littlegreenplanet reblogged
What I learn from Science & Technology Studies is that you shouldn't blindly trust science because there's a fair amount of fuckery (mostly unintentional but sometimes not) going on in the background, but you also shouldn't *not* trust science in the way that most people who don't trust science don't trust science.
Anyways, hope that helps!
So to be clear, science:
- Often takes as implicit particular philosophical assumptions that aren't necessarily valid in all cases (e.g., psychologists accepting liberal-individualistic models of human nature and neglecting social causes)
- Relatedly, often works with things that are easy to measure, regardless of whether there is any a priori argument in favour of those quantities being particularly relevant (the so-called "streetlight fallacy"--e.g., there are actually rather few results from clonar mice that are directly portable to humans, but clonar mouse studies remain a standard in medical research because they're easy to conduct)
- Relatedly, often assumes that entire complicated systems can be reduced down to proxies that are easy to measure and especially to quantify, regardless of whether this is a reasonable assumption or not (e.g., "gene fetishism" neglecting the role of epigenetics, proteomics, etc. in favour of attributing every significant aspect of an organism to its genes)
- Often takes as implicit certain perspectives and cultural biases, especially white/male/Western perspectives (e.g., the entire centuries-old body of midwifery lore being ignored upon the professionalization of medicine as a discipline in the seventeenth century)
- Often encodes other cultural biases as well (for example, mycology was, until quite recently, extremely understudied and relegated to a minor subfield of botany because Anglo cultures tend to have a low regard for fungus; this in spite of the fact that fungi make up a very significant chunk of the earth's biomass)
- Can often present entire models of how the world works that are arrived at based on sociological factors within science itself (Thomas Kuhn's paradigms), or within the wider society (Foucault's epistemes)
- Often misstates statistical significance because scientists lack an adequate command of the discipline of statistics.
- Can churn out a lot of substandard studies because of professional pressures on academics to publish, publishers' pressures to have the next big thing, and the time constraints of peer reviewers.
- Can often just produce straight-up garbage because some fields are beholden to commercial interests (e.g., the pharmaceutical industry maintains entire journals that just exist to give crap drug trials the appearance of scientific legitimacy)
- Can be manipulated by dishonest reporting (e.g., the pharmaceutical industry, again, might conduct hundreds of studies and publish only the one that produces favourable results; Facebook might conduct hundreds of studies on manipulating public attitudes and only publish the few that encourage advertisers to give them money)
- Is shaped by the priorities of the state and capital (i.e., in terms of what research questions get funded)
- Is a structurally collective enterprise that builds largely on trust in the competence and intellectual honesty of one's peers, rather than verification of every previous result by every individual scientist
- At a policy level, can produce misleading results just based on what particular types of scientist are invited to the table (e.g., COVID-19 containment measures going disastrously awry because epidemiologists were considered relevant to include on the panel but social psychologists were not)
However, none of this, when taken together, should be interpreted to mean:
- Science is made-up
- Scientific findings bear no relation to the actual behaviour of nature
- You can just pick and choose what aspects of science to believe in based on gut instinct or what makes you feel good
- Science is not the best tool we have for distinguishing what's real from what we want to believe.
