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A good sample needs to be random and representative of the population as a whole, otherwise you introduce sampling bias. Imagine trying to do a survey of what
by MrJohz 1y ago
A good sample needs to be random and representative of the population as a whole, otherwise you introduce sampling bias. Imagine trying to do a survey of what people's favourite fast food restaurants are, but doing it inside a McDonald's — it doesn't matter how large your sample is, it's going to be heavily biased. This is why survey companies spend a lot of effort trying to find random, representative samples of the population, and often weighting their samples so that they match the target population even more.
If we treat elections like a survey, then they have a massive inherent bias to the sampling method: the people who will get "surveyed" are the ones who are engaged enough to get registered, and then willing to go to a physical polling station and vote. This will naturally bias towards certain types of people.
In practice, we don't treat elections like a survey. If we did, we'd spend a lot of time afterwards weighting the results to figure out what the entire country really thought. But that has its own flaws, and ultimately voting is a civic exercise. You can do it, you can avoid it: that choice is yours, and ultimately part of your vote. In a way, you could argue that the sample size for an election is 100% of the population, where "for whatever reason, I didn't cast a vote" is a valid box to check on this survey.
That said, the whole "samples can be biased" thing is very much relevant for elections because many political groups have an incentive to add additional bias to the samples. That could be as simple as organising pick-ups to allow their voters to get to the polls, or teaching people how to register to vote if they're eligible, but it could also involve making it significantly harder or slower for certain groups (or certain regions) to register or vote.
- potamic 1y agoA 100% sample is unattainable, not just practically, but fundamentally. Even if you made voting mandatory and ensured collection of every single vote, there will always be people who will fudge their vote because they are not interested in the process. I argue that any election is only representative of people engaged with the process and that fundamentally cannot change. Within that subset, you shouldn't need 100% sampling for high confidence. But agree that random distribution is key to this, but I don't see how that could change with the messaging that every one must vote, versus saying just vote if you're interested.
- MrJohz 1y agoI mean that an election is (theoretically) an 100% sample because every eligible has the ability to interact with the voting process at the level that they choose. So the decision for some people to invalidate their vote, or to vote tactically, or not to vote at all, or whatever else: that's part of the act of taking part in an election. In that sense, you can't not take part in an election, if you're eligible to vote. This is important, because normally, once you take a sample, you need to analyse that sample to ensure that it is representative, and potentially weight different responses if you want to make it more representative. For example, if you got a sample that was 75% women, you might weight the male responses more strongly to match the roughly 50/50 split between men and women in the general population. But in an election, we don't do this, because the assumption is that if you spoil your ballot or don't take part, that is part of your choice as a citizen. But I think we're saying the same sort of thing, but in different ways: you can either see "the sample of an election is every citizen, regardless of whether they voted" or "the population of an election is everyone who voted", and in either case the sample is the same as the population, and we can therefore assume that it is representative of the population.