mark, you have measurable chain wear. I replace chains at 1/16". If it's a 5,6,7,8 or 9 speed chain (if in doubt, count the rear cogs) you can go a little further.
• Use a chain wear gauge. Use a gauge that is intended for the number of rear cogs. (Past 9 speeds, the chains start getting significantly narrower, as do the cogs, making the wear more of an issue.) There are 2 tests on the gauge;
• the first (usually marked .05) means that you can reasonably replace the chain,
• the second (marked .75 or 1.0, depending on the type of chain it's meant for) means that the chain is done, finis, kaput. You can keep riding it, but be ready to replace the cassette along with the chain, and maybe the chainrings.
• Abbey Bike tools makes a chainwear gauge that uses a different approach, but if you are far enough into bicycle tech to buy a $45 gauge, you probably don't need this article!
  
• Shift into the big ring, grasp the chain where it wraps around the front of the chain, and see if you can pull the chain away from the ring. If you can discern movement, you are looking at replacing the chain. If you see light between the link and the chainring, look at replacing the cassette as well.

Q: What about just running the whole drivetrain until it's absolutely toast, then replace the whole thing? 

A: People do that, and some claim that it's a wash (higher cost, but less frequent). I admit, I'm picky about shifting quality, and a worn chain (and worn cassette) don't shift as well. It's also a PITA when you're on a long tour and you have to source replacement parts. (Ask me about replacing cleats in the middle of South Dakota sometime.)

Q: How do I minimize chain wear?

A: Keep the chain clean. 

• Wipe it down after a long ride, or once a week if you do a lot of short rides. 
• Periodically take the chain off the bike and give it a thorough cleaning in a solvent bath or ultrasonic cleaner. (I'm picky, I do both.  Water based degreaser in an ultrasonic bath, followed by agitation in denatured alcohol, which does double duty in getting the last remnants of gunk out and in getting the water out.)
• Use fenders. Most of the damaging crud that hits a chain from the outside is thrown onto the front chainring by the front wheel. I have fenders on my "daily driver" bike.

    Use a good (i.e. appropriate to the use) lubricant. This is a very contentious issue among cyclists, but here are the broad categories with some guidance for their use:

• Oil-Based. TriFlow, Boeshield T-9, any lubricant that is called a "wet" lubricant.
• Best choice for dealing with wet / rainy conditions. 
• Downside is that the oil will tend to hold dust and dirt, so not so good for dusty conditions. 
• The worst thing you can do here is use too much. Apply a drop to each roller, let it sit for 15 minutes, wipe off any excess with a dry rag.
  
• Dry Lubricants. Generally either described as "dry", the Rock 'n Roll brand is common. 
• These have a solvent with a wax or other dry lubricant in suspension. The solvent evaporates, leaving the lubricant behind. 
• Great and convenient for dry conditions, and often serve to clean the chain in the application process. (Read the directions.)
  
• Often require you to wait overnight between lubing and riding. 
• Can get expensive.
  
•  Wax
• Involves completely stripping any existing lubricant off the chain and immersing the chain in melted wax.
• Definitely holds the least dirt and grit, and often has the lowest friction.
• Downside is that it is a hassle, and has to be redone as often as every 200 miles. For me, that would mean doing it at least every week on-season. (I'm anal about chain wear, but not that anal.)
  

I use Boeshield T-9 on my endurance events bike and my daily driver, both of which see getting caught in the rain. I use a Dry Lubricant (Rock 'n Roll Extreme Dry) on the bike that sits on the indoor trainer. It not only never sees rain, but the dry lubricant keeps the trainer and the floor cleaner.
 

The Modern-Day Molech Machine - Part II

 About a dozen years ago I wrote a Blog post titled "The Modern-Day Molech Machine" about how distorted ideas about beauty were distorting us, and our children, in the name of the almighty dollar.  Well, here's Round 2, this time about Media, and particularly Social Media.

My Bachelor’s degree is in Mass Media and Organizational Communication, and I have been a lifelong student of Media and Society. Most people (myself included) do not use media wisely, especially Social Media. A tool that can (and should) create connection between people instead created division and contentiousness. I’d like to explore some of the mechanisms behind that.

