Perfect example of a base rate fallacy - https://en.wikipedia.org/wiki/Base_rate_fallacy
What percentage of GitHub activity goes to GitHub repos with less than 2 stars? I would guess it's close to the same number.
What percentage of GitHub activity goes to GitHub repos with less than 2 stars? I would guess it's close to the same number.
Interestingly, there are 21.37b commits in GitHub, implying 104 additions per commit. Per the dashboard, Claude is linked to 20.81m commits and 50.44b additions - or 2,424 additions/commit. So additions for Claude-linked repos is higher, and it's actually higher for repos with 0-1 stars (2,568 additions/commit for Claude, 91 for all GitHub). None of this is a smoking gun but aligns with the intuition that Claude is producing enormous amounts of code. TBD whether it is 'adding value'.
Would be appreciative of anyone who verifies/invalidates this. https://play.clickhouse.com/ https://ghe.clickhouse.tech/#clickhouse-demo-access
This likely tripled the amount of stars I have.
workers on the management track
(But I don't use AI on them.)
stars : uniq(k)
1 : 14946505
10 : 1196622
100 : 213026
1000 : 28944
10000 : 1847
100000 : 20
1 : 14946505
10 : 1196622
100 : 213026
1000 : 28944
10000 : 1847
100000 : 100
- visibility
- popularity (technical, domain, persona)
- genuine utility
- novelty
...
There are also plenty of super high utility repos that are widely used (often indirectly), but don't have a lot of stars, or even a meagre amount.
Also there is the issue of star != star, because it's not granular.
It's similar to upvotes on general social media platforms. Everyone likes cute cats doing funny things somewhat, but only few people appreciate something that's more niche but way more impactful, useful or entertaining (or requires some effort to consume), but those who do, value it very highly. But the same person might use the same score (single upvote) for a cat video and a video that they value much higher.
If anything, the fact that this is what he arrived at, even when starting with the opposite position, is proof of the validity of this result.
The problem is that this title is editorialized, and the fact is cherry-picked. Why not =0? Why not >1000? This is just a dashboard, it highlights "Interesting Observations", but stars statistics is not there.
Most people figure out this scam very early in life, but some cling to terrible jobs for unfathomable reasons. =3
The answer to such questions is always that, given their circumstances, they have no realistic choice not to.
This is very obvious, and it's frustrating to continually see people pretend otherwise.
If folks expect someone to solve problems for them, than 100% people end up unhappy. The old idea of loyalty buying a 30 year career with vertical movement died sometime in the 1990s.
Ikigai chart will help narrow down why people are unhappy:
https://stevelegler.com/2019/02/16/ikigai-a-four-circle-mode...
Even if folks are not thinking about doing a project, I still highly recommend this crash course in small business contracts
https://www.youtube.com/watch?v=jVkLVRt6c1U
Rule #24: The lawyers Strategic Truth is to never lie, but also avoid voluntarily disclosing information that may help opponents.
Best of luck =3
In this type of situation, the fundamental issue is that making progress depends on many people acting in unison to increase their bargaining power, which is (a) hard to arrange even if everyone who acted this way would benefit, and (b) actually may be detrimental to some people (usually the high performers).
In my observations it is usually conditioned fear, personal debt-driven risk aversion, and or failure to even ask if the department above you is really necessary. These days, it is almost always easier to go to another firm if you want a promotion. =3
https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect#...
> In popular culture, the Dunning–Kruger effect is sometimes misunderstood as claiming that people with low intelligence are generally overconfident, instead of denoting specific overconfidence of people unskilled at particular areas.
Dunning-Kruger has also been discredited with suggestion they may have been over confident themselves:
The Dunning-Kruger Effect Is Probably Not Real (2020) https://www.mcgill.ca/oss/article/critical-thinking/dunning-...
Debunking the Dunning‑Kruger effect – the least skilled people know how much they don’t know, but everyone thinks they are better than average (2023) https://theconversation.com/debunking-the-dunning-kruger-eff... the Dunning‑Kruger effect – the least skilled people know how much they don’t know, but everyone thinks they are better than average
The study conclusion inferred the skills needed to be effective at some task, are the same skills needed to correctly evaluate if you are actually proficient at the same tasks.
Or put another way, the <5% population of narcissists by their nature become evasive when their egos are perceived as threatened. Thus, often will pose a challenge in a team setting, as compulsive lying or LLM turd-polishing is orthogonal to most real world tasks.
People are not as unique as they like to believe, and spotting problems is trivial after you meet around 3000 people. Best to avoid the nonsense, and get outside to enjoy life. Have a great day =3
If you read your own reference (not the picture, but where you took it from on Wikipedia) really really carefully, you might be able to tell why it so perfectly applies to you
The person with little knowledge overestimates they're capability, and the person which actually knows how complicated [the thing] is , usually isn't as confident they mastered it.
Your take on that makes absolutely no sense
But the claim above was that having low confidence was correlated to higher skill. Ie, skill and confidence are anti correlated. The chart does not show that. The lowest data point for confidence is the point on the left of the chart. This is also the data point corresponding to people who have the least competence. Having low confidence is not evidence that you’re secretly an expert. Confidence and competence are still positively correlated according to that chart.
The Dunning-Kruger effect is not so strong that there are scores of novices convinced they are experts in a field. But in your case, I admit the data may not tell the full story.
"Baloney Detection Kit"
https://www.youtube.com/watch?v=aNSHZG9blQQ
Best regards =3
It's good to raise people's expectations of themselves
The study conclusion inferred the skills needed to be effective at some task, are the same skills needed to correctly evaluate if you are actually proficient at the same tasks.
https://arxiv.org/abs/2505.02151
If the data infers another explanation is more applicable, than I'd be interested in the primary papers/studies the editorialized opinion seems to have omitted. =3
I mean, it’s an indicator. Just not a definitive—or individually sufficient—one.
in otherwords, plot the percentage or average metric and not the absolute metric.
e.g. number of lotto winners per thousand people living in that grid, percentage of starred repos as a percentage of all repos, per capita alcohol consumption, average screen-time etc.
Edit: unless ofcourse the point of the heatmap is to show the population distribution itself. In which case the metric would be number of people per square kilometer or some such.
Personally I think comparing github stars is always going to be a fraught metric.
If the answer wasn't in hundreds of request per seconds, i wasn't interested in job.
I found job at ad tech companies, pay wasn't any good but the challenges were immense.
Most people write code, which will hardly be run by other people or even receive any customers.
Value and use are not always synonymous.