My focus is more so on measuring a non-changeable aspect of individuals. Education can be exchanged for another outcome and it would be the same issue. I just used education as an example
This is more so a critique of what we are trying to intervene on when conducting research. Especially in health research where interventions/treatments/policies are frequent
Say we were to look at the impact of gender on depression rates
Are we really studying gender or are we studying sexism?
While socially constructed, we cannot change someone’s gender with an intervention or treatment
Also, the person’s identity isn’t the problem. It’s our society’s response to these identities that must be changed
We can change a populations overall education level with more access to education and more quality education
We can implement policies to better treat depression
But, going back to fundamental causes, racism is essentially what needs to be treated. Sexism is what needs to be treated. Social stratification is the issue
I hope I understood your question
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The use of randomized controlled trials (RCTs) to study the impact of specific interventions, has over the last decade become a dominant methodology in development microeconomics
However, some argue that socioeconomic RCTs do not test hypothesis rooted in theory and ignore mechanisms of causality
For example,
"In 2006, approximately 1,300 men and women were tested for HIV. They were then offered financial incentives of random amounts ranging from zero to values worth approximately four month’s wages if they maintained their HIV status for approximately one year..."
So I decided not to talk about vaccines today. Instead, I will be talking about clinical trials more broadly. I know quite a bit about vaccines but not enough to call myself an expert. And expert opinion is needed right now. So imma stay in my lane.
I worked doing project management for clinical trials during my gap year between undergrad and grad school. It was boring but I learned a lot
A clinical trial is seen as the best was to find a causal link between two variables
A lot of measures treat individuals as dehumanized objects that are used as inputs in a statistical measure presented as value-free
they also tend to disregard the reality that humans are just mammals who interact with nature and other animals
This human-centric research comes up wrong over and over because we act like we are above our environment. We manipulate nature to suit our needs without looking at the consequences to everything else
Using quantitative research to study groups with intersectional identities has methodological issues
Much of this info will be taken from the article:
"When Black + Lesbian + Woman ≠ Black Lesbian Woman: The Methodological Challenges of Qualitative and Quantitative Intersectionality Research"
I do love that the article starts with an Audre Lorde quote
“... constantly being encouraged to pluck out some aspect of myself and present this as the meaningful whole, eclipsing and denying the other parts of the self”
One of my favorite subjects to talk about: causality and methodologies
Epidemiology is all about measurement and causal inference. Sociology is more theoretical but it does touch on methodologies quite a bit.
Epid is bound by its methods. Sociology is bound by its theories. So to conduct epid studies, math or stats makes the most sense. Sociology can use any method so long as the method makes sense to the study
I taught two semesters of sociological research methods. So I've become really interested in the social critiques of epid methods and vice versa. Let's get it
Medicalization is where human conditions are treated and defined as medical conditions
Is it imposter “syndrome” or are you literally an imposter because academia was built for and by wealthy, cishet, white men. Many of whom were agents of slavery and genocide