I learned a lot listening to this piece on the Shelterforce website : Are Urban Planners Ignoring Climate Gