Me too Michael, me too. I figured the folks who were using the "prevention" numbers would be able to clarify it for me. Guess I figured wrong. /shrug.
_________________ "Dress cops up as soldiers, give them military equipment, train them in military tactics, tell them they’re fighting a ‘war,’ and the consequences are predictable." —Radley Balko
Joined: Thu Sep 03, 2009 9:59 am Posts: 15740 Location: Combat Information Center
Khross wrote:
Arathain:
Our military is already over-extended and under-staffed for current engagements. I would not oppose expanding our military to 1990 levels at a minimum. Even then, we might not actually have enough people in uniform to address current conflicts. We have also continued to cut funds for both personnel, maintenance, and innovation over the last 20 years.
If you want to dramatically cut funding, you will need to cut more personnel, eliminate more redundancy in our officer corps, and withdraw the United States from international military actions and personnel obligations. Our first priority should be domestic defense and national self-interest: if we cannot protect either, then our military fails to meet its constitutional requirements.
Khross: I strongly agree with the underlined portion. That said, what would you say to the assertion that the military is viewed entirely too prevalently as a social benefit rather than a source of combat power, and that cuts cout be made to pointless, inefficient agencies and contracting within it resulting in significant monetary savings without reduction in combat power.
_________________ "Hysterical children shrieking about right-wing anything need to go sit in the corner and be quiet while the adults are talking."
.....well, I'm going to go with the number they stated in the OP. One could make a reasoned argument that it's less, but I'm sure you're going to argue that it's actually zero.
Since they pass out condoms and encourage other forms of birth control, I'm going to advance the theory that it is substantially more than zero.
Then I think I deserve federal funding. I've prevented far more pregancies than planned parenthood. I daily do not impregnate thousands of women therefore preventing thousands of unwanted pregnancies each day. I'm going to compound that number by factoring in the amount of money I save federal and state agencies for not having to raise my offspring. I'm a saving machine according to the numbers!
We need to justify funding and results on hard data of what is performed, not the current trend of claiming victory when something doesn't happen. "Saved or created" is a sham.
_________________ A man who has nothing for which he is willing to fight, nothing which is more important than his own personal safety, is a miserable creature and has no chance of being free unless made and kept so by the exertions of better men than himself. ~ John Stuart Mill
It's not a sham; it's just hard to quantify. For instance, it's hard to say exactly how many deaths would be prevented if Americans switched to a healthier diet and exercised more, but that doesn't mean advocating diet and exercise is a sham.
It's not a sham; it's just hard to quantify. For instance, it's hard to say exactly how many deaths would be prevented if Americans switched to a healthier diet and exercised more, but that doesn't mean advocating diet and exercise is a sham.
Everyone dies so the answer is 0 deaths would be prevented.
It's not a sham; it's just hard to quantify. For instance, it's hard to say exactly how many deaths would be prevented if Americans switched to a healthier diet and exercised more, but that doesn't mean advocating diet and exercise is a sham.
But deeming advocating those changes as the reason for a dip in deaths would be irresponsible correct? Same with this "statistic" and ones on the econ that are being put out for jobs. You can't define something by explaining what it isn't.
_________________ A man who has nothing for which he is willing to fight, nothing which is more important than his own personal safety, is a miserable creature and has no chance of being free unless made and kept so by the exertions of better men than himself. ~ John Stuart Mill
Joined: Thu Sep 03, 2009 9:35 am Posts: 2903 Location: Maze of twisty little passages, all alike
RangerDave wrote:
It's not a sham; it's just hard to quantify. For instance, it's hard to say exactly how many deaths would be prevented if Americans switched to a healthier diet and exercised more, but that doesn't mean advocating diet and exercise is a sham.
It's not just "hard" to quantify; it's impossible, barring an invention that allows us to see into alternate universes. These types of claims are what historians would call "counterfactuals". If we take action A, we cannot factually know what would have happened if we had not taken action A. We can theorize and make conjecture, but as soon as we start talking about things that didn't actually happen, we are outside the realm of fact.
