bearmf

However, I see that there is nothing in the article specifically about primary caregiver being female. To summarize, it is better to have one primary caregiver who has established a strong attachment with child. Traditionally it has been a female role, and I do believe women are better suited for it.

That said, you cannot be a mother to your child. Your roles now are approximately equal, but they will inevitably change over time. Feeding and changing diapers is enough for now, and that indeed can be split between partners, because baby cannot really tell the difference right now.

For further normal development, babies need to develop a bond with their mother. This gives them a fundamental sense of security. It is one of human baby's primary needs which is also observed in most mammals.

Children later become attached to their fathers. It is a different experience for them, which involves more "rational" thought instead of primary urge to bond with their mothers.

EDIT: It is certainly not unheard of, but only for top graduates. Also, I see you were talking about equivalent 110k salary in Toronto which would be 130-140k in New York. This is a high base salary by any standard.

The problem that I see here is that by removing all social and cultural context we will lose some genetic information as well. It is very hard to measure influence of genetics on social or cultural outcomes, but it definitely does exist.

Your points 3-5 are completely wrong. Genetics determines race, not the other way around. Points 4 and 5 are just meaningless "racist" phrases, not statements in a line of reasoning.

Group differences in IQ do exist, and Flynn effect does not make them go away. Flynn effect increases scores across the board, it does not equalize different groups.

Black people in US have lower average IQ than white people do, Asian people have higher average IQ. The reasons for this are many, but genetics certainly comes into play: IQ is heritable.

Trying to explain away group differences by "culture" is mostly bad science - trying to make the facts fir your desired conclusions.

This is indeed independent of degree but highly dependent of company you are working for. There are developers working 10-12 hours a day who cannot structure their work because they are just expected to stay in the office for said time period.

The exception to this exception exists between city and state sovereignties located within the same state. Although cities are different sovereignties than the state they are located within, the two are not permitted to attach jeopardy more than once cumulatively.

He is referring this study: http://www.conferenceboard.ca/hcp/hot-topics/caninequality.a...

It has a chart of INFLATION-ADJUSTED median after-tax income in 2009 dollars, from 1976 to 2009. He then takes a figure for 1984 from this chart, around $48500, and proceeds to compare it to prices in 1984 dollars, without converting them to 2009 dollars.

So from a house price of 100k in 1984, he infers it was only 2x times median income then. While in fact, he needs to convert 100k in 2009 dollars and get around 200k and 4x times median income.

"It would take a lot of research and work to discover what a "good district" is, while in western Europe you can just send your kids to school and not worry about it. Lots of states don't have any good districts at all." All of this is false, sorry. There are sites like greatschools.org where most public schools are rated. It is relatively easy to distinguish a good district from a bad one. And I don't believe you can send your kids to schools and not worry anywhere in the world, it is just a bad way to raise them. As about states not having any good districts.. Examples, please.

Health insurance certainly sucks, but 10k deductibles are not common at all. Insurance companies pay most of the time, if you are in network they really cannot refuse after the fact.

Salaries for software engineers in US are much higher than in most of Europe, and taxes are lower. Though it is probably not 2x.

- big data is overhyped

- potential benefits are likely smaller than you think (this is true for most new technologies)

BUT:

- he seems unaware about modern analysis tools and their power

- state of the art in machine learning has actually advanced a lot in the last 20 years

- as a result a lot of problems that were intractable back then are being solved (Jeopardy, Go)

- there are completely new problems (all the social stuff, huge recommender systems)

- big companies are not good at innovating

- outsourcing is MUCH harder than it seems, especially to Bangalore

The question of the size of the market is crucial. Small labor markets are very inefficient. This means that the number of qualified people is small enough, but the number of companies they can choose from is also small. It is hard to find a job when the number of companies hiring is probably less than 100.

I am sure it takes much less than "years" for any smart PhD in applied mathematics to learn most of data analysis tricks. It is not theoretical physics after all.

Say you need someone who knows a lot about Hadoop and Amazon EC and is also intimately familiar with most learning algorithms and has a PhD. You are having trouble finding the guy. You start crying about "the big data talent shortage".

And here is the problem. Most PhDs have no experience with Hadoop or Amazon EC. Some of them might know Java well enough.

Now, consider a smart guy with PhDwho knows Java and has done something parallel with it, working on real "dirty" data. He can pick up Hadoop in no time from your software engineers. He will learn to tweak and optimize in his time - it is domain specific and cannot be learned off the job.

Will he be hired? Probably not. But people will keep crying about shortage.