A Clash Of Empires, Russia & USA Part I — Guest Post by Ianto Watt

Nations are built upon citizens. Empires are built upon slaves. Furthermore, nations must grow internally to survive, whereas Empires must grow externally, else they die. Now if these propositions are true, then perhaps we have a means of assessing the relative state of the world, especially as it relates to this past year. More to the point: has America made any progress towards re-claiming her nationality? And conversely, has Russia made any further progress in her intention to replace The Empire? Because, I contend, those are the two overriding issues of the day. Everything else is small potatoes.

Really, the two are one. Why? Because if America were to actually walk away from her Empire in order to regain her national character, then that would open wide the door to Russian imperial expansion. It’s a zero sum game in politics. No vacuums allowed. Here’s the choice, America. Regain your past, or lose your future. Choose your purpose and you will define your choice. You can be one of many legitimate nations upon the earth. Or be master of the universe. Which will it be? It’s the same choice all nations face. Rule your own home, or else rule your neighbor’s home. You can’t do both. Maybe you can for a while. But not forever. Just look at the list of empires and their duration. The clock has pretty well run out.

Historically speaking, it seems pretty clear. If you chose to rule your neighbor, you will lose your own home. If you choose to rule your own home, you at least might survive. Is the grass really that much greener on the other side of that fence? It’s a funny thing. Slaves tend to outlast their masters. Just look at the Russians if you want proof. And funnier still is the fact that she now wants to risk her survival by becoming the ruler of her former masters. All of them. Khazars, Swedes, Pechenegs, Mongols, Poles, Frogs, Germans, and everyone else. Especially of course, the Anglish. Her tormentors for 300 years. The masters of the Great Game. The game we have inherited.

Conversely, if America does not attempt to rule her own national home (to the exclusion of others), then she must be prepared to defend her empire. She must prepare to confront her neighbors. All of them. And here’s the problem; her neighbors may have the same idea in mind. That’s the problem with the Imperial idea. There’s no copyright. It’s an infection, and anyone can catch it. So, it seems to me, the choice comes down to this, will we choose humility or hubris? Are we homebodies, or busybodies? Either choice is painful. But one will come at a much higher cost.

So here’s where we’re at. The fork in the road. Which way will we go? You might recall that in July of 2016, I had remarked that Donald would win and that he would deliver the keys of The Empire to Vlad. The question then is this: do we still want to be an Empire, where we have no recognizable and peaceable neighbors, or do we want to be a nation again, with our own individual personality, living amongst other legitimate sibling nations? Even if it means someone else will be the new master?

We have seen at least half of this prediction come true. Donald has won. Has the second half been accomplished? Has he delivered the keys? Let’s have a look. But to do this, we have to understand Donald, if that is possible. I’m not always sure he understands himself, but that isn’t important at the moment. The key is to understand the conflicting positions he has taken. When he says he wants to make America great (again), we have to ask, ‘Which America’? America the nation, or America the Empire? We can’t be both, because the definition of nation and empire are antithetical to each other. We have to choose who we want to be before we can affect the necessary change. You can’t be Romulus and Remus at the same time, Komrade.

You may ask why these two choices must be exclusive. And I will refer you to my opening sentences. I contend that nations grow internally, whereas empires grow by external expansion. If a nation is experiencing positive population growth (without immigration), it is relatively healthy. If it is not, it is dying, as Japan is. And most European nations are doing the same. And admittedly, a nation truly can admit immigrants without harming itself, but only if the immigrants are restricted to being a numerical minority and if they are congruent with the host country’s culture. That is to say, in harmony with the underlying foundation of the host country’s belief system. And no, I’m not talking about political systems here. I am referring to cultural beliefs. And as we all (should) know, a culture is the outgrowth of a cult. That is to say, a religious belief. A case in point was Europe during the existence of Christendom, or approximately 800 to 1500 AD.

In this epoch, an immigrant from France was able to peaceably live in Germany, Britain, Ireland, Italy, or nearly anywhere on the continent, assuming he was Catholic. His own national culture was subordinated to his spiritual culture, even in his home country. As long as that was the case, he could generally get along with his new neighbors in his new country. He could even intermarry without worry, as there would be a presumption of commonality in the most important questions of life. Because, you know, a man has only two important decisions to make in life. The first is, who will he marry, spiritually? And the second is, who will he marry temporally? Screw up one, and you’re in trouble. Screw up both, and you’re toast. But if you make the right choice, you can leave all the rest to her. Her, as in The Church. Her, as in your wife. Be faithful to the first, and the second will be faithful to you.