The primary thing that one has to remember is that the product of the Media, whether print, broadcast, streaming, or social is NOT the media itself. Content is not the product. You and I are the product, or, more precisely, our attention.

Media content is a farm, and the crop is eyeball/seconds.

This fact drives all of media, and business decisions in media. Remember “soap operas”? Originally, those (radio, at the time) shows were actually produced by the advertiser, generally a laundry soap, hence the name. They didn’t do so to entertain housewives, but to get their attention, and to present a world where any housewife who was worthwhile used the advertised detergent.

Of course, this was at the time when advertising hadn’t passed much beyond the “billboard” stage, where the advertiser didn’t know much about the audience. Today we have “big data” of which A.G. Nielsen was a big pioneer in the media world.

You know Nielsen if you’ve ever heard about “Nielsen ratings” which is a measure of how popular a program is, and that is a direct measure of how big a “crop” the “farm” has. However, Nielsen’s audience research goes far beyond just counting eyeballs.

Nielsen developed audience analytics, where “how many” is important, but “what kind” is equally important. Nielsen began early on characterizing the audience, so a show would have a rating, and a view of the demographic of the audience. Certain shows were more popular with certain advertisers, because those shows drew an audience that the advertiser wanted. That particular “crop” became more profitable, so that kind of show proliferated.

A sidebar: Many Conservatives have decried “liberal media bias”. I’m sorry, but that’s a thing. Media as a whole has developed a liberal / progressive bias. While many think that this is a vast conspiracy, I see a simpler, and more likely¹, cause. People on the liberal / progressive end of the political philosophical spectrum are more likely to try something new, including trying a new product. Advertisers will pay more for an audience that will, on the whole, be more likely to buy. This creates a natural financial push towards that political philosophy, which creates a hiring bias (after all, you hire people who will make you more money), which leads to newsrooms filled with people who think alike. Those staff writers grow up to become Editors, who hire people who think the way they do, and the newsroom becomes an echo chamber. 

This isn't a conspiracy, it's financial incentives plus human nature. For more on this, I highly recommend the book Republican like Me, written by the former President of NPR.

That also explains Fox News, because some products are favored by politically and fiscally Conservative people. Fox News and other conservative media draw those advertisers.

Nielsen created “audience segmentation”, and it affected every aspect of broadcast programming, even the news. You have probably seen the internet meme about Walter Cronkite, and how he “just read the news”. Well, there was media bias and market segmentation back then, too. “Uncle Walter” appealed to political conservatives, and this was a result of on-air demeanor, how the stories were written, and what stories were reported on, and for how long. Liberal / Progressive households (like the one I grew up in) favored Chet Huntley and David Brinkley, as well as PBS for news. Those in the middle, tended to watch ABC news.

The social divisiveness we see today is a natural progression from audience segmentation, and it’s logical extension into Social Media, where the “audience” is also the “content creator”. Social Media faces the same financial pressures as any other form of media, and responds in the same way, with audience segmentation. Audience segmentation in social media, becomes audience polarization. Again this is a natural outcome of the financial pressures and the business model.

However, with social media, the process of audience segmentation is automatically performed by the algorithm. Remember, making money is driven by getting, and keeping, attention. The algorithm is designed to identify the content people are attracted to, and presenting that content to them, on an ongoing cycle. This self reinforcing process (feedback loop) creates polarization, because what people see is more and more biased towards their preconceived notions of truth and reality.

The natural tendency and outcome of these processes is to divide us. Resisting that outcome takes effort, because tribal identity is so easy and comfortable.

But resist it we must.

Health Care, Medical Insurance, and some related stuff...

(A lot of this post was inspired by, and many ideas in it come from, Kevin Williamson's Wanderland newsletter dated 12/9/2024. It's available at https://thedispatch.com/newsletter/wanderland/no-mandate-but-still-a-mess/. I heartily encourage signing up for the newsletters at The Dispatch, and subscribing if you can, regardless of your political persuasion. They'll make you think, which is never a bad thing.)

OK, there has been a huge uptick in media (social and traditional) about insurance and health care, thanks to events in New York recently. (The murder of the CEO of a health insurance company, in case this blog lasts longer than the memory of the event.) I have some thoughts on the topics.

