Posted on 04/10/2020 10:52:27 AM PDT by LilFarmer
The few parents of school-age kids I’ve talked all say their kids are sailing through their at-home and on-line courses far faster than they do in school. And they attribute it to schools teaching to the lowest common denominator, plus time wasted because of disruptive kids.
Oh.
Well if my good friend did not run off to the Philipines to avoid this government, he could have pointed out at least a few dozen errors in translation from the original text. He finds them everytime he looks for em. He went out there to preach the good word. What I see is a society corrupted by debt based currency. Are we going for 100 trillion short term ?
Translation glitches vary.
Some are a question of whether the original said “Jesus Christ” or the reverse “Christ Jesus”.
Some are variants in the Greek spelling of “David”. Some are variants of verb tense (not “Jesus wept” v. “Jesus did weep”, but similar).
There is a list of slightly bigger variants here: https://en.wikipedia.org/wiki/List_of_major_textual_variants_in_the_New_Testament
Again, almost none of them give me much concern.
The overwhelming majority of these differences are only of interest to pedantic scholars. Other than the long ending of Mark’s Gospel, none have any real significance that affects the guidance scripture gives for our lives.
You’re not giving your metric a chance to prove itself.
To show my point (Without resorting to math I haven’t used more than half a dozen times in 50 years...)
Say that a week ago you wanted to predict the deaths today.
You should use what was predicted by your metric for today , not what was shown by your metric a week ago.
And to predict the deaths a week from now you should use what is predicted by your metric for a week from now.
Not what it shows today.
Sure slopes and graphs change.
But you’re not giving your graph a fair chance.
Alright, I took my shot.
As the counter-example, I've been in my home office continuously since 2014. I decided that required some changes from being 193 lbs @ 5 ft 11 in. Enter "My Fitness Pal". Premium package. Zone proportions: calories 30% protein, 30% fat, 40% carbs. Intermittent fasting: 600 calories M-Th, 1250 calories T,W,Fr,Sa,Su. Start: 191 lbs Jan 2016. Target 146 lbs. Jan 2017: 146 lbs, 13.6% fat, 20.4 BMI. Currently, 151, 16% fat, 21 BMI. Recent results a consequence of 70 hour weeks for the last 2 years and sleep broken by my diabetic wife working night shift.
I'm hoping the death march program rescue can be reduced to 40 to 50 hour weeks. I'll turn 64 in August. I've worked at this pace most of my life. It would be nice to have a slower pace.
No the original script, requires someone very familiar with the language. He is a bible scholar and I flat out told him that it is very unreadable from a technical point of view. Phrases can literally have 3 or 4 meanings. Context is everything apparently. That’s when he told me about the contextual translation errors.
I think the word you want is model. The metric I came up with is just a way or measuring, evaluating, or tracking something. I happen to use ND/TD, because IMO it's the most accurate. I could just as easily used total cases, or total recoveries, etc., in any number of ways.
A model is a representation or simplified version of a concept, phenomenon, system, ..., or aspect of the real world.
A model predicts or provides accurate information when all factors affecting the outcome are well known and controllable. For instance, in determining stresses some structure may encounter based on known forces and strengths of materials that went into its construction.
I think the word 'model' is overused when applied to real world events such as hurricane tracking, global warming, and in this case, the spread of the corona virus when there are so many unknowns. Without constant updating, as many factors change, such a "model" is not be very useful. As we've seen in the news.
But you’re not giving your graph a fair chance.
I have to say, you're not the only one who looks at this as a proving of this model/graph/metric. Forget about actually trying to predict how fast the virus is spreading, which countries are having the best success, how many would have died if the current measures hadn't been taken, etc.
We're out to prove or disprove something. Well I'm not. I wanted to create a tool, this index based on daily deaths / total deaths, that would be useful in scoring how well a country or state was doing in fighting the spread of the Corona virus. It's proven very useful for that alone. As an additional benefit, it's usable in calculations to predict to some degree where we'll be in days or even weeks.