Hard sciences address this problem precisely by trying it both ways. They run parallel experiments in which they do A and A' (the control) and compare the results over a very large number of trials. With enough repetitions, and with extreme care that the experimental conditions are exactly the same, and that all other possible variables that might affect the results have been eliminated, this provides (if the theory is "correct") an increasingly strong correlation between action A and a particular type of result. In time, our confidence in this correlation is so strong, and because we have taken great effort to eliminate every other possibility we can think of, we basically stop caring that we can't actually, strictly prove causation.
In the social sciences , this kind of rigorous experimentation is rarely done. For the most part, it really can't be done. The experimental conditions for a proposition like "does PP, in its entirety, increase or decrease the total number of abortions performed in the U.S." are simply far too complicated to ever reproduce exactly in way that the variables can be accounted for and controlled in order to establish a valid correlative model. Simply put, we cannot make an exact clone of the United States, sans Planned Parenthood, and compare what happens to the United States with Planned Parenthood at exactly the same moment in time, etc., etc. Since we can't do that, we could try shutting down Planned Parenthood and see what happens. Of course, this wouldn't be very statistically significant, but at least it's a valid, factual experiment that provides real data. All of the "statistics" published so far (in either direction) are just wild-ass guesses. No one has actually tried seeing what happens in real life.
This issue is basically the elephant in the room for the economic and social sciences. To cope with these problems, sociologists often employ techniques like regression analysis to eliminate variables from the equation, so to speak. Regression analysis is certainly a valid tool of statistics, but the difficulty is in applying it in a valid way. This is where things get very ... soupy for non statistics nerds, and the laymen is easily lost. Regression analysis is complicated, and its a big pain in the *** for sociologists. In more recent decades, this method is being pushed out of the way by the "counterfactual model", which -- from what I've read about it -- is even more divorced from reality.
The core of the counterfactual model for observational data analysis is simple. Suppose that each individual in a population of interest can be exposed to two alternative states of a cause. Each state is characterized by a distinct set of conditions, exposure to which potentially affects an outcome of interest, such as labor market earnings or scores on a standardized mathematics test. If the outcome is earnings, the population of interest could be adults between the ages of 30 and 50, and the two states could be whether or not an individual has obtained a college degree. Alternatively, if the outcome is a mathematics test score, the population of interest could be high school seniors, and the two states could be whether or not a student has taken a course in trigonometry. In the counterfactual tradition, these alternative causal states are referred to as alternative treatments. When only two treatments are considered, they are referred to as treatment and control.Throughout this book, we will conform to this convention.
The key assumption of the counterfactual framework is that each individual in the population of interest has a potential outcome under each treatment state, even though each individual can be observed in only one treatment state at any point in time. For example, for the causal effect of having a college degree rather than only a high school degree on subsequent earnings, adults who have completed high school degrees have theoretical what-if earnings under the state “have a college degree,” and adults who have completed college degrees have theoretical what-if earnings under the state “have only a high school degree.” These what-if potential outcomes are counterfactual.
Formalizing this conceptualization for a two-state treatment, the potential outcomes of each individual are defined as the true values of the outcome of interest that would result from exposure to the alternative causal states. Thepotential outcomes of each individual i are y1i and y0i, where the superscript 1 signifies the treatment state and the superscript 0 signifies the control state. Because both y1i and y0i exist in theory for each individual, an individual-level causal effect can be defined as some contrast between y1i and y0i, usually the simple difference y1i-y0i. Because it is impossible to observe both y1i and y0i for any individual, causal effects cannot be observed or directly calculated at the individual level.2
By necessity, a researcher must analyze an observed outcome variable Y that takes on values yi for each individual i that are equal to y1i for those in the treatment state and y0i for those in the control state. We usually refer to those in the treatment state as the treatment group and those in the control state as the control group.3 Accordingly, y0i is an unobservable counterfactual outcome for each individual i in the treatment group, and y1i is an unobservable counterfactual outcome for each individual i in the control group.