First, medical insurance is NOT health care. It isn't even "health insurance" because it certainly doesn't do anything if you stay healthy.

Health care is eating properly, getting regular exercise, taking supplements and medication if and when needed, and seeing your doctor regularly for a checkup.

Medical insurance (like all insurance) is a financial instrument to manage risk. You pay an insurance company to absorb the risk of you needing medical intervention of some sort. To the extent they pay for aspects of health care as I've defined it here (gym memberships, checkups, vaccinations, etc.) that is them managing the risk you asked them to take for you. When they deny a claim, that is also them managing their risk (perhaps unfairly and stupidly, but more on that later.) When they ask you a lot of health-related questions, that is them calculating the risk you are asking them to accept.

You have car insurance (at least the law requires you to have a minimum liability coverage of some sort if you operate a car.) Your car insurance doesn't insure that you have a working car at any particular moment, and it doesn't pay for regular maintenance. It doesn't pay for tune-ups, oil changes, alignment, tires, brake pads, and a host of other things that you need to do to have a reliable, safe (healthy) car.  That's on you. They may give you a "safe driving discount" which is another form of risk management.

There are a lot of reasons why the services of a doctor are crazy expensive in America, but one of them is certainly that Americans, as a whole, are terrible about health care. We build communities that can't be walked in, we avoid physical work whenever possible, and we eat terribly. People who try to maintain their health are considered "fringe". That's a cultural issue I could write about at excessive length, but I won't rant here.

Going back to the car analogy, Americans essentially treat our bodies like cheap used cars: We drive them until the wheels fall off, then get another. Except we can't get another, so we end up paying a "mechanic" insane amounts to make the vehicle serviceable again. That's obviously stupid when put that way, but that's what we, as Americans, mostly do.

To the extent we take personal responsibility for health care, we reduce the risk that we're trying to pay someone else to cover, and reduce the cost of insurance. 

OK, back to insurance as a financial instrument for a bit.  Certainly there are problems with how we manage that risk transfer service, so let's talk about that. First, insurance is heavily regulated. That regulation is a problem, not the amount or type of regulation per se, but the fact that it regulated in 52 very different ways. Each state (and territory) regulates insurance a little differently, which is a knock-on effect of other aspects of the Constitution. That network of differing regulation drives up insurance costs in two ways:

• It makes meeting regulatory requirements difficult and expensive, by imposing a lot of duplication of effort.
• It makes the pool of insured people a lot smaller, since every plan is state-specific, and so the risks are state-specific, which means the pool of insured people becomes state-specific. The smaller a pool of insured people, the fewer people that risk is statistically spread across, and the more uncertainty about the risk.

Both of those could be mitigated, without Federal action, by States developing compacts in which they regulate insurers the same way, using the same forms, rules and procedures. (Hot tip, we do something like that currently with the companies that own and operate the electric transmission system, pardon the inherent pun.)

A lot of people advocate for "single payer" or "medicare for all". In fact, only a few other countries (the UK and the countries that were once their territories) do that. The other developed nations that people point to as having better health care and lower costs than the US (a) have populations that generally take care of themselves better, and (b) have a single, very stringent, regulation system for the whole country. Look at the Swiss, for example.  I would point you to Kevin Williamson's discussion in his Wanderland newsletter (link in the first paragraph.)

Now, I had promised that I would talk about unfair and inappropriate denial of coverage, which clearly happens. I would venture that most of us have experienced it, or know someone who has. I have two amazing and related hacks for y'all.

THE FIRST HACK: One of the things that is pretty consistent across the US is your right to be given the following information on request:

1. Name, License Number and Board Specialty of the physician who make the decision that treatment was not necessary.
2. Copies of all materials used to make that determination.
3. Proof that the physician is current with their registration in your state and up to date on all their continuing education.
4. The aggregate rate at which that physician approves or denies similar treatments for peer review.

Most insurance companies will just approve the claim, rather than admit that the decision was made by a physician who is not licensed in your state, not current on their training, or practicing medicine outside of their specialty (or is just someone with a GED and a checklist, or an AI system, or...)

THE SECOND HACK: ProPublica has a website that will generate an appropriate letter to make that request, based on information that you enter. Bookmark this: 

https://projects.propublica.org/claimfile/

Figures don't lie, but...