‘Do these drapes look good?’ Sure, dear, whatever you like. ‘Do you like the color of this paint?’ Of course, honey, I think it looks swell. “What would you like for dinner?’ Whatever you cook, baby. I love your cooking.

Yes, all the man has to do is make the basic choices. But then he has to stick with them. That’s the hard part. But if he does these two things correctly, everything else will take care of itself. So, let’s look at the first decision; that is, who we will marry spiritually, and see where we are, as a nation. Let’s start at the beginning and ask, has America ever had a homogeneous spirituality? The answer is no. Unless, of course, you accept the hodgepodge of Protestant belief systems as a unified whole. And yes, in a sense it was unified, in its beginnings. Unified against Holy Rome. But once the runner left the bag, who knew where he’d run? The truth is, America was born in reaction to the then-current iteration of Imperial Rome, which of course was Angland. The ‘British Empire’, where the actual British were enslaved. And the Anglo’s were on top. That’s Imperial living for you.

Over in the New World, things just repeated themselves as the Anglish Civil War played out. And the original fracture made permanent by Henry simply continued, as ‘the church’ splintered a thousand times. Today, there are over 30,000 separate denominations, many of which have beliefs that are directly contradicted by many other sects. Only Julian Felsenburgh and his Masonic brethren can make heads or tails out of all of that. And they have. How? They simply ignore everything beyond the initial question; do you believe in a Higher Power? Yes? Then we’re brothers! Allah Akbar! Welcome home. To America, where Felsenburgh hailed from. To America, the newest iteration of Imperial Rome. Where everyone is welcome, regardless of who that Higher Power is that you believe in. As long as you’ll burn a little incense for Julius (Felsenburgh) Caesar, everything is fine. Until the shooting starts, of course.

If there is no commonality of spiritual beliefs, between spouses or citizens, there will always be problems. Problems that may even threaten the life of the nation, if the level of immigration is high enough and sustained for a long period of time. In fact, if there is no commonality of belief, even your own children may be strangers to you. Just as your neighbors may be. Good luck. But let’s assume the home front is stable, and let’s look next door. Who is that guy? Do I recognize him? Is he like me? No, not racially. But that’s not the real problem. The real question is, do I see him each Sunday? If I don’t, there’s a hint of what’s to come. Because, if I don’t see him on Sunday, we must not be brothers. Something’s wrong here. Trouble is coming. And actually, it’s already here.

It doesn’t matter what my neighbor looks like, as long as I see him in the clarity of Sunday morning. If I do, we look exactly alike. As members of the same race. The human race. If I don’t see him on Sunday, I see him as an alien. And sooner or later, that means war. Sooner has passed. Later has come.

That’s the problem that confronts Donald. Does he want to befriend his neighbors, or does he want to dominate them? It’s the same question every Caesar is asked. And his answer is almost always the same: domination. Not that Caesar hates them. No, that’s not necessary. The real problem is this, how do you let go of the tiger and not get eaten? Who can square that circle? Who is wise enough to do it? Who is strong enough to fight the tiger, and not just ride it? I don’t think it is Donald. I don’t think it is Vlad. Or anybody, actually. Except Felsenburgh. And he’ll need a strong dose of Masonic magic to do it. But don’t worry, that’s his strong point. But he’s not here yet.

In the meantime, between now and when Felsenburgh arrives, what is the state of the world? Are we going up or are we going down? We, as in America, that is. The Empire. Because that is what we truly are. And no matter what the stated desire is on the part of any occupant at 1600 Pennsylvania Avenue, there is only the reality that we are still astride the tiger. No amount of talk (alone) will change that. Only decisive action (or even inaction) can accomplish such a change. So let’s look at the scorecard of the past year and see if we have begun to dismount the tiger-skinned throne. And who might be trying to replace us. You know who I mean. So, let’s have a look. Let’s see if the Empire is getting a new boss.

