Interlude: Asymptotic Mastery, Study Participants, and Suspiciously Recent

I have a confession. Sometimes I struggle to think of myself as an expert.

At first, I wondered if I had this struggle because of the imposter phenomenon (an alternative to "imposter syndrome," which often carries a negative or ​clinical connotation​). Early in my career, the imposter phenomenon was definitely at play. But now, I think my struggle is rooted in something else.

So I've been thinking: how does someone achieve mastery of a subject to become an expert? More importantly, can anyone achieve true mastery of an evolving subject like language (or a scientific field)?

The more I sit with these questions, the more I think that mastery is asymptotic. In case you're not a math nerd like me, an ​asymptote​ is a line that continuously approaches a specific value as a variable tends toward a limit, often infinity, without ever actually reaching it. In other words, as you change the variable (expand your skills), the line gets closer and closer to the desired result (true mastery) but never actually reaches it.

That analogy captures my thoughts on mastery well. No matter how many skills you learn, mastery is not an endpoint to attain. Instead, it's an aspiration to motivate you to keep learning, practicing, and growing your skills.

So perhaps mastery is not an end goal, but rather a mindset. One that invites all of us to stay curious, open, and humble—no matter how far along we are on the asymptotic curve.

Now onto this week's round-up...

Round-up

From My Desk

​Why “Subjects” Is Harmful Language in Medical Research​
A single word can change how we view people who participate in medical research. One word that is particularly troublesome in medical research is the word “subjects.” In this video, I share why this word is a problem and what words you can use instead to show respect, empathy, compassion, and kindness to people to take part in medical research.

Upcoming

​Modern Authors Tools and Workflow​ – AMWA-MAC Annual Conference
During this panel discussion, I'll join three medical writers in examining how medical writing teams are managing global, technology-driven authoring and review workflows. We'll discuss ​effective collaboration​ across time zones, smart integration of writing and review tools, version control and audit readiness, responsible use of AI, and what the next 5 to 10 years may hold for medical writing workflows.

Reading

How recent is recent? Retrospective analysis of suspiciously timeless citations​
"Our investigation confirms what many readers have long suspected, but none have dared to quantify: in the land of biomedical publishing, 'recent' is less a measure of time than a narrative device. With a mean citation lag of 5.5 years and a median of 4, the average 'recent' reference is just about old enough to have survived two guideline updates and a systematic review debunking its relevance. Our findings align with longstanding concerns over ​vague​ or ​imprecise​ terminology in scientific writing..."

​Why “Ta-Da Lists” Might Be the Most Motivating Productivity Hack Ever
“The ta-da list is basically a way to take inventory of all your accomplishments. Instead of writing things down that you need to do, it’s a list of the things you’ve already done. (You’re saying a congratulatory, “ta-da!’ Get it?) They’re a complement to to-do lists, and strangely motivating.”

​Rising Publication Costs Strain Researchers​
"These high costs...can be barriers for early career scientists and those from institutions with less resources and funding. . .open access models create inequities. . .[and] research funding is a finite resource."

Thank you so much for reading.

Warmly,

Crystal

Crystal Herron, PhD, ELS(D), CMPP

Crystal is an editor, educator, coach, and speaker who helps scientists and clinicians communicate with clear, concise, and compelling writing. You can follow her on LinkedIn.

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Interlude: Consistent Practice, "Harmless" Phrases, and Not Disclosing AI Use

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Interlude: Caring for Readers, Meetings with a Point, and Sounding Like AI