News travels in academia much faster than papers get published.
At a dinner last month, I heard the familiar phrasing again: "Did you know? Academician So-and-so and that Distinguished Young Scholar are old partners—they're really tight, and their labs collaborate all the time."
The person saying it sounded certain, and the person hearing it nodded repeatedly. Then the sentence would keep spreading through dinners, group chats, and tea breaks between sessions, gaining a bit more detail with every retelling.
Here's the question:Is it true?
I asked a question that might have been a bit of a downer: "Is there any evidence?" The other person was taken aback for a moment: "Everyone says so."
"Everyone says so" is probably the least reliable data source in the history of human information. Fortunately, these days the cost of verifying an academic rumor is so low that it takes less than the time of a meal—
Step one: hear the claim. "So-and-so and so-and-so are old partners"—don't rush to believe it, and don't rush to spread it.
Step two: verify with one click. Open MuchSci's Talent Profile and use the Two-Person Collaboration Baseline Analysis to check the public relationship between these two people. The whole process takes just a few clicks.
Step three: draw a conclusion by tier. Verification results have only four tiers—there is no fifth answer:
· Verified direct collaboration—there is public evidence, the "old partners" claim holds, so feel free to cite it;
· Public relationship exists—there is a public connection but collaboration is not proven, so the claim must be downgraded to "they have crossed paths";
· No direct evidence found—no supporting evidence can be found in public data; it's best not to spread it, or to note that it is "unverified";
· Unable to determine—the data is insufficient for a conclusion. "I don't know" is also an honest answer.
I checked on the spot that day. The result was "a public relationship exists but collaboration is not proven"—they did appear together in a public project, but the dramatic description of them as "old partners who are really tight" is not supported by public data.
I shared the result around the table, and everyone laughed and said that from now on, before passing on a claim, they should run it through this first.
In fact, broadly speaking, this is a matter of information literacy:Before relaying claims from academic circles, let public data vet them first. Every verified relationship has an evidence chain, and there are no gray areas between the four tiers—this is exactly what makes it more reliable than "hearsay."