 I want to compare two charts, one is famous, the other is not, yet...

First, let's look at the chart that Donald Trump was pointing to when someone took a shot at him. This is a little fuzzy, because it's from a screenshot.

The first thing I want you to notice is that the chart has a big arrow at the bottom pointing to the end of Donald Trump's admnistration, marked "TRUMP LEAVES OFFICE". Note where it is pointing on the time scale, around March of 2020.

Except Trump didn't leave office in March of 2020. (If he did, then who was acting as President?) He left office on January 20, 2021. March of 2020 was 7 months before the election, and almost 10 months before Trump left office.

 That's odd.  You would think that if there was any date that the Trump campaign would get right, it would be the date he left office.

The second thing I want you to notice is the date marked "TRUMP Tariff threat leads to Mexican cooperation."  That's May of 2019.

Let's look at the second chart, the less famous one:

Yeah, this one's also a screenshot, so it's fuzzy too.  I'll update with clearer images when I can source them. This chart does two things that the first one doesn't:

• Corrects the date when Trump left office to January 2021.
• Adds data through September of 2024 (so far.)

Notice the rise in illegal immigration since the low point the original chart called the end of the Trump administration. That's a roughly 85,000 person increase in the monthly rate of illegal immigration from that low point. Even if you attribute some of that increase to the November election, and Biden becoming President-Elect, most of it happened before November, and the rate of increase tapered off in November.

So the decline in Illegal immigration started around May of 2019 and reversed around March of 2020. It's possible that Trump's actions and policies caused that dip, but those policies were still in force during the rise in most of 2020. Could there be another cause at work?

How about a global pandemic? It may be coincidence, but the decline started around the time that lockdowns began, and reversed around the time that vaccines became widely available in the US. Latin America was about a year behind the US in vaccine availability and the rate of vaccination.

Could the decline in illegal immigration have been a pandemic response, and the rise in illegal immigration late in Trump's return in fact a return to what the rate of illegal immigration have been without the pandemic? Could the Trump campaign be knowingly taking credit for something the Trump administration had nothing to do with? Stranger things have been done and said in politics.

Now let's look at the decline late in the Biden administration. What could have caused that?  Well, in 2023, in response to the surge in immigration, the Biden administration got Mexico to station troops to stem immigration into the US. It worked.

By the way, that cooperation was established in a 2022 "Summit of the Americas" in Los Angeles. A Declaration from that Summit (released June 10, 2022) did the following:

• Got Costa Rica, Colombia and Ecuador to offer legal immigrant status for Venezuelans crossing their borders. The situation in Venezuela drove a lot of immigration to the US, that is now being stopped in other countries.
• Got Mexico, Belize and Costa Rica to place tighter restrictions on Venezuelans flying into their countries.
  

 It was the Biden administration that got Mexico to pay for a wall, by stationing Mexican troops to enforce the border from their side. It was the Biden administration that got other countries to create a series of smaller "walls" to do what the Trump administration promised, but failed, to do.

Yes, a lot of people get into this country bypassing the legal process.  Why is that? Well, the legal system is swamped, so thousands of immigrants a day are crossing the border, asking for asylum, and getting briefly detained and, if there isn't an obvious issue, released, bypassing the Asylum process.

Why is the legal system swamped? Well Congress failed to act. Constitutionally, it is Congress' job to write laws and fund the enforcement process. The Congress had a bipartisan fix, or the start of one, before them last year.  It didn't pass, because the Republican support for it pulled out at the last minute.

That kept illegal immigration a live topic for this year's election. There was a way to start resolving the issue, and the Republican party chose politics over signing off on legislation that they co-wrote. They did the political thing, rather than the right thing.

You can build a wall, or you can work on better solutions. Take your pick.

In simple fact, the immigration situation is far more complex than a simple graph is ever going to show. 

Especially when that graph has carefully selected wrong data.

Figures don't lie, but they sure can be manipulated to sell a false narrative.

The 2020 Election: Was there a "Steal" to Stop?

