I think the comments by "Lowell & Salzman L I E" rebut this well:
The methodological problem in the study is it, surprisingly, uses the narrow employment designation of "science and engineering occupation". The National Science Foundation specifically warns, �??The S&E labor force does not include just those in S&E occupations. S&E skills are needed and used in a wide variety of jobs.�?? However, the study used a 4.8 million figure for science-related jobs, which is the number for those in occupations formally defined as S&E, even though nearly 13 million workers say they need at least a bachelor's degree level of knowledge in science and engineering fields in their jobs. In other words, the study reached its conclusion primarily by ignoring about 8 million people in US labor force. That appears to be reason the study arrived at the claim that US has about three times as many S&E graduates as S&E job openings each year, even though there is no evidence of massive unemployment among recent graduates in these fields.
The broader problem with the study is it assumes a "bean counting" approach to what is dynamic in nature. After all, there was not even an Internet economy two decades ago, so to assume that we have plenty of talented people, assumes that we have created all the innovations we need and, therefore, American companies should stop trying to invent and innovate. A market economy can never have too many talented people, since, as we have seen, smart employers and entrepreneurs will utilize this talent to improve all our lives. * -- Pages 10-11 of Talent Search: Job openings and the need for Skilled Labor in US Economy, NFAP Policy Brief, Mar 2008 http://nfap.com/pdf/080311talentsrc.pdf
Every scientist who discovers a new class of drugs requires ten* more to study all the derivatives.
Every engineer who creates a new machine allows ten* more to build machines that use this machine.
S&E create wealth. The other top-paying degrees -- law, business -- don't create wealth. They may allow the S&E to more efficiently create wealth, but they don't create wealth.
*Number made up, but it is certainly greater than zero
And a business guy who who handles the business end allows ten more engineers to build useful machines.
A natural extension of your logic: GvR or Stallman may allow S&E people to more efficiently create wealth, but he doesn't create wealth himself (Python, Emacs, etc are only tools to create other stuff)
This topic is disappearing, but I'd still like to address your point.
Wealth def. 3b: anything that has utility and is capable of being appropriated or exchanged.
Python and emacs fit the definition, but making decisions in a company produces nothing that can be "appropriated or exchanged". Python and emacs are wealth just as much as a screwdriver and hammer are.
Also, if 100% of people functioned as scientists or engineers, things (wealth) would still be made. Money is just a claim against the wealth of the nation; just because you can earn more money doesn't mean you've increased the collective wealth.
Every businessman with an idea for an invention requires ten* engineers to slave away on the implementation while he takes most of the profits
*Number made up, but one should always remember that it's not only scientists and engineers that are coming up with ways to make our lives better and create wealth
> The other top-paying degrees -- law, business -- don't create wealth. They may allow the S&E to more efficiently create wealth, but they don't create wealth.
"Salzman says that reports citing low U.S. international rankings often misinterpret the data. Review of the international rankings, which he says are all based on one of two tests, [...] show the U.S. is in a second-ranked group, not trailing the leading economies of the world as is commonly reported."
If I am understanding that correctly, that is not so much misinterpreting the data as not being able to frickin read.
Misinterpreting data, to me, signals an improper application of statistics to some raw data to assert something.
Not being able to look at a grouped list of rankings and realize that just because a certain group as a whole is below another group as a whole does not imply that every country in the second group is below every country in the first group is, well, sheer idiocy, not merely misinterpretation.
If the basis of the 'US is behind in math' idea is really that policy types and journalists can't properly interpret the set of rankings, then it really scares me that they are in charge of our public discourse/policy.
For those who don't follow the link, the first link places the US, with 95% confidence intervals:
- 25th to 28th among the 40 countries on math;
- 12th to 23rd among the 40 countries on reading;
- 20th to 27th among the 40 countries on science.
The second link just divides the countries into above average, average, and below average. The US is "below average" on math, and no reading rank is reported.
It's often said that the countries that score better than the United States in internationally standardized achievement tests are only testing a high-ability sample of their population, while the United States is testing a representative sample. But this is baloney. One example of a webpage about this issue is
More generally, I know the assertion is wrong because I can read the languages of other countries and I have lived overseas and I have observed their school systems and how the common people of other countries live in daily life. Several of the newly industrialized countries of east Asia and southeast Asia have a much higher level of numeracy, such that algebra is a standard curriculum subject for all students in seventh grade, including the below-average students, and such that people from those countries think it is bizarre that American store clerks count out change from a purchase for their customers, as if the customers can't calculate their own correct change mentally. Simply put, the policy analysts and journalists who say the United States is behind other countries and thus behind where it should be (given the very large expenditure on K-12 education in the United States) are correct.