Well, has Vlad left Crimea? Nope. Has Vlad withdrawn his ‘little green men’ from Ukraine? Nyet. Has Vlad left Syria? Nah. And according to Mary Anastasia O’Grady of the Wall Street Journal, has Vlad (and his puppet Maduro) stashed over 5,000 MANPADS in Venezuela? Yep. Has Cuba been freed? Hah! And let’s look at that same paper for another story about our military prowess (as seen through Russian eyes). Evidently, the Empire will still be hitching rides on Russian rockets through 2025, and perhaps 2028. Why? Well, I guess because we can’t get the job done anymore. John Kennedy sent us from scratch to the moon in less than a decade, but now we can’t even launch our own stuff to the Space Lab, let alone beyond earth orbit. We’re reduced to buying vintage 1989-design kerosene-powered rocket engines from the Russians. How humiliating.

Here’s another recent story about our military ‘readiness’ as it relates to European preparedness against a possible Russian incursion. Who wrote this story? The commander of the 173rd Airborne Brigade. Read it. It’s ugly. His report tells the story of how his men are totally under-equipped, under-manned, but more importantly, under-trained in the ways of Russian warfare. The kind they practice in Ukraine. The equipment shortages can’t be fixed in the short term because the equipment they need isn’t available. Some of it is simple stuff (camouflage nets and HF Radios). Other equipment has yet to be designed, let alone produced. No wonder our European ‘allies’ feel a little less friendly towards us, and are acting a little (a lot) more friendly towards Moscow. Europeans are cowards, but they’re not idiots. We are the opposite.

Wait, there’s more. Let’s not forget North Korea. Have things been getting better there? I know, everybody says that nobody can control that twerp, but let me ask you this, do you really think that criminal regime could make those stunning technological advancements in such a short period of time? Not just the achievement of exploding a test nuke. That’s pretty easy. No, I’m talking about the dozen (or more) versions of launch vehicles, several of an intercontinental nature, complete with mobile launchers, miniaturized and possibly MIRV’ed warheads, all on its own? In that amount of time? And now they claim to have achieved an H-Bomb capability? Really? So let’s back up, and you explain to me why we have to buy launch vehicles for the next 10 years from the Russians. Go ahead, I’m waiting.

Remember, as you rely on those rosy CIA/DIA/OSS assessments, those guys have been late and/or wrong on every call since Saddam’s WMD’s. And the GDP of the Soviet Union before that. Hell, even Pearl Harbor. So then, seriously, do you think Vlad (and his Chinese compatriots) have had no hand whatsoever in this amazing technological Korean sprint? Well, sure, the Israeli’s were probably in the mix as well, considering their past duplicity with the Red Chinese and the Pakistanis and their Islamic Bomb. But that’s simply business, Komrade. No ideology there.

What do you think of all these provocative missile tests Kim has launched? Do you think he’s doing all of this on his own? Really? Well, here’s what I think. I think Vlad is telling Kim to do these things. Why? So that Vlad and his men can observe our reactions, or lack thereof. Either one will tell them a lot. If we attempt to shoot down the test missile, Vlad’s boys get to observe (at a technical level) our technological response. Nothing like getting to watch your opponents practice session, right? And if we don’t try and shoot down the missile, that speaks volumes too. About our abilities and more importantly, our willingness to use them. Both Vlad and our ‘allies’ are watching. Either way, Vlad gets free data. Very useful data.

What about Europe? How is Vlad faring there? Well, did Gerhard Schröder, the former Chancellor of Germany, just join the Board of Directors of Rosneft, the Russian natural gas and oil giant? And has Viktor Orban of Hungary turned on his former patron, George Soros (a notorious foe of Russian resistance to the N.W.O.)?

Forget about Ukraine for just a moment as you contemplate Vlad as the Tsar of All Russias. How many Russias are there? Three, of course. Great Russia, where Moscow rules, directly. Little Russia, of course, where Kiev thinks it is in control. And don’t forget White Russia. Byelorussia. Belarus, in today’s lingo. Right next to Poland. And Ukraine. And the Baltic idiots. Belarus, where the NATO Gang thought they were in control, until Vlad taught them otherwise. And where the Byelorussians are participating in the latest Russian military exercises, ‘Zapad‘, designed to rattle the cages of the Baltic midgets who were stupid enough to join the NATO mutual suicide pact. Zapad? Oh, that’s Russian, of course. It means ‘West‘. Gosh, what could that mean?

Death To Those Who Call For Death For Climate Change Denial!

Stream: Death To Those Who Call For Death For Climate Change Denial!

