But many are inalienable. It's a tough argument, particularly within the context of history and the constitution, to argue gun control. You pretty much have to stick to "ban guns because I'm scared."
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Justice Scalia would disagree with you -
Like most rights, the right secured by the Second Amendment is not unlimited. From Blackstone through the 19th-century cases, commentators and courts routinely explained that the right was not a right to keep and carry any weapon whatsoever in any manner whatsoever and for whatever purpose. See, e.g., Sheldon, in 5 Blume 346; Rawle 123; Pomeroy 152-153; Abbott 333. For example, the majority of the 19th-century courts to consider the question held that prohibitions on carrying concealed weapons were lawful under the Second Amendment or state [****95] analogues. See, e.g., State v. Chandler, 5 La. Ann., at 489-490; Nunn v. State, 1 Ga., at 251; see generally 2 Kent *340, n 2; The American Students' Blackstone 84, n 11 (G. Chase ed. 1884). Although we do not undertake an exhaustive historical analysis today of the full scope of the Second Amendment, nothing in our opinion should be taken to cast doubt on longstanding prohibitions on the possession [**2817] of firearms by felons and the mentally ill, or laws forbidding the carrying of firearms in sensitive places such as schools and government buildings, or laws imposing [*627] conditions and qualifications on the commercial sale of arms.26Link to the text of the note
LEdHN[21] [21] HN21 We also recognize another important limitation on the right to keep and carry arms. Miller said, as we have explained, that the sorts of weapons protected were those "in common use at the time." 307 U.S., at 179, 59 S. Ct. 816, 83 L. Ed. 1206. We think that limitation is fairly supported by the historical tradition of prohibiting the carrying of "dangerous and unusual weapons." See 4 Blackstone 148-149 (1769); 3 B. Wilson, Works of the Honourable James Wilson 79 (1804); [****96] J. Dunlap, The New-York Justice 8 (1815); C. Humphreys, A Compendium of the Common Law in Force in Kentucky 482 (1822); 1 W. Russell, A Treatise on Crimes and Indictable Misdemeanors 271-272 (1831); H. Stephen, Summary of the Criminal Law 48 (1840); E. Lewis, An Abridgment of the Criminal Law of the United States 64 (1847); F. Wharton, A Treatise on the Criminal Law of the United States 726 (1852). See also State v. Langford, [***679] 10 N. C. 381, 383-384 (1824); O'Neill v. State, 16 Ala. 65, 67 (1849); English v. State, 35 Tex. 473, 476 (1871); State v. Lanier, 71 N. C. 288, 289 (1874).
D.C. v. Heller
I'm always for more data. But.
You have zero context for the statements you're making about models being young, or things being uncertain, or the quality of data. As compared to what? Ideal data? The current climate models probably have more man and computational hours into them than 99% of scientific simulations will ever see. It's entirely possible they're king of the hill.
In regards to a "wrong theory," certainly you're not arguing that the last 300 years of physics are incorrect. I thought we agreed that CO2 was a greenhouse gas, infrared radiation comes from the sun, and humidity exists. What I thought you were arguing is that forcing was overestimated, which would mean an adjustment to one of the parameters in the models. The difference between a "wrong theory" and a parameter in a model isn't pedantic, it's yet another example demonstrative of the gaping chasm between scientific practice and your understanding. TSI is not just now being examined, it has been looked at for decades. Half of a minute on Google Scholar clearly demonstrates this.
I agree, you have to have a strong foundation to work from. The foundation you've demonstrated entails an absolute complete lack of understanding of the mathematics, empiricism and analysis that goes into these studies. All else aside, without the mathematical foundation you're just parroting what you read elsewhere. Every single one of your posts is riddled with misconceptions and misunderstandings about the theory, the analysis, and the data, and even without your confrontational attitude the prospect of correcting them all is completely overwhelming. You are probably the most ideal personification of Dunning Kruger I have ever encountered.
I obviously can't stop you from continuing to make sweeping (and way overly authoritative) statements about things you very clearly do not understand, all I can do is recommend taking a couple calc or modern physics courses at your local community college. You know, for some of that good old-fashioned liberal indoctrination.
https://futurism.com/watch-neil-degr...for-americans/
Seems to fit to the topic.
Zero context? Reality vs models is the context. And the models failed.Quote:
You have zero context for the statements you're making about models being young, or things being uncertain, or the quality of data. As compared to what? Ideal data? The current climate models probably have more man and computational hours into them than 99% of scientific simulations will ever see. It's entirely possible they're king of the hill.
The fact that they both failed and now even Mann and Sanger are saying they are wrong not only agrees there is uncertainty, but that there is something that is still undiscovered, that the underlying science is wrong.
I agree this isn't a simple field, but the alternative is that we are making hard and fast claims based on limited data and poor models. Models that can't even adjust for clouds, because the scale of the grid is still 500 miles a sector, and clouds are too small.
Also the factors involved are huge, the equation is a huge hot mess also. You should download the FORTRAN code some time and read the programmer notes. Lots of items like aerosols are just fudge factor codes, manual adjustments in the code.
I think it can be better - far better. And part of that is scrapping the old model all together, and also looking at other theories - something that hasn't been very frowned upon since the Hansen Model. Erik was working on a 12 dimension AI, and I was trying to get the company to retro weight 12 factors into the AI so we could actually build a clearer picture of weights for the items like CO2, water vapor, methane, etc. We have the tech, but we do need more data than one CO2 sample point that is our given. Hence the good news the OCO-2 satellite is up - but we only have just under 2 years of data from it. And it totally contradicts all previous CO2 models.
Hence, the use of the word "YOUNG".
