In today’s episode, we’re diving into a mysterious and dramatic decision-making stat that’s been popping up everywhere lately.

But when you try to track it down, no one actually knows where it comes from. Every source just says it comes from various sources—or cites a source that points to… more unnamed sources, in an endless loop.

So what’s the truth?

We’ll break down the citation loop that keeps this number alive, expose the lack of a real source, and reveal how even major publications like Harvard Business Review, Forbes, and PBS repeated it without fact-checking.

Join me as I unpack what we know (and don’t know) about decision-making, how misinformation spreads even in places we should be able to trust, and why we need more good people in research to answer questions like this.

Referenced:

• 2015 - Roberts Wesleyan University Article
• 2016 - The Wall Street Journal
• 2018 - Psychology Today
• 2018 - National Library of Medicine
• 2021 - PBS
• 2022 - CNN Health
• 2023 - Harvard Business Review
• 2023 - Forbes
• Cornell University Study
• OREO Study
• Noom Study
• Microsoft Ad

In today’s episode, I’m tackling a viral health claim that sounds simple—but isn’t: that doing 10 squats every 45 minutes during an 8.5-hour period of sitting is better for blood sugar regulation than taking a 30-minute walk.

Is that what the research actually says? Not quite.

We’ll break down the study’s methodology, expose the grammatical ambiguity that helped this misinformation spread, and reveal how even AI initially misread the study.

Plus, you’ll learn why you should make reading the methods section of research your superpower, how bad science communication erodes public trust, and why representation in research matters more than you think.

Join me as I unpack what this study really found, challenge misleading claims, and share practical tips for spotting the next viral “science-backed” myth before it fools you.

Referenced:

• The Study
• The Video on Instagram
• The Tweet
• The Newsweek Article

In today’s episode, I’m tackling the bold, research-backed claim that AI produces lower carbon emissions for writing and drawing than humans. We’ll break down the study’s methodology, question its framing, and uncover the glaring omissions that make its conclusions feel more like a pro-AI pitch than neutral science. Plus, you’ll learn what Mark Twain has to do with all of this and why apples-to-oranges carbon calculations can skew the bigger picture.

Join me as I unpack the study’s findings, explore why bias in research matters, and share tips for critically evaluating the next viral “science-backed” claim you encounter.

Referenced:

• Scientific Reports article
• The Writer Magazine
• EPA’s Greenhouse Gas Equivalencies Calculator
• The Nature Conservancy’s footprint calculator