I have no historical stake in this argument (i.e. I was not a part of the Nix community at the time that this controversy occurred). However, I do care very deeply about data and the ways in which it is presented.
Apologies for any clipping of quotes; I am trying to be concise. Also from reading the linked sources, MIC is “military industrial complex”.
If I understand your argument correctly, you are inferring from the 234 signatories to these letters (232 to the first, 2 to the second) that “over 99% of community… is against MICs”. However, the linked first letter specifically disavows that notion. It states:
Please understand that agreeing and signing this open letter:
Is not an endorsement of a specific political allegiance. Does not mean you are personally against the Military Industrial Complex. Does not take in account past or future decisions and opinions.
Signing this open letter only means that:
You do not want to see the NixOS community become vehicle for advertising the Military Industrial Complex.
Additionally, 99% of the 234 people who were willing to sign 2 specific open letters is also not “numerically” 99% of the community. For comparison, there were 2,290 respondents to the Nix Community Survey 2024 and 4,619 people listed in the nixpkgs maintainer list (builtins.length (builtins.attrNames (import ./maintainer-list.nix))
). I am unclear on what percentage of the Nix or NixOS community these measures can capture, but even as a conservative measure this is already 10x to 20x more people who have shown themselves willing to engage as part of the Nix community, yet did not engage with these letters.
I acknowledge that most research is based on statistical inference from smaller samples, so it isn’t only a question of numbers. However, such inferences are limited by how a specific methodology may or may not be able to control for factors such as selection bias. An open letter signatory process is poorly equipped to provide reliable data on proportionality because it is only designed to collect affirmative data.