On entitlement, toxicity, and burnout in Open Source.
[Toxicity is] rude, disrespectful, or unreasonable language that is likely to make someone leave a discussion.
– Google, Project Jigsaw

I didn’t expect to learn something new from this paper.
I’d hoped it was obvious by now: there’s no room in tech for the brilliant jerk.
But the paper, “‘Did you miss my comments or what?’ Understanding Toxicity in Open Source Discussions,” taught me something new. They took a deep-dive into GitHub comments to name something I’d seen but never had a term for: “entitlement.”
The five flavors of toxicity
The authors lump toxic comments into five flavors—four I’ve seen before:
- 🤬 Insulting – Typing angry words at people.
- 😏 Arrogance – When a comment author forces their “clearly superior” views on others. A hallmark of many technical disagreements.
- 🤡 Unprofessional comments – Comments that make project members uncomfortable. Mostly unfunny attempts at humor that are inappropriate in a professional setting.
- 🧌 Trolling – The lowest form of toxicity. As Justice Potter Stewart quipped about trolling1, “I’ll know it when I see it.”
And one is new to me:
- 🆕 Entitlement – Pure PEBKAC fury. Comment authors act as if maintainers have violated a contract. They make unreasonable requests of the maintainers. They demand the software be different.
I’d seen entitled comments but never had a name for them.
“Entitlement” is a new term for me
Entitlement is commonly targeted at people, […] insulting them for not doing what they wanted them to do or do it fast enough.
– Understanding Toxicity in Open Source Discussions
The term is new, but the paper renders a familiar scene, “The author is usually visibly upset about not being able to use the tool, often complaining about wasted time.”
The situation is all-too-common and exhausting. And when it happens over-and-over, maintainers give up.
It made me wonder: why have I never seen “entitlement” in a code of conduct?
For example, the Contributor Covenant2 names all the flavors of toxicity from the paper—except “entitlement.”
Maybe “entitlement” is a new term for everyone
¯\_(ツ)_/¯
.
♻️ The entitlement-burnout cycle
complaints, questions, and requests for enhancement from users can feel like ‘a constant stream of negativity’
– Understanding Toxicity in Open Source Discussions
When maintainers make toxic comments, they’re often responding to entitled comments.
The cycle looks like this:
- Frustration – A user gets frustrated with the project
- Entitlement – Users start making demands of
maintainers
- They complain about the project not working how anyone would expect
- Or they complain about the maintainer not working fast enough.
- “wasted time”
- Insulting – Finally, this causes project members to snap—insulting the user
- Burnout – This interaction burns out project members and repels new users. The burnout withers the project and causes more users to get frustrated.
So, let’s do something about entitlement
[Toxicity] can increase the risk of projects becoming abandoned or unmaintained
– Understanding Toxicity in Open Source Discussions

The Open Source software powering the internet is chronically underfunded and understaffed.
We still refuse to learn one of the crtical lessons of heartbleed: maintainers need our support.
First, Open Source maintainers need money—give them money if they’ve written code critical for you or your company.
But maintainers also need mental space to function.
So, now that we have a term let’s do something about entitlement:
- Add it to your code of conduct.
- And say something when you see it happening.
Otherwise, at best, we’re all doomed to reimplement terrible versions
of OpenSSL and ImageMagick forever *shudder*
.
Thank you to Brennen, Kosta, and Željko for reading the early drafts of this blog. The remaining errors and dumb opinions are mine; all the invisible fixes are theirs.
To see posts by date, check out the archives
Paper
Review: “Did you miss my comments or what?” Toxicity in Open Source
Discussions
Posted
by
Tyler Cipriani
To see posts by date, check out the archives
Paper
Review: “Did you miss my comments or what?” Toxicity in Open Source
Discussions
Posted
by
Tyler Cipriani