Sharp readers will notice differences between the version here and at the Stream. The intro here is mine.

Death to those who call for the death of those who question the failed theory of devastating man-made global warming!

Punish those who call for punishment of those who support climate realism!

Jail the people who call for incarceration of scientists who demonstrate the uncertainty in global temperature forecasts!

Penalize the folks who demand non-conforming scientists be penalized for giving their professional opinion!

Hey—if our betters are allowed to call for torches and pitchforks against their enemies, then by golly, so am I. Fair’s fair.

Hang ’em high

First to the scaffold should be the angry prune and one-time funnyman Eric Idle, who tweeted “I think that denying climate change is a crime against humanity. And they should be held accountable in a World Court.” When summarily found guilty, the perpetrators he said should be “Put down gently”. As should anybody who tells such lousy jokes.

Mounting their last steps with Idle will be the editors of The Nation, who allowed to be published the article “Climate Denialism Is Literally Killing Us: The victims of Hurricane Harvey have a murderer—and it’s not the storm.?” The author claims refusing to act to his satisfaction against “climate change” is equivalent to “premeditated murder” and should be punished as such. Murder is a capital crime. As should be the rape of logic committed by the author.

¡Fuego!

We’re near to over-straining our nooses, which must be saved for the evilest wrongdoers. This is why it is best that Esquire’s Charles P. Pierce meet his Maker by firing squad. Pierce said “Climate denial already is a synonym for mass murder.” And we know the fate of mass murderers. That same end should be meted out to writers at celebrity tittle-tattle magazines who pretend to understand physics.

Prison blues

Even though it may seem a good idea, not all sins against Truth are punishable by death. Incarceration and punitive fines have their place. Thus it’s off to the hoosegow for Brian Merchant, a writer at The Outline responsible for the negligent piece, “Climate Change Denial Should Be A Crime: In the wake of Harvey, it’s time to treat science denial as gross negligence–and hold those who do the denying accountable.

Merchant said hurricane Harvey is “what climate change looks like.” No, it is what a rare hurricane looks like. If anything, “climate change”, which can’t itself cause anything, is causing a decrease in hurricanes and tropical storms, as hurricane scientist Ryan Maue showed us. [EDITORIAL NOTE; USE THIS PIC IF WE CAN!] For Merchant’s gross criminal ignorance of easily verifiable truths, he should be put away for five to eight years, with no time off for good behavior…

It’s war!

The case of the sovereign nation of Canada is the most difficult…

What Neural Nets Really Are: Or, Artificial Intelligence Pioneer Says Start Over

There is ancient wisdom in the phrase never believe your own press that computer scientists have laid aside in their quest to discover “artificial” “intelligence”.

In the Axios article “Artificial intelligence pioneer says we need to start over” Steve LeVine writes:

In 1986, Geoffrey Hinton co-authored a paper that, four decades later, is central to the explosion of artificial intelligence. But Hinton says his breakthrough method should be dispensed with, and a new path to AI found…

Speaking with Axios on the sidelines of an AI conference in Toronto on Wednesday, Hinton, a professor emeritus at the University of Toronto and a Google researcher, said he is now “deeply suspicious” of back-propagation, the workhorse method that underlies most of the advances we are seeing in the AI field today, including the capacity to sort through photos and talk to Siri. “My view is throw it all away and start again,” he said…

In back propagation, labels or “weights” are used to represent a photo or voice within a brain-like neural layer. The weights are then adjusted and readjusted, layer by layer, until the network can perform an intelligent function with the fewest possible errors.

But Hinton suggested that, to get to where neural networks are able to become intelligent on their own, what is known as “unsupervised learning,” “I suspect that means getting rid of back-propagation.”

If you have not read the series on how an abacus cannot be a brain, nor considered “artificial intelligence”, please do so first (Part I, Part II, Unsupervised learning digression).

Back propagation is only a technique, meaning there are others, to create weights in an “artificial neural network”. Not for the first time do I praise, with genuine enthusiasm, the marketers of computer science for creating wonderful names.

Here is the world’s simplest ANN:

y –> w*y –> z

Some value of y is input into the “network”, and it is then “hit” by a weight, to produce the outcome z. So that if y = 7 and the weight is 2, then (brace yourselves!) z = 14.

It does not matter where the weight w came from, whether from back propagation or from the Lord Himself. It is the weight.

