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
Job listings with over 50% bullet points significantly reduce female applicants
“If you go above 50% bulleted content in a listing, you quickly reduce the proportion of women who are likely to apply for the job, statistically.”
Kieran Snyder Mar 18, 2016 ▶ 12:09 Using AI to Predict the Performance of Text // Kieran Snyder, Textio (Data Driven NYC / FirstMark)
Insight
Diversity of an applicant pool strongly predicts how quickly jobs fill
“It turns out that the percentage of underrepresented groups who apply to a job is a very good predictor of how quickly the role will fill”
Kieran Snyder Mar 18, 2016 ▶ 9:07 Using AI to Predict the Performance of Text // Kieran Snyder, Textio (Data Driven NYC / FirstMark)
Assertion Supported
Corporate jargon in job postings disproportionately deters applicants of color
“Like some of that corporate jargon, the words like synergy and stakeholders and ROI. It turns out everybody hates them, but underrepresented groups, especially people of color, hate them even more. So nobody is as likely to apply when you include that language…”
Kieran Snyder Mar 18, 2016 ▶ 17:37 Using AI to Predict the Performance of Text // Kieran Snyder, Textio (Data Driven NYC / FirstMark)
Insight
Machine learning models often predict outcomes without explaining why they happen
“The models that you can create can often tell you what might happen, but they can't always tell you why.”
Kieran Snyder Mar 18, 2016 ▶ 1:04 Using AI to Predict the Performance of Text // Kieran Snyder, Textio (Data Driven NYC / FirstMark)
Insight
Text is the primary daily volume output of almost every business
“Whatever business you are in, whether you're making software, or you're making hamburgers, or you're making playground equipment, The thing you're actually making the most of every day at work is text, ah, almost certainly.”
Kieran Snyder Mar 18, 2016 ▶ 1:18 Using AI to Predict the Performance of Text // Kieran Snyder, Textio (Data Driven NYC / FirstMark)
Assertion Not checkable as stated
Over a third of recruited candidates abandon applications after reading the listing
“Over a third of people that you're reaching out to who are looking for jobs walk away when they see your job listing.”
Kieran Snyder Mar 18, 2016 ▶ 3:16 Using AI to Predict the Performance of Text // Kieran Snyder, Textio (Data Driven NYC / FirstMark)
Assertion Not checkable as stated
Job seekers scan listings for only a couple seconds before deciding
“Turns out people scan a listing for only a couple seconds before deciding whether to engage.”
Kieran Snyder Mar 18, 2016 ▶ 3:07 Using AI to Predict the Performance of Text // Kieran Snyder, Textio (Data Driven NYC / FirstMark)
Disclosure
Textio collected 15 million job listings tagged with performance outcome metrics
“At this point we have about fifteen million job listings across industries and geographies that are tagged with, in many cases, very rich outcomes.”
Kieran Snyder Mar 18, 2016 ▶ 4:39 Using AI to Predict the Performance of Text // Kieran Snyder, Textio (Data Driven NYC / FirstMark)
Assertion Partly supported
The average corporate cost per hire is approximately $2,000
“Considering your average cost per hire is about 2000 dollars, you're saving a fairly substantial amount”
Kieran Snyder Mar 18, 2016 ▶ 17:03 Using AI to Predict the Performance of Text // Kieran Snyder, Textio (Data Driven NYC / FirstMark)
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