Like you said - we have been through this before. And so you know that I am not making that argument. You obviously missed something or I miss-explained something, or even made a typing error and instead of going "hey, we are past this, maybe he meant something else, I will ask him to explain" you fall back on a stupid strawman that is off topic.Quote:
In regards to a "wrong theory," certainly you're not arguing that the last 300 years of physics are incorrect. I thought we agreed that CO2 was a greenhouse gas, infrared radiation comes from the sun, and humidity exists.
This is where you mistake the design and structure of the model. You seem to have some assumptions of it, and think I am the one who doesn't understand it.Quote:
The difference between a "wrong theory" and a parameter in a model isn't pedantic, it's yet another example demonstrative of the gaping chasm between scientific practice and your understanding.
The model as is uses a method of structure that holds items constant deliberately so as to see other results that are forcings. But these items vary hugely through out the grid. Some items that have a large variability in relation to CO2, like clouds, are set to a constant. Clouds, if they change just 1% can overshadow the affect of 285 to 400ppm of retained energy from CO2. There hasn't been either a good way to add clouds to the model, nor has there been a lot of ability to get detailed cloud cover for the last 100 years because we haven't had the tools, nor were they applied to this type of modeling. They just put it in
Again, the science is still young, and our tools are poor. We can just lightly guess at the point this process was started using proxies and some small very localized datasets, compared to the far more rich and complex data we are just now getting from satellites. Shoot, our previous models of CO2 flow were a 'known' - until the OCO-2 went up and changed all of that. If they used that as the go-by, with detailed usage in the models, the new empirical data just trounced it. Everything would need to be re-written. Hence, young. Premature might be a better word.
The problem is the error bars on the models are far larger than the signal. The adjustments that are being adjusted manually are larger than the signal. While we see a result from the models that is completely wrong. This is not a PID loop - this is a hard variable adjusted to try and make the curve fit.
They all are wrong. They do not track with empirical data. They are all falsified.
They may have used large amounts of computer processing time, and that might impress you, but the argument is lost, completely, if they failed to model anything correctly or even come close.
Here you are, high on your horse telling me I need to revisit college, yet the principle you are missing to cover your argument is Middle School level basic science.
If the data is falsified by empirical study, then the hypothesis is wrong.
Even with all of the playing with clouds and methane and 200yo science, something is completely, consistently, methodologically wrong.
It is falsified. You keep trying to support a theory that is FALSE that produced Models that are FALSE.
That is a level of stubbornness and arrogance that is kind of fantastic to watch, but the science isn't on your side. It might not be 100% on mine, but it is 70% not yours. Sanger and Mann and a good chunk of those who supported the AWG Theory are now on my side.
Steve, you lost the argument that models are correct. That they can forecast anything. That they play in a curve that resembles reality. They don't. By the amount that Richard Lindzen said. By the amount that I said. By the amount that now Sanger and Mann said. We are all saying the same thing on this now... so...
You already lost.
Show some sportsmanship.
josh lost this before he even started it. lol.
As far as I can tell you are basing the "models are wrong, Mann and Santer agree with Lindzen" statement on the following:
http://www.meteo.psu.edu/holocene/pu...reGeosci17.pdf
But, in the first 2 pages, they clarify how the external forcings are "wrong":
Their statistical analyses is essentially correcting parts of the models with data to see whether or not internal variability could explain "the pause" - it cannot. They explicitly counter your position that the overall forcings are wrong:Quote:
Originally Posted by the paper
Emphases mine. References for further investigation of the stratospheric water vapor trends (likely to be lower frequency than tropospheric)Quote:
Originally Posted by same paper
https://pdfs.semanticscholar.org/e97...e444cbbb97.pdf
For a background in why the simplistic explanation doesn't reproduce the historical record over short terms:
https://www.atmos-chem-phys.net/17/8...-8031-2017.pdf
I don't know who Erik is, but a "12 dimensional AI" sounds an awful lot like a neural network with 12 input parameters. Without knowing anything else about the architecture (a simple, non-deep model can be executed in softwares as simple as Excel), I can tell you with high confidence that this is not a good approach. You'd need, at minimum, an LSTM-RNN, and even then you're almost certainly overfitting. As these models are completely data driven, they can only probe retroactive effect sizes, and are very hard to get causality out of, because they tend to be time-lag agnostic. Some understanding of the physics is needed to inform the models, and then empirical fits to the data tend to work really well. The chemical engineering curriculum is replete with examples of this - I've been putting the Chilton-Colburn analogy in heavy rotation myself lately.
Okay, you kinda got me, you are right, science is about understanding. But that isn't this discussion. It was said I took anti-scientific positions, of which you stated affirmative.
In the end, my scientific position was upheld, with science. Your's was not. It is still the internet, it isn't about science. It is about being right.
(bows)
I am repeating myself, again, but: 'The Theory' states water vapor will increase at a rate of approximately 3X the amount of CO2, since CO2 and Water have a 'power' of about 1.
Without that forcing CO2 is not a run-away GHG. It needed to use water as the feedback for that.
The skeptics have said this for a while. The models were based on that. If there was not a 3X increase in stratospheric water vapors, the Theory is wrong.
Well,
No increase. A slight decrease.Quote:
a decrease in stratospheric water vapour
The net effect of the forcing errors is that
the simulations underestimate some of the cooling influences
contributing to the observed ?slowdown
There is no conflict - that stated exactly what I have been stating for a while. In fact, Lindzen actually measured that forcing in the 2009 and 2011 papers and found it to be negative.
This has been killed Ryan. A dozen times in here. I am just repeating myself. Again and again.
Here is a picture:
http://joannenova.com.au/globalwarmi...g-water-DE.jpg