OK, I generally try to not stray too deep into the miasma that is politics these days, but there is something that is worrying me. I’m seeing people, bright, intelligent people whom I respect, still buying into the “voter fraud” argument. If you’re one of those people: I hate to say this, but I truly do love you, and love sometimes has to speak the truth:

Y’all have been gaslighted. I don’t say that lightly, and I’m trying not to be mean about it, but that’s the only thing I can find to explain the phenomena.

I have two different explanations for why the 2020 Election couldn’t have been stolen: One Logistic and one Statistical. We’ll take the Logistic first.

The Logistics problem begins with this simple fact: Every voting precinct has a different slate of candidates, offices, and issues. Not every state, or every county, every voting precinct. For example, in my precinct, I vote for a different school board than the one for the city I live in, because I’m part of that school district. The school district doesn’t follow city boundaries.

Each voting precinct has a different ballot, which means that the encoded data will be different. Each precinct’s mail in ballots will be different as well. Wikipedia reports that in 2020, there were 176,933 precincts in the United States. That doesn’t have to be an exact number, though. Managing to fraudulently manipulate the results from anything over a few thousand different voting precincts rapidly becomes a logistical nightmare. Anything over 100,000 precincts in a 24 hour period? Logistically impossible. What about with a computer? Well, you would have to find a way to program a computer to invisibly manipulate different ballots, captured by different means, all within 24 hours.

What about AI? Well; (1) AI was not that advanced in 2020, and (2) AI requires a huge sample of text and images (multiple millions of samples) to be able to even recognize a ballot reliably, let alone decipher hundreds of thousands of different forms and formats, and successfully manipulate them. I'm pretty sure that someone would have spotted all those samples being accumulated.

Now, on to Statistics: I’m deep down a “numbers and logic” guy, so let’s take a logical look at some numbers. I’m using two sources of information: A 20 year MIT database of observed voter fraud as of 2020, and a table of 2020 state-by-state vote counts from Dave Lep’s Atlas of US Presidential Elections.

First, the MIT database shows, over the past 20 years, just over 1,200 cases of voter fraud, 204 of which involved mail-in ballots. That is a rate of voter fraud of 0.00006%.

Now let’s look at Dave Let’s Atlas. I didn’t pick this site because of any particular political bent, it just happened to be the first one I found that had a handy table. First, let’s look at the popular vote. The margin of popular vote victory for the Biden/Harris ticket is 3,078,287 votes. In order to make it a “dead heat”, half of those (1,539,543) would have to be fraudulent. There were 158,590,015 total votes cast across all 50 states, so a “dead heat” popular-vote election would require that there was a fraud rate of just under 1%

That is 16,000 times the rate of voter fraud observed at MIT, just to get to a dead heat. A victory for Trump/Pence by the same margin would require a fraud rate of 1.94% of all votes cast, about 32,000 times what MIT observes.

Ah, but a few key states for the Electoral College were close! What about those? Basically, we’re talking here about Arizona (11), North Carolina (15) and Georgia (16). For the sake of discussion, let’s assume that all 3 actually should have gone to Trump/Pence. The next closest state, by a “% of fraudulent votes to make it a dead heat” measure is Wisconsin, with 0.31%. That is still 5,000 times the MIT observed rate. Let’s assume that Wisconsin should have gone to Trump/Pence by the same margin (10,000 times MIT’s rate of vote fraud). Now you’re at a dead heat in the Electoral College at 269 each.

That’s what you have to assume to imagine that voter fraud made it a dead heat. 10,000 times the observed rate of voter fraud.

Not a clear victory for Trump/Pence, just a dead heat in the Electoral College. You have to assume that every one of the 4 closest states to a dead heat should have gone to Trump/Pence.

For a clear victory (by the same vote margin) you would have to throw in Pennsylvania (the next closest state after Wisconsin) with an assumed a rate of fraud in of 12,000 times the MIT observation.

To be clear: To buy the argument that voter fraud manipulated a loss for Trump/Pence, you have to assume that either; (1) a campaign to affect the vote through fraud at 12,000 times the observed rate of fraud has so far gone totally undetected by the people responsible in both parties, or (2) MIT’s data only reflects unsuccessful fraud, and the successful fraud isn’t caught. (That’s called “ascertainment bias”, where you don’t know reality because your sample size misses too much.)

