Thanks Karolina, this is great! It's nice to see a balanced perspective considering the pros and cons of RCTs. It can be very frustrating seeing RCTs treated as either a silver bullet or a useless piece of trash. They're a tool in a toolbox like every other kind of research, and in my opinion, best used in conjunction with broader foundational research approaches like qualitative data collection, case studies, descriptive or correlational studies, and so on. I'll definitely be bookmarking this to refer back to.
That's a good idea and actually not too hard to implement in the grand scheme of things. It's not something that will get done right away, but I can add it to the list! And if anyone reading would like to collaborate to produce that, please get in touch!
I think you're right, that one does seem to be a bit misleading... thank you for calling my attention to that. It looks like an eccentricity in the NHANES data. While it has things like cakes and pies with eggs in them as one type of food respondents could report, it also allowed them to report foods in terms of their constituent ingredients. So you could report a ham and cheese sandwich as a ham and cheese sandwich OR as sliced ham, sliced cheese, mayo, and bread. Because we restricted our analysis to just the primary animal product in each report, raw eggs are a bit of an odd case...the specific foods in that category are "Egg, yolk only, raw", "Egg, white only, raw", and "Egg drop soup." It's actually the soup that's the problem, because the ingredient list has it categorized as its own sole ingredient (egg drop soup, made up 100% of egg drop soup!). That's definitely a problem since it ended up assigning the entire weight of a serving of soup to the egg. I think the best option is probably just to remove raw egg as a category entirely, but I'll double-check and consult the rest of the team first.
Thanks for the feedback!
Thanks for your comment. If you want to use the objective term, "days of life" is most accurate -- we used the number of animals affected, and multiplied by their lifespans, accounting for different causes of mortality. You could certainly argue we editorialized a bit by referring to any day of life for a farmed animal as a day of suffering. I agree that there are differences in the extent of that suffering between species and circumstances, but in the interest of keeping the degrees of uncertainty as low as possible (see my comment to sawyer), we chose to say a day is a day is a day. Given that the numbers are massively dominated by factory farmed chickens and aquacultured fish, I feel pretty comfortable referring to it as days of suffering.
Thanks, sawyer! We haven't done that ourselves for exactly the reasons you mentioned--there were already many degrees of uncertainty in the analysis just based on spotty data availability, so we felt that adding something with that amount of subjectivity would reduce the overall utility of the analysis because some people would agree with our decisions and some wouldn't. But the lists within species may work as a simple proxy, and the data and code are available to anyone with more investment who would like to make that adjustment themselves. If you're thinking about doing it and would like to chat, feel free to reach out! It's my first name @ faunalytics.org.
For those interested, Faunalytics now has some data to speak to some of these points. Our report (https://faunalytics.org/covid-19-poll/) covers public understanding of the animal origins of COVID-19, reaction to an argument presenting the connection between disease and animal farming, and support for legislative measures banning or restricting types of animal farming that are linked to zoonotic disease.