Biased Data, Improper Research…And They Still Demand More H-1Bs
In November, Michelle Malkin discussed this idea on her website, in a piece titled "The Myth of H-1B Job Creation". Michelle is an author and Senior Editor for the Conservative Review.
In her article, Michelle calls out big tech and politicians for their nonsensical claim that hiring H-1B workers from foreign countries somehow fuels American job growth.
Bill Gates cited a National Foundation for American Policy study when testifying before Congress in 2011, that for every H-1B holder that technology companies hire, 5 additional U.S. jobs are created around that person. A source is not cited on the transcript, but this may be the source: H-1B Visas and Job Creation: NFAP Policy Brief » March 2008
The Wall Street Journal called out Bill Gates for his misleading testimony because the data set of the NFAF study “was confined to S&P 500 tech companies which ‘excludes the leading users' of H-1B visas—offshore outsourcing companies from India such as Infosys, Wipro and Tata.”
In addition, the WSJ found that the study showed a correlation, not a causation. Meaning the visas could indicate broader hiring at the company, and weren't necessarily the cause of it.
Mark Zuckerberg and the U.S. Chamber of Commerce later cited another NFAP study by Madeline Zavodny and asserted that 2.62 more jobs are created for U.S.-born workers for each foreign-born worker in the U.S. with a U.S. STEM graduate degree.
That study "initially examined data from the years 2000 to 2010. Zavodny hypothesized that states with more foreign-born workers would have higher rates of employment among native-born Americans. Initially, she was unable to find a significant effect of foreign-born workers on U.S. jobs."
"...Zavodny revealed that when she showed her initial results to the study sponsor, the backers came up with the idea of discarding the last three years of data — ostensibly to eliminate the effects of the economic recession — and trying again."
The study was released in 2011, yet the data stops at 2007. There were at least 3 more years of data available that were excluded.
Discarding data to produce a result you want? That's not science. That's corruption.
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