There’s a scene in AMC’s “Breaking Bad” where Gail Boetticher explains to Walter White how to make the perfect cup of coffee. And it all sounds so plausible—there’s a perfect coffee, and science will magic it for us.
That whole idea, scene, and contraption are, of course, wrong.
But there are real ways to experiment your way towards a more perfect cup.
🗺️ The quest for good coffee
In 1957, a professor of food science at MIT forever changed what we think of as good coffee.
E.E. Lockhart posited that coffee flavor is the result of two variables:
- How much coffee you use
- How much of that coffee dissolves into the final cup (total dissolved solids—TDS%)
Lockhart surveyed a bunch of people to suss out the ideal range for these values, creating the “Coffee Brewing Control Chart,”—which is still in use today.1
And you can use Lockhart’s data to better your own brew.
🔬 Coffee science at home

When he was developing the Aeropress, Alan Adler was a frequent poster on the coffeegeek forums. There he shared the results of his experiments measuring coffee using a simple brix refractometer.
And, unfortunately for everyone in my immediate family—I own one of those, too!
🧪 An experiment: finding the ideal grind for the Hario v60
Over Christmas, I got a Hario v60 pour-over brewer. And I used science to zero-in on what I think is the perfect grind size.
Materials
- Hario V60 plastic dripper
- Baratza Virtuoso
- Bonavita electric kettle
- Escali Primo gram scale
- Ethiopia Refisa dry process from Ozo coffee
- Tap water—the miracle of modernity
Methods and Results
I tried to brew two cups of coffee the exact. same. way. Except for one variable: the grind.
Variable | Course grind | Fine grind |
---|---|---|
Grinder dial setting | 22 | 17 |
Water temperature | 95°C | 95°C |
Water amount | 320g | 320g |
Coffee used | 20g | 20g |
Coffee brewed | 277g | 271g |
TDS% | 1.4% | 1.7% |
Extract% | 20% | 23% |
This measured difference is obvious, but can I taste a difference?
Taste and preference
A widely used protocol for figuring out if you can discern a difference between two products is the triangle test.
In a triangle test, you present three cups of coffee: two are identical, one is different. The goal is to pick out the odd cup consistently (better than random change; i.e., 1/3).
So, I took my two coffees and split them into 3 cups:
- 3 cups: A, B, and C
- Cups A & C – fine grind (“17”)
- Cup B – course grind (“22”)
And, then I mixed up the cups and tried to pick the odd one out:
Result | Trial | Different cup | Cup I picked |
---|---|---|---|
✅ | 1 | B | B |
✅ | 2 | B | B |
❌ | 3 | B | A |
❌ | 4 | B | A |
✅ | 5 | B | B |
As dramatic as the chart above looks, picking the “different” cup was tricky. I encourage you to try it—it was a fun experiment.
In the end, I preferred the course grind—it seemed sweeter and fuller vs. the fine grind. The fine grind coffee was astringent: sharp and tannic.
🍕 Coffee cognition theory
The theory of pizza cognition tells us that an individual’s first and primary source of pizza … will become the pizza against which all others are judged.
– Sam Sifton, The New York Times
I prefer strong coffee.
But I also prefer a light roast, single-origin coffee.
Much of the science of coffee is about extraction. But the art of coffee is hundreds of other choices: light roast, dark roast, Ethiopian, Sumatran, dry process, honey process, “briping,” and any other outre preference folks would find criminal to omit.
So far there have been three waves of coffee in the United States:
- First wave – Instant coffee. Diner coffee. Folgers.
- Second wave – Dark roast. Peet’s/Starbucks.
- Third wave – light roast, single origin: Blue bottle/Stumptown.
What I consider “good coffee” is a product of when I started drinking coffee—smack in the middle of the third wave.
But there’s no perfect coffee, no matter what Gail Boetticher says.
In 2020, scientists recreated Lockhart’s experiment—the coffee chart holds up! But cluster analysis holds some new insights: https://ift.onlinelibrary.wiley.com/doi/abs/10.1111/1750-3841.15561↩︎
To see posts by date, check out the archives
To see posts by date, check out the archives