A good point made by a previous reply here is that sci-tech skill sets are relevant in more than just sci-tech jobs. It would indeed be good if more lawyers, physicians, business managers with business degrees, and technicians and industrial workers without college degrees had strong knowledge of math and science. That is what makes manufacturing successful in many developing, low-wage countries: the workers on the factory floor and their foremen have a basic level of technical skill that allows efficient manufacturing that can produce products with a finished cost (including shipping to distant markets) and level of quality that is competitive in international markets.
It looks like the methodology that they are comparing is very different. The BusinessWeek article cites things like increasing numbers of people achieving in those subject areas. The international surveys look at the average achievement in those subject areas.
To simplistically illustrate with made up facts:
Let's say BusinessWeek finds that in 1990, 5% of students achieve an excellent result in math and in 2000 10% of students achieve an excellent result in math. That's quite an increase. Let's say that there were 100 students and so the "A" category increased from 5 to 10 students. Awesome! However, that doesn't tell us what the average student is achieving.
The OECD and others usually look at the average (mean or median) achievement. It is entirely possible that elite education is increasing while average education is decreasing.
If you look at those two distributions, you can come to different conclusions based on your methodology. By mean average, the US is declining from a 1.75 score to 1.55. However, the US also has more achieving really excellent scores.
One thing to note about a study like this is that the United States tends to have more immigrants than other nations. Immigrants are fine people, but they face disadvantages in integrating into a new society. Often times there are language and cultural barriers that slow learning as, well, part of their learning is spent overcoming those barriers. This could drag down average US scores in academics when comparing them to countries that don't have immigrants that might spend a lot more time learning the spoken language over studying math. If you're dealing with two people of equal ability, but one has to study a second language to become fluent first, that person's achievement won't be as great (or at least will be delayed as they have taken time to study something else). This isn't something bad about immigrants, but it does say that there might be biases in the results of a study if one group includes more immigrants.
There are also much greater selection biases in other countries. Take France vs the US as an example. In the US, most students attend a traditional high-school. Yes, there are vocational schools, but those aren't stressed. So, in the US, an academic test is likely to cover a decently random sampling of the population at any given age. In France, secondary education is very segregated. As such, it is possible that there is quite a selection bias for the exams between those that are studying sciences and math and those that are doing vocational studies in who takes the exam.
I do think the US should be doing more to promote math, science and engineering, but I wouldn't be so quick to say that the US is fundamentally behind. The US education system does face challenges that many other systems don't - such as absorbing a greater number of immigrants, dealing with historical prejudices that have disenfranchised and disadvantaged many, and trying to academically (vs vocationally) educate the vast majority of our children.
I'm not saying that anything in here is correct. I haven't studied international education enough to make any conclusions. This is simply meant to raise the possibility that the statistics aren't the full picture.
The methodological problem in the study is it, surprisingly, uses the narrow employment designation of "science and engineering occupation". The National Science Foundation specifically warns, �??The S&E labor force does not include just those in S&E occupations. S&E skills are needed and used in a wide variety of jobs.�?? However, the study used a 4.8 million figure for science-related jobs, which is the number for those in occupations formally defined as S&E, even though nearly 13 million workers say they need at least a bachelor's degree level of knowledge in science and engineering fields in their jobs. In other words, the study reached its conclusion primarily by ignoring about 8 million people in US labor force. That appears to be reason the study arrived at the claim that US has about three times as many S&E graduates as S&E job openings each year, even though there is no evidence of massive unemployment among recent graduates in these fields.
The broader problem with the study is it assumes a "bean counting" approach to what is dynamic in nature. After all, there was not even an Internet economy two decades ago, so to assume that we have plenty of talented people, assumes that we have created all the innovations we need and, therefore, American companies should stop trying to invent and innovate. A market economy can never have too many talented people, since, as we have seen, smart employers and entrepreneurs will utilize this talent to improve all our lives. * -- Pages 10-11 of Talent Search: Job openings and the need for Skilled Labor in US Economy, NFAP Policy Brief, Mar 2008 http://nfap.com/pdf/080311talentsrc.pdf