3 ms·
Definitely, it’s harder to use. But I’d rather not do analysis than do wrong analysis. If I can’t measure poverty correctly, then using a simple number isn’t u
by prepend 3y ago
Definitely, it’s harder to use. But I’d rather not do analysis than do wrong analysis.
If I can’t measure poverty correctly, then using a simple number isn’t useful to generalize and make conclusions. And I certainly wouldn’t want to target interventions.
There’s a reason why it’s complicated.
- giraffe_lady 3y ago> If I can’t measure poverty correctly, then using a simple number isn’t useful to generalize Why not? It can be good enough to identify a pattern to focus more precise study on. "I'd rather not understand this at all if we can't have a perfect understanding" is a harsh and anti-science stance on this imo.
- prepend 3y agoMore like “I’d rather have minimally acceptable understanding than incorrect and harmful understanding.” The reason is there are many confounding variables so measuring poverty incorrectly and reaching a wrong conclusion can focus resources toward people who don’t need it (eg, single people making half the median wage who are not in poverty). I think sometimes you don’t have a choice. But in this case, there is a more accurate measure to use, so not using it makes conclusions less helpful. I think claiming things as “anti-science” is a gatekeeping function that is counterproductive. Especially when people don’t understand statistical significance and are trying to make conclusions that aren’t accurate. I don’t think things are “anti-science” or “pro-science” as these are imprecise and meaningless statements. I’m not sure what you mean by saying anti-science. But I think it’s not logical to assume something that is minimally effective is striving for perfection and something that isn’t significant is good enough.