Dealing with the first point, some may argue that it is all a product of a massive conspiracy to cover up the fraud. In response, I would point to Chuck Colson’s comment about his belief in the Resurrection:

“I know the resurrection is a fact, and Watergate proved it to me. How? Because 12 men testified they had seen Jesus raised from the dead, then they proclaimed that truth for 40 years, never once denying it. Every one was beaten, tortured, stoned and put in prison. They would not have endured that if it weren't true. Watergate embroiled 12 of the most powerful men in the world-and they couldn't keep a lie for three weeks. You're telling me 12 apostles could keep a lie for 40 years? Absolutely impossible.”

Regardless of how you may feel about the Resurrection, Mr. Colson’s point about conspiracy is valid: The Watergate conspirators couldn’t collectively keep a secret for 3 weeks. The more collaborators there are in a conspiracy, the more possibility that someone would break, especially when their careers and even their lives are being threatened. A cover-up on this scale would have to involve thousands of people, at many levels, any of whom would be able to bring forward evidence to prove the conspiracy, any time in the past almost 4 years. Nobody has come forward, nobody has confessed, despite the threats, and despite the opportunity to be a hero by saving some court cases.

Didn’t happen. That dog don’t hunt.

Now, let’s think through that second possibility for a moment, because “Survivorship bias” and Ascertainment bias both happen. MIT’s data when I referenced it covered 20 years of observations (1999 – 2019)*.

The assumption that the data is that massively flawed, and that the real rate of fraud is underreported by a factor of 12,000, calls into question every election in the past 20 years, regardless of who won.

So, if you want to believe that Trump’s loss in 2020 was a result of undiscovered voter fraud, you would have to accept that his victory in 2016 was a fraud as well.

Either; (a) there has been massive fraud for the past 20 years, that the MIT survey doesn’t pick up on, or (b) the 2020 election had a rate of voter fraud that exceeded the historical precedent by a factor of 12,000, and that with all the tens of thousands of people responsible (see my logistical argument) either missed it, or lied, and nobody has ‘fessed up.

That’s why I’m saying that, if you, bright person whom I respect, buy the “voter fraud” argument about the 2020 Election, you have been successfully gaslighted.

The numbers just don’t work. The logic is faulty. I’m sorry to say it, but your perception of reality has been distorted.

* I originally wrote this in late 2020, and have only minimally updated it since.

An argument for Intelligent Design from an surprising source

Neil Degrasse Tyson just posted an incredible argument for Intelligent Design on TikTok. 

He didn’t think it was an argument for Intelligent Design, but it is.

Here’s how it goes, he starts talking about shuffling playing cards, and gets to the fact that there are 52! (52 factorial) different possible sequences of cards after a proper shuffle. For those who don’t remember that part of math, 52! is:

52 x 51 x 50 x 49 x 48 x 47 x 46 x 45 x 44 x … x10 x 9 x 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1

which works out to 8 x 10⁶⁷. 8 with 67 zeroes after it. A really big number.

To put that into context, he explains that if you took a trillion people, in each of a trillion civilizations, in a trillion different universes, handed each a deck of playing cards, and gave each person instructions to shuffle their deck a trillion times a second, and had that go on for a trillion years, you would only have a 40% chance of one of those shufflings giving the same order as a deck you just shuffled.

So how is that an argument for Intelligent Design?

How old does Science say the Universe is? The longest time that I have found in scientific research is 26.7 Billion years.

Let’s assume for the sake of discussion that the development of intelligent life only requires 52 steps, in the correct order. Each step is represented in our thought experiment by a playing card. Only one sequence out of all the possible sequences results in life as we know it. Neil argues that hitting the correct sequence would take;

• a trillion universes,
• times a trillion civilizations,
• times a trillion people,
• times a trillion shuffles per second,
• times 31,536,000 seconds per year,
• for a trillion years,
• with only a 40% chance of success at hitting the correct sequence.
  

Here we are having this (presumably) intelligent conversation in (at most) 2.67% of the time, in just one universe!

The counter argument is that this isn’t the only cycle the universe (or multiverse) has taken.

If all that is, is on infinite repeat, anything could happen.

Even a famous atheist accidentally posting an argument for Intelligent Design on TikTok.