Now this is an ANN. The only thing that separates it from the over-hyped versions marketed in “deep learning” and similar-sounding programs is the complexity, by which is meant the number of possible inputs, layers (the “w*y” is a “layer”), and outputs. Some ANNs can be a tangled mess, with lines connecting layers here and there and everywhere, with weights aplenty. But none differs in any essential sense from our simple network.

In short, an ANN is just like our wooden abacus. It is not alive. It is completely dumb. It is a machine which takes inputs, applies definite operations to them, and produces an output. Your sewing machine and typewriter do the same. And so does an abacus. This is not intelligence, though these are all artefacts.

The proof is complete, but it is doubtful it will be convincing to those who have for too long believed their own press. So let’s press the example.

Suppose we add more complexity to our ANN, as in the picture above. The topmost “hidden” node takes inputs from three input nodes, and produces, after weighting these three inputs, two inputs to output nodes, which in those output nodes are hit with other weights to produce z_1 (the topmost output node). The weights are not drawn, but they are there, as described.

Well, this is simply a mechanical process, once the weights are specified. Barring malfunction, it is entirely deterministic. It is a dry process. There is no mystery to it. Adding layers and complexity just makes it bigger and more expensive to run. It will never make it alive, or intelligent. A pipe organ is not more alive than a flute because it has more gears and levers.

It does not matter where the weights come from, via back propagation or something else. A weight is a weight. Changing from w = 2 to w = π does not make our simple ANN alive or intelligent because the second weight is more complex. Playing only the black keys on piano does not make the tune closer to an intelligence than playing only Jingle Bells.

Since the origin of the weights do not matter, it does not matter if they are recreated on some regular basis, perhaps as a function of how far the output nodes are from some eventual reality. That is, making the mechanism “dynamic” does not make it alive, or intelligent. If fact, as was explained in the abacus example, it makes no difference whatsoever. It is just makes it more complex.

Too, speeding up the calculations only makes the thing run faster; speed is not intelligence. And there is nothing that will “emerge” from the structure as complexity grows—not supported by any physical process, that is. (The topic of “emergence” needs its own article.)

There is no hope of creating intelligence from artificial neural networks, or anything that works in a similar fashion to them.

I have more on this topic in Uncertainty: The Soul of Modeling, Probability & Statistics.

I learned of the Axios article from Christos Argyropoulos.

Signal + Noise vs. Signal — Important Update

If we imagine these are atmospheric concentrations or stock price anomalies, this is a terrific example of reification, or replacing what did happen with what did not.

Update I see that I failed below to demonstrate the ubiquity of the problem. So your homework is to search “testing trend time series” and similar terms and discover for yourself. Any kind of hypothesis test used on a time series counts.

My impetus was in reading an article about a paper some colleagues and I wrote about atmospheric ammonia. The author wrote, “The statistical correlation between hourly ammonia concentrations between measurement stations is weak due to large variability in local agricultural practice and in weather conditions. If data are aggregated to longer time scales, correlations between stations clearly increase due to the removal of noise at the hourly timescale.”

There’s the belief in “noise”, which does not exist, and there’s also the second (bigger) mistake, which is measuring correlation of time series after smoothing, which increases (in absolute value) the correlation (as has been proved here and Uncertainty_ many, many, many times). This happens even for two strings of absolutely unrelated, made-up numbers. Try it yourself.

So you just look for mentions of “noise” in stock prices, and so on and see if I’m right about the scale of the problem.

Original article

Two weeks ago the high temperature on the wee island upon which I live was 82F (given my extreme sloth, I am making all details up).

Now for the non-trick question: What was the high temperature experienced by those who went out and about on that day?

If you are a subscriber to the signal+noise form of time series modeling, then your answer might be 78F, or perhaps 85F, or even some other figure altogether. But if you endorse the signal form of time series modeling, you will say 82F.

Switch examples. Three days back, the price of the Briggs Empire stock closed at $52 (there is only one share). Query: what was the cost of the stock at the close of the day?

Signal+noise folks might say $42.50, whereas signal people will say $52.

Another example. I was sitting at the radio AM DXing, pulling in a station from Claxton, Georgia, WCLA 1470 AM. The announcer came on and through the heavy static I thought I heard him give the final digit of a phone number as “scquatch”, or perhaps it was “hixsith”.

