lecture 12 - relevance

• traditional position: relates to the (logical) positivist epistemology • you can’t rely on normative reasons for relevance of theory: it is relevant if it is good science good = precise, logical, rigorous, methodological, high quality - not normative to identify research object: not problem-solving, politically motivated or something, it should be method driven (neutral desire to fil gaps in knowledge, no matter where it will take us) • enlightenment function = relevance is assumed, the relevance is in furthering knowledge criticism: knowledge is power, producing knowledge for different reasons makes a difference (e.g. you can see scientists responsible for what they do/create: e.g. atomic weapons) = ethics plays a role - perhaps more knowledge in certain circumstances isn’t good - science can be used in an unethical way (question = how does enlightement function handle this)

form of research: the way it is presented it would be more relevant if polsci communicated better solutions: - free access to journals - social media - popular writing (opinion articles, newspapers, etc. to show results of research more widely) - media engagement barriers: jargon (sometimes necessary to capture a concept, but sometimes it only serves to exclude people from understanding), gatekeeping CRITICISM on this: simplifying may hide complexity, will not include data and references -> doesn’t do research/knowledge justice question: how do you balance these different concerns? - you can’t do everything, it’s a trade-off in resources

problem-solving as priority scientists shouldn’t look at random knowledge gaps, they should look at what has societal relevance/benefit • e.g. problem of turnout: people aren’t voting, people find it to low -> scientists can research why there is a low turnout • • providing solutions: e.g. mandatory voting, paid time off to vote CRITICSM; - it can become a tool for gov. - who decides what a problem is? it’s not just scientists finding gaps, someone else is defining problems (do people with money become the main agenda-setting actors) e.g. AI research: microsoft invested in openAI research - who decides what research is being done?

design thinking: designing particular policies polsci coming together with other disciplines to design policy problem: policy always good for some, bad for others. with what legitimacy do we decide how policy should work out? also weird to say polsci should have no say in policy: empirical social science research helps determine what makes policy succesful

production of knowledge should get out of universities, there should be more co=production: cooperation with civil society + firms it needs to stop locking people out criticism: universities are designed to be places where people do methodological work, they have the resources to do research for its own sake (result: becomes technical, difficult) -> ….

academics and universities are in aan ivory tower : far removed from society • negative aspects: knowledge is locked away (behind/in the tower) while it should be shared + ivory towers are far away from the people (isolation researchers -> scientists may have wrong understanding of the world outside of the ivory tower = less realistic) • positive aspects (you can also see it as a positive thing to isolating universities from society): isolates dangers from society (defensive structure), gives independence (protects from outside influence, you can choose what to work on (wouldn’t be the case in a market context)), it portrays science as something that has value, with a tower you can look really far (you have a good overview)

• citizenship education • political science to protect foundations of liberal democracy = opposite of first approach (should be value-free, objective) problem: not all social scientists agree that democracy is valuable or needs to be protected + risk of overstepping: there is academic freedom to DO defend or attack it

• developing critical thinking • clarifying concepts & public discourse • demystifying politics • speaking truth to power