You guys can shit all you want on laboratories' academic methods of consensus and peer review, they are the ones who actually have the measurement instruments and spend years in a musty office getting the data. They are not playing that consensus and peer reviewing game to convince people, they're doing it to scam fundings out of the government. Fuck, they probably don't want to be peer reviewed, but they don't have a choice because it's a requirement for publishing in scientific journal, and number of publication is proportional to funding xD
Still, It's healthy to doubt everything. Consensus is rejected when a new experimental measurements consistently contradict the established model, but it can always be retconned and overfitted to agree with new data. So that's why it's important to recognize where consensus is unstable and always changing (especially when it comes to extrapolating stuff into the future).
You gotta concede that researchers spend a lot of time getting data and spin it to convincing conclusions that fits best their observations. Meanwhile dude lambda has better shit to do than note the sea level or some shit. So it's understandable that people would tend to listen to academic consensus. Especially considering that our tax money are litteraly funding these guys (unless they have secret deals with companies which happens. You don't know what it's like when you're a researcher to have your funder look at you in disappointment and says "we can't publish that shit, yo.")
In conclusion, have fun weighing people's opinion, might as well use a crystal ball
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If someone has an assignment about climate change, no matter controversial it is, you can just use past data. There must be past measurement of CO2, sea acidity, temperature for the past fifty years and it can be compared to models of the time.
Extrapolation for the future risks to be biased because there are actual real world conflict of interest with huge consequences.
Just because a model predicted stuff correctly in the past means that it'll work for the future. If that was the case, we'd be filthy rich by predicting the stock market. So, when you make your presentation on future perspective, you can say it's another beast altogether and present different paths.