µ* (Outer Measure)
@mustar.bsky.social
I am many things: a writer, a physicist, a theoretical philosopher, but above all I am a man… a hopelessly inquisitive man. No DMs
Accidentally letting a person die as you enter your rekordbox mind palace and browse your house music playlist for the perfect CPR track
December 31, 2025 at 12:07 PM
Accidentally letting a person die as you enter your rekordbox mind palace and browse your house music playlist for the perfect CPR track
Happy birthday legend!
December 22, 2025 at 12:14 PM
Happy birthday legend!
(embed link from an earlier draft, still heat and so great to hear when Mother played it on a big system)
December 15, 2025 at 10:08 PM
(embed link from an earlier draft, still heat and so great to hear when Mother played it on a big system)
Both Kowton and Asusu been out of it for too long 😔
www.youtube.com/watch?v=oUeH...
asusu.bandcamp.com/track/velez
www.youtube.com/watch?v=oUeH...
asusu.bandcamp.com/track/velez
End Point, by Peverelist & Kowton
from the album End Point / Vapours
peverelist.bandcamp.com
December 15, 2025 at 10:07 PM
Both Kowton and Asusu been out of it for too long 😔
www.youtube.com/watch?v=oUeH...
asusu.bandcamp.com/track/velez
www.youtube.com/watch?v=oUeH...
asusu.bandcamp.com/track/velez
As a subset of eligible voters, I don’t think we are discussing a meaningful data set. It has meaning only in its negation (reform voters). My first skeet to Aurelien was rhetorical way of challenging that the statistic is worth sharing
December 13, 2025 at 12:07 PM
As a subset of eligible voters, I don’t think we are discussing a meaningful data set. It has meaning only in its negation (reform voters). My first skeet to Aurelien was rhetorical way of challenging that the statistic is worth sharing
Right, sorry for mixing my tenses
December 13, 2025 at 11:31 AM
Right, sorry for mixing my tenses
Extrapolation is not an unusual treatment of the data. But if you have muddled your data set by combining, eg, “people who like chocolate” with “people who go for morning walks” and no longer distinguish between the two, I think there is less you can usefully derive from it
December 13, 2025 at 11:09 AM
Extrapolation is not an unusual treatment of the data. But if you have muddled your data set by combining, eg, “people who like chocolate” with “people who go for morning walks” and no longer distinguish between the two, I think there is less you can usefully derive from it
I’m not extrapolating, it’s microblogging and such errs are quite common. *Wouldn’t have
December 13, 2025 at 11:05 AM
I’m not extrapolating, it’s microblogging and such errs are quite common. *Wouldn’t have
Fuck yeah! Thanks 🥲
December 13, 2025 at 1:46 AM
Fuck yeah! Thanks 🥲
Cool! The tentacles are the how connections between neurons are reinforced? They move in this way and find ”the right” neuron to connect to?
December 13, 2025 at 1:30 AM
Cool! The tentacles are the how connections between neurons are reinforced? They move in this way and find ”the right” neuron to connect to?
*more reasonable _in the absence of further evidence_
December 13, 2025 at 12:57 AM
*more reasonable _in the absence of further evidence_
I do think a proportional (to actual votes) assumption is a more reasonable treatment of the ‘haven’t voted’ category than saying they ‘wouldn’t vote for Reform’ or grouping them with ‘voted against Reform.’ I do support Aurelian’s reasons for resisting the assumption, if not the alternative
December 13, 2025 at 12:54 AM
I do think a proportional (to actual votes) assumption is a more reasonable treatment of the ‘haven’t voted’ category than saying they ‘wouldn’t vote for Reform’ or grouping them with ‘voted against Reform.’ I do support Aurelian’s reasons for resisting the assumption, if not the alternative
I am aware of your work. I‘m sorry I was unable to communicate why I took issue with your use of statistics
December 12, 2025 at 3:51 PM
I am aware of your work. I‘m sorry I was unable to communicate why I took issue with your use of statistics
‘Didn’t vote for [X]’ removes the distinction and I don’t think you can make much useful further analysis in doing so
December 12, 2025 at 3:38 PM
‘Didn’t vote for [X]’ removes the distinction and I don’t think you can make much useful further analysis in doing so
Correction to earlier skeet: I think there is an important category distinction between “didn’t vote [for any party]” and “voted, but not for [X].”
December 12, 2025 at 3:35 PM
Correction to earlier skeet: I think there is an important category distinction between “didn’t vote [for any party]” and “voted, but not for [X].”
“Reform won the election with 10% of the registers vote“ would have been a framing I would take no issue with, by the way. My problem was bundling the categories “didn’t vote” and “voted against Reform”
December 12, 2025 at 3:27 PM
“Reform won the election with 10% of the registers vote“ would have been a framing I would take no issue with, by the way. My problem was bundling the categories “didn’t vote” and “voted against Reform”
The argument you are making is for the overestimation of public support for Reform? I don’t think the 9/10 didn’t vote for Reform has much useful to say about this if 9/10 didn’t vote.
December 12, 2025 at 3:23 PM
The argument you are making is for the overestimation of public support for Reform? I don’t think the 9/10 didn’t vote for Reform has much useful to say about this if 9/10 didn’t vote.
It’s the same kind of statistics that a loser who says “yeah, but if everyone who didn’t vote voted for me, I would have won.” This may be a fact by the numbers, but it is not an appropriate bundling of the ’didn’t vote’ category and is dishonest in its consideration of only the extreme case.
December 12, 2025 at 2:16 PM
It’s the same kind of statistics that a loser who says “yeah, but if everyone who didn’t vote voted for me, I would have won.” This may be a fact by the numbers, but it is not an appropriate bundling of the ’didn’t vote’ category and is dishonest in its consideration of only the extreme case.
I just think—for the category conflation—it’s a dishonest headline figure, even if true. You need further analysis to make claims about the % of intersection. Your figure accounts for only one extreme
December 12, 2025 at 2:09 PM
I just think—for the category conflation—it’s a dishonest headline figure, even if true. You need further analysis to make claims about the % of intersection. Your figure accounts for only one extreme