The Ledger

Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.

clear all ✕

why aren't all 9 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable

Assertion Not checkable as stated
Between 30% and 50% of first-year hires fail
“30 to 50% of first year hires fail.”
Frida Polli Feb 3, 2017 ▶ 3:03 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)
Assertion Not checkable as stated
Neuroscience games lack inherent gender or ethnic bias
“Unlike some of the other data that people are using to predict fit in people, the games were generally, are generally not thought to have any inherent gender or ethnic bias, so they're not picking up on that if the training sample is biased.”
Frida Polli Feb 3, 2017 ▶ 6:08 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)
Assertion Supported
Nonverbal neuroscience games avoid cultural biases found in questionnaires
“And we assess 90 different cognitive, emotional, and personality traits, and again, these are all nonverbal, ah, games, so they're not culturally anchored the way, you know, questionnaires or other things might be.”
Frida Polli Feb 3, 2017 ▶ 5:41 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)
Assertion Not checkable as stated
Most recruitment startups simply apply machine learning to resumes
“So there are a handful of startups that are starting to do this type of work in the recruiting field. Many of them are focusing on the resume as a field, as a source of data.”
Frida Polli Feb 3, 2017 ▶ 12:28 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)
Assertion Not checkable as stated
Behavioral data shows VCs chase high rewards while hedge fund managers hedge
“VCs are very motivated by that sort of high reward stuff. Versus the head fund managers, they're hedging, right? So of course they're going to put in effort for a variety of different things, including low reward situations.”
Frida Polli Feb 3, 2017 ▶ 20:54 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)
Assertion Not checkable as stated
Assessments may measure 90 traits, but only 10 determine job fit
“The second thing I would say to that is we measure 90 different traits, right? Of the things that are end up being important, it's usually maybe 10. Maybe, maybe fewer than that. The remaining 80 are left to vary tremendously, right?”
Frida Polli Feb 3, 2017 ▶ 24:36 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)
Assertion Not checkable as stated
The average recruiter receives 250 applicants per job posting
“The average recruiter gets 250 applicants for every job that they post.”
Frida Polli Feb 3, 2017 ▶ 1:58 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)
Assertion Not checkable as stated
Recruiters manually scan resumes for an average of six seconds
“If it's a person doing the scanning, they'll on average scan it for six seconds”
Frida Polli Feb 3, 2017 ▶ 2:06 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)
Assertion Partly supported
The most commonly used career instrument, Myers-Briggs, is 80 years old
“The most commonly used instrument is the Myers-Briggs and it is almost a century old at this point. It's 80 years old.”
Frida Polli Feb 3, 2017 ▶ 17:08 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)
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