"I agree there is a problem, but is it ever frustrating having to tolerate completely fallacious statistics and bogus metrics. That sets the conversation back."
The statistics you cite are quite frankly bad statistics. You could have written the following and it would have been just as meaningless:
* "716 humans who left industry X"
* "I have collected stories from 716 other humans who have left industry X"
* "Of the 716 humans surveyed, 465 are not working today."
* "Two-hundred-fifty-one are employed in non-Industry X jobs, and 45 of those are running their own companies. A whopping 625 humans say they have no plans to return to Industry X
Which strongly implies "left the industry", not "moving to this job" or "that job". 2/3s of them aren't working at all, not "promoted to something else"
When you eliminate the nouns that allow our own biases to fill in the blanks and arrive at our own strong implications, it's quickly obvious that those statistics mean absolutely diddly-squat without additional related figures (like base rates) that allow us to perform an informed comparison.
"I agree there is a problem, but is it ever frustrating having to tolerate completely fallacious statistics and bogus metrics. That sets the conversation back."
The statistics you cite are quite frankly bad statistics. You could have written the following and it would have been just as meaningless:
* "716 humans who left industry X" * "I have collected stories from 716 other humans who have left industry X" * "Of the 716 humans surveyed, 465 are not working today." * "Two-hundred-fifty-one are employed in non-Industry X jobs, and 45 of those are running their own companies. A whopping 625 humans say they have no plans to return to Industry X Which strongly implies "left the industry", not "moving to this job" or "that job". 2/3s of them aren't working at all, not "promoted to something else"
When you eliminate the nouns that allow our own biases to fill in the blanks and arrive at our own strong implications, it's quickly obvious that those statistics mean absolutely diddly-squat without additional related figures (like base rates) that allow us to perform an informed comparison.