I’m going to horribly oversimply this. For example. Say I am wearing a shirt a cheap one for Wal-Mart.
This shirt was produced in a sweat shop. That sweat shop has .0005 deaths per day. Thus by wearing this shirt and supporting the mechanisms that brought it to me. I have a killcount for today a number substantially smaller then .0005 and obviously there’s a tonne of subjectivity on what that number might be.
Now include the dye factory that made the shirt green, the shoes I am wearing, the bus I am riding in, the coffee I drink. All these luxuries and that number may go up a little.
I am wondering if this is somthing that is being considered anywhere is somone building a calculation to determine our daily kill counts.
I’m sure most of us probably don’t what to know what ours might be, but knowing what parts of our daily lives have the highest values we might work harder to change for the better.
https://en.m.wikipedia.org/wiki/Micromort
Micromorts is an adjacent topic and has the data you’re looking for, just not the grouping. Somewhere to start if you’re curious.
This could be used. Though the examples here here are more oriented to risk of death for doing X. Micromorts could probably be used in determining values I am thinking of.
I am terrible at math so excuse the terrible example.
Let’s say working in a sweatshop in Vietnam has a micromort of .6 and the resouce you are calculating uses up to one third of these shops. Then you’d be adding .3 to your count.
We can say 1000 micromorts is one probable death.