With photography, you don’t have that control at all because traditionally photography was about prints. Every printer (regardless of kind) had to be profiled and you needed an explicit ICC conversion process for it to work. If you are solely publishing photographs digitally and have no intention of printing, you actually could adopt a film workflow and it would be just fine.

In short, film production doesn’t actually need the added complexity of ICC profiling. They could adopt it, but it’s not strictly necessary. Trouble comes when people don’t understand the fundamental reason why gamma correction and different primary spaces exist in the first place.

Regardless of what you use for a linearizing function, the more important thing is that you use the correct encoding function afterward, so that you don’t introduce any additional gamma correction. For example, it was common to use a simple squaring function for speed. This gives fairly good results as long as you apply the square root function afterward to restore the original gamma correction. It doesn’t matter if the source is 2.2 or 2.4 gamma encoded or something else, that correction will be preserved. The blending post-linearization will be less accurate, but much better than not linearizing at all.

The early LCDs were poor because of limitations of the backlight’s spectrum. Once LED backlights were introduced, this was no longer a problem.

It’s not just a matter of introducing a correction factor (although that exists, see Judd-Vos) because the solution is more complex than that. The practical take away is that color matching cannot just involve comparing a narrow point in isolation but also needs to have a baseline of controlled surround and specular reflections in addition to understanding the nature of the perceived color (reflective, emissive, narrowband, wideband, etc.).