3 ms·
I'm not surprised. People are different. I've been part of studies throughout the game industry, the highest performing engineering teams are usually males of
by norwalkbear 4y ago
I'm not surprised.
People are different.
I've been part of studies throughout the game industry, the highest performing engineering teams are usually males of similar cultural background.
But it's so unpc, we avoid hiring them directly. We usually hire them thru their consulting groups for the very difficult engine tasks
- karpierz 4y agoWhere did you get that from the article? It's not saying "women are different than men", it's saying "journalists treat female managers less professionally than male ones".
- pc86 4y agoAnd also that "journalists treat female executives at established companies more critically than female founders" which is an interesting and perhaps somewhat counterintuitive point.
- yrgulation 4y agoProbably wanted to push for this: “males of similar cultural background”. Cant even begin to imagine the toxicity of that place.
- muglug 4y agoHaving spent 20 years writing code, I have no idea how to measure “performance”. Is it “lines of code written”? Is it “technical debt addressed”? Is it a measure of how many engineers grew in those roles? Does it measure how many engineers burned out after a year? Does it measure projects with reasonable starting estimates? Does it focus only on the products that sold well, or does it also include games that bombed?
- norwalkbear 4y agoWhen it's industry specific it's easier to measure. Game engines are very specialized beasts that have a very high degree of math, physics, and algos for shortcuts. Then getting it working on very specific hardware.
- magicalist 4y ago> easier to measure Still forgot to mention how it's measured? And presumably if these were studies they were published?
- hourago 4y ago> the highest performing engineering teams are usually males of similar cultural background. So, in an industry that 95% of employees are men you find that the top performing are men? I recommend that you take a look at Bayes theorem. It explains your bias and how you are misinterpreting your observation. - https://en.wikipedia.org/wiki/Bayes%27_theorem https://en.wikipedia.org/wiki/Bayes%27_theorem