flown-the-coop said:DannyDuberstein said:
I'll also say this as a finance executive that has had to move teams/roles out of the US and constantly works with teams outside of the US - our Mexico teams run absolute circles around these guys. I absolutely will not move work to India. They are useless. From what I have gathered, it's a low IQ society propped up by fake education.
As a finance executive you know the bolded is not true or you have been outsourcing to ******ed Indians. Like any society, but in particular one consisting of over 1 billion people who most all lived in squalor and poverty (by western standards) until the last 30 years, you will have some misses. Also keep in mind that the "brain trust" has been methodically exported since the 1900s and exponentially in the last 40-50 years, and its logical the remaining workforce is subpar compared to 30 years ago when business process outsourcing started to really cook.
But it's not a low IQ society.
I agree with you.
People keep throwing out this IQ thing a lot. I've seen this on twitter also. Lynn-Becker, possibly with a hidden agenda, created a dataset with IQ being 78 and now every racist in town repeats it.
Here's another dataset
https://worldpopulationreview.com/country-rankings/average-iq-by-country
India: 98.44
USA: 101.04
By this data, we aren't that much above Ramesh. Are we gloating about less than 3 points? We are even less than Iran at 104.8.
I asked AI about Lynn-Becker. Looks like they took a few of those numbers out of their rear orifices.
Quote:
Major Scientific Critiques and Flaws
The scientific community heavily rejects the Lynn-Becker methodology for several critical reasons:
- Plausibility Errors: An IQ score below 70 generally denotes clinical cognitive impairment. The Lynn-Becker dataset claims countries like Sierra Leone or Nicaragua have average IQs of 45 and 52 respectively. Critics note it is sociologically impossible for a functioning society to exist if the average citizen requires full-time disability support. [1, 2, 3]
- Severe Sampling Bias: Instead of rigorous, representative testing, their data frequently relied on tiny, highly skewed samples. For example, their national IQ estimate for one African nation was calculated using a sample of just a few dozen malnourished, illiterate child refugees. In Nicaragua, their score was pulled from a study tracking children specifically because they suffered from neurodevelopment-depressing pesticide exposure. [1, 2, 3]
- Imputation/Guesswork: For over 70 countries where no IQ studies existed, Lynn and Becker simply "imputed" (guessed) the numbers by averaging the scores of geographically or ethnically neighboring nations. [1, 2, 3]
- Ignoring Environmental Factors: The dataset treats IQ as a fixed genetic trait. However, independent re-analyses of their data show that differences disappear or shift dramatically when accounting for differences in health care, nutrition, economic stability, and access to formal education. Standardized test data (like PISA or TIMSS) captures educational infrastructure, not biological potential. [1, 2]