Here are two questions: (1) What number did I hear? (2) What number did the announcer say?

The signal+noise folks will hear question (1) but give the answer to (2) (they will answer (2) twice), whereas the signal folks will answer (1) with “scquatch or hixsith”, and answer (2) by saying, “Hey signal+noise guys, a little hand here?”

We have three different “time series”: temperature, stock price, radio audio. It should be obvious that everybody experiences the “numbers” or “values” of each of these series as they happen. If it is 82F outside, you feel the 82F and not another number (and don’t give me grief about fictional “heat indexes”); if the price is $52, that is what you will pay; if you hear “scquatch”, that is what you hear. You do not experience some other value to which ignorable noise has been added.

For any time series (and “any” include our three), some thing or things caused each value. A whole host of physical states caused the 82 degrees; the mental and monetary states of a host of individuals caused the $52; a man’s voice plus antenna plus myriad other physical states (ionization of certain layers of the atmosphere, etc.) caused “scquatch” to emerge from the radio’s speakers.

In each case, if we knew—really knew—what these causes were, we would not only know the values, which we already knew because we experienced them, but we could predict with certainty what the coming values would be. Yet this list of causes will really only be available in artificial circumstances, such as simulations.

Of the three examples, there was only one in which there was a true signal hidden by “noise”, where noise is defined as that which is not signal. Temperature and stock price were pure signal. But all three are routinely treated in time series analysis as if they were composed of signal+noise. This mistake is caused by the Deadly Sin of Reification.

No model of any kind is needed for temperature and stock price; yet models are often introduced. You will see, indeed it is vanishingly rare not to see, a graph of temperature or price over-plotted with a model, perhaps a running-mean or some other kind of smoother, like a regression line. Funny thing about these graphs, the values will be fuzzed out or printed in light ink, while the model appears as bold, bright, and thick. The implication is always that the model is reality and values a corrupted form of reality. Whereas the opposite is true.

The radio audio needs a model to guess what the underlying reality was given the observed value. We do not pretend in these models to have identified the causes of the reality (of the values), only that the model is conditionally useful putting probabilities on possible real values. These models are seen as correlational, and nobody is confused. (Actual models, depending on the level of sophistication, may have causal components, but since the number of causes will be great in most applications, these models are still mostly correlational.)

We agreed there will be many causes of temperature and stock price values. One of the causes of temperature is not season—how could the words “autumn” cause a temperature?—though we may condition on season (or date) to help us quantify our uncertainty in values. Season is not a cause, because we know there are causes of season, and that putting “season” (or date) into a model is only a crude proxy for knowledge of these causes.

Given an interest in season, we might display a model which characterizes the average (or some other measure) of uncertainty we might have in temperature values by season (or date), and from this various things might be learned. We could certainly use such a model to predict temperature. We could even say that our 82F was a value so many degrees higher or lower than some seasonal measure. But that will not make the 82F less real.

That 82F was not some “real” seasonal value corrupted by “noise”. It cannot be because season is not a cause: amount of solar insolation, atmospheric moisture content, entrainment of surrounding air, and on and on are causes, but not season.

Meteorologists do attempt a run at causes in their dynamic models, measuring some causes directly and others by proxy and still others by gross parameterization, but these dynamical models do not make the mistake of speaking of signal+noise. They will say the temperature was 82F because of this-and-such. But this will never be because some pure signal was overridden by polluting noise.

The gist is this. We do not need statistical models to tell us what happened, to tell us what values were experienced, because we already know these. Statistical models are almost always nothing but gross parameterization and are thus only useful in making predictions, thus they should only be used to guess the unknown. We certainly do not need them to tell us what happened, and this includes saying whether a “trend” was observed. We need only define “trend” and then just look.

Why carp about this? Because the signal+noise view brings in the Deadly Sin of Reification (especially in stock prices, where everybody is an after-the-fact expert), and that sin leads to the worse sin of over-certainty. And we all know where that leads.

Addendum

“But, Briggs. What if we measured temperature with error?”

Great question. Then we are in the radio audio case, where we want to guess what the real values were given our observation. There will be uncertainty in these guesses, some plus-or-minus to every supposed value. This uncertainty must always be carried “downstream” in all analyses of the values, though it very often isn’t. Guessing temperatures by proxy is a good example.

I have more on this topic in Uncertainty: The Soul of Modeling, Probability & Statistics.