In the counterfactual modeling tradition, attention is focused on estimating various average causal effects, by analysis of the values yi, for groups of individuals defined by specific characteristics. To do so effectively, the process by which individuals of different types are exposed to the cause of interest must be modeled. Doing so involves introducing defendable assumptions that allow for the estimation of the average unobservable counterfactual values for specific groups of individuals. If the assumptions are defendable, and a suitable method for constructing an average contrast from the data is chosen, then an average difference in the values of yi can be given a causal interpretation.
Finally, it must of course be pointed out that in all of the above, including the hard sciences in many cases, you should understand that the very idea that the results of these experiments imply something about the probability of causal theory is an offspring of the field of thought known as as Bayesian probability. This is an enormous unto itself.
_________________ Sail forth! steer for the deep waters only! Reckless, O soul, exploring, I with thee, and thou with me; For we are bound where mariner has not yet dared to go, And we will risk the ship, ourselves and all.
Your're using very imprecise terms like "cut the hell out of" and "significant presence" and I really have a hard time knowing what you mean when you say those. Thus, in a very technical sense, you're correct: it is possible to do that.
Intentionally, as I don't have access to data necessary to generate realistic numbers. I'm merely trying to convey my opinion that it can be done to some degree.
Joined: Thu Sep 03, 2009 9:59 am Posts: 15740 Location: Combat Information Center
Arathain Kelvar wrote:
Diamondeye wrote:
Your're using very imprecise terms like "cut the hell out of" and "significant presence" and I really have a hard time knowing what you mean when you say those. Thus, in a very technical sense, you're correct: it is possible to do that.
Intentionally, as I don't have access to data necessary to generate realistic numbers. I'm merely trying to convey my opinion that it can be done to some degree.
Like I said, it's clearly physcially possible to some unknown degree. I don't think anyone was trying to say it was beyond the realm of what could conceiveably be accomplished.
That, however, doesn't help us much to know because that doesn't reduce the range of possibilities beyond a very miniscule amount.
In your case its excuseable that you don't access the dara because you're simply pointing out the possibility. However Aizle, and quite a few other people, have been equally vague over the years but simply advocate cuts without any real ability to justify those cuts. It's just a vague assertion that the military is "way overfunded", realying on an underlying, possibly unconcious assumption, that there will always be more military to cut, and that it can always absorb more cuts.
_________________ "Hysterical children shrieking about right-wing anything need to go sit in the corner and be quiet while the adults are talking."
It's not a sham; it's just hard to quantify. For instance, it's hard to say exactly how many deaths would be prevented if Americans switched to a healthier diet and exercised more, but that doesn't mean advocating diet and exercise is a sham.
It is when you use it as justification. When you make a claim the burden of proof is on you. When you state a number like X million jobs were...you better be able to prove it. If not then you're lying plain and simple.
_________________ "...but there exists also in the human heart a depraved taste for equality, which impels the weak to attempt to lower the powerful to their own level and reduces men to prefer equality in slavery to inequality with freedom." - De Tocqueville
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, this kind of rigorous experimentation is rarely done. For the most part, it really can't be done. The experimental conditions for a proposition like "does PP, in its entirety, increase or decrease the total number of abortions performed in the U.S." are simply far too complicated to ever reproduce exactly in way that the variables can be accounted for and controlled in order to establish a valid correlative model. Simply put, we cannot make an exact clone of the United States, sans Planned Parenthood, and compare what happens to the United States with Planned Parenthood at exactly the same moment in time, etc., etc. Since we can't do that, we could try shutting down Planned Parenthood and see what happens. Of course, this wouldn't be very statistically significant, but at least it's a valid, factual experiment that provides real data. All of the "statistics" published so far (in either direction) are just wild-ass guesses. No one has actually tried seeing what happens in real life.
unto itself.