If one is only interested in proving if a projection was accurate or not, or to what degree, then there are the previous graphs I've posted which could serve as a historical reference to be used in determining exactly how accurate a previous prediction had been.
I already kind of do that with what I consider certain milestones. Back around the 6th April, or maybe even earlier, I had projected about 27,000 fatalities on 15 April. A projection I had run a couple days ago showed about 28,000 for April 15. Tonight I ran another projection that gave a result of 24,605 fatalities for 15 April.
What changed? What changed was the daily fatality index. Several weeks ago, my wife and I went to the grocer and maybe 5 out of 100 people were wearing masks. Two weeks ago we made a trip to the same grocer to replenish fresh food items and maybe 25 out of 100 people had masks. Today we made another trip to the grocer and more than 80 out of 100 people were wearing masks.
You can't model something that hasn't happened in living memory and which has so many unknown factors. It would be like trying to model the NY Stock Exchange and expecting accurate results months from now.
One can update graphs and plots and use what we call technical analysis to determine the general direction of movement, etc., but often real world events completely invalidate what we previously believed would happen.
So there...
Love the “so there...”
me too.
And may I add, thank you, for asking the questions which gave me an opportunity to better describe this tool I'm using. :)
It takes time to train your digestion to efficiently use fat. Starting the day with "bulletproof coffee" on top of a good night's sleep is a big help staying focused on work.
Took it as it was meant. Enjoy our convos.
I can agree with that!
Blueplum,
You are wrong.
See:
Sickle Cell and Recruit Training
https://navymedicine.navylive.dodlive.mil/archives/3184
“Sickle cell disease is a genetic hematologic disorder in which normal adult hemoglobin is substituted by hemoglobin S. Under certain circumstances, this form of the oxygen-carrying part of blood becomes viscous, resulting in damage to the body. Situations which may exacerbate this include low-oxygen conditions, such as those faced by pilots or service members at increased altitudes. Notably for the military, in 1968, four recruits with sickle cell trait (a carrier condition for sickle cell disease) died during training exercises at elevation. Following this, the U.S. Navy began testing all recruits and limiting the operational billets available to those who tested positive. This persisted until 1981, when a class action law suit was filed against the Air Force Academy, citing racial discrimination by declining to admit students with sickle cell trait, which is predominantly found in African Americans. In 1981, the Department of Defense mandated that restrictions be removed.”
And see:
Sickle cell trait and health concerns in Army soldiers
At a Glance
https://www.nih.gov/news-events/nih-research-matters/sickle-cell-trait-health-concerns-army-soldiers
August 23, 2016
Researchers found that sickle cell trait does not raise the risk of death in active-duty U.S. Army soldiers.
Soldiers with sickle cell trait did have a higher risk of a severe breakdown of skeletal muscle caused by strenuous physical activity.
This risk, however, was also increased among older soldiers, those who smoked, were obese, or who had recently used certain medications.
And See:
Sickle Cell Trait Prevalence Among U.S. Military Service Members: 1992–2012
https://academic.oup.com/milmed/article/182/3-4/e1819/4099332
David W. Niebuhr, MC USA (Ret.), Ligong Chen, MD, Stephanie Shao, MPH, Jonathan Goldsmith, MD, Celia Byrne, PhD, Darrell E. Singer, MC USPHS Author Notes
Military Medicine, Volume 182, Issue 3-4, March-April 2017, Pages e1819–e1824, https://doi.org/10.7205/MILMED-D-16-00136
Published: 01 March 2017
horse’s mouth:
///all Marine recruits have a battery of blood testing done on day three of training by staff...Parris Island...sent to the Medical Dispositions Officer...more than 45 percent hemoglobin S, a recruit can be separated from training for a condition that is disqualifying /////
https://navymedicine.navylive.dodlive.mil/archives/3184
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