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Joined 11 months ago
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Cake day: July 28th, 2023

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  • London is full of excellent amazing things but they’re spread out over an absurdly large area so it’s such a pain doing anything. And everyone who lives there is so numb to it! They’ll happily indulge every day in 3-4 hours of public transport as if this is a rational way to live.

    I’m very happy that they have a reasonably decent transit system, but fuck me I wanted those 4 hours in my life actually.








  • Base 10 on your hands is really base 1. Every finger is either 0 or 1 and we just count them! Base 12 we do have 12 positions each representing a digit, and two potential digits from our hands.

    Binary is so much more efficient because you have 10 digits, just like in base 1, but you use them more efficiently.

    The next logical step is trinary, if we can incorporate enough fingers it would go higher than binary. Wikipedia suggests three positions of your fingers - up, down, and somewhere in between, or folded - but I’d be surprised if anyone can realistically do that with all their fingers. However, using four fingers on each hand and pointing them at different knuckles/the tip of your thumb gets you 8 digits of base 4 (including not pointing at the thumb at all as 0)… And actually doesn’t tangle your fingers up too bad.


  • If only we could combine the two and get to 2^12… Sadly, this would require 12 thumbs.

    Ooh, actually you can get to 2^8 without worrying about those pesky tendon issues by putting your fingertips against your thumb instead of trying to extend your fingers… Hmmm… Maybe we can even go to 2^10 this way by incorporating knuckles. Might lose some time today figuring out more hand counting systems. I wonder if anything higher than 2^10 is possible…




  • Writing boring shit is LLM dream stuff. Especially tedious corpo shit. I have to write letters and such a lot, it makes it so much easier having a machine that can summarise material and write it in dry corporate language in 10 seconds. I already have to proof read my own writing, and there’s almost always 1 or 2 other approvers, so checking it for errors is no extra effort.



  • Do you think the paper drew sensible conclusions, or do you just not like my arguments?

    A correlation coefficient of .5 is in the ballpark of or bigger than the correlation between human height and weight. I wouldn’t be surprised if the bottleneck isn’t in the reliability of the measurement.

    This is fair enough, my background is not in social research so to me 0.5 is a moderate correlation. Not sure what you mean by the ‘bottleneck’ here, are you suggesting that the correlations could be higher with a different survey?

    Unmodeled interactions here also would only be able to suppress the explained variance - adding them in could only increase the R-squared!

    Given that the explanatory variables are in some cases more strongly correlated with each other than the response, do you think the model without interactions is likely to be an appropriate way to analyse the relationship between the response and the explanatory variables? It doesn’t at all make sense to me to do one single regression model and say “The F test says this is a good model, so the explanatory variables explain the response”, especially with a relatively low R^2, and given the fact that there is evidence of multicollinearity presented alongside!

    The paper presents the fact that they have done a regression model with a few good significances without any real analysis of if that model is good. We don’t see if the relationships are linear, we don’t see if the model assumptions are met. Just doing a regression is not enough, in my opinion.

    In case your 101 course hasn’t covered that yet:

    There’s no need to be rude. It’s perfectly acceptable to disagree with me, but you could do it politely.

    F-tests are also commonly used when performing an analysis of variance.

    Yes, I’m well aware, although I’m not sure what your point is. They haven’t done any analysis of variance.

    As is it’s impossible to say if the model they found is actually very good.

    You say that after quoting explained variance, which is much more useful (could use confidence intervals… but significance substitutes here a little) in this context for judging how good a model is in absolute terms than some model comparison would be (which could give relative goodness).

    My point is that they haven’t made any effort to find a model that best fits the data, they have just taken all the available variables, smacked them into python or R or whatever, and written down the statistics it spits out. There’s no consideration in the paper given to interpreting the statistics, or to confirming their validity.

    From the study:

    Although the regression weight for age was not significant, the direction was negative, suggesting greater endorsement for the car items for the younger sample.

    Not only was p-value for age clearly not significant, the confidence interval for the coefficient was [–.21, .17]… This includes 0 ffs! There’s no evidence here that there is greater endorsement of the car items in younger respondents. Why was age even included in the model in the first place, given that the correlation was near 0?

    Like I said - there is some evidence here of an interaction, I’ll concede that in context the correlation isn’t bad for 2 of the dark tetrad items, Wild and Crafty, but the analysis they have used to present this information is not well thought out or presented. Personally I don’t think that a linear regression model is even the right way to analyse the data they have, I especially don’t think this regression model is a good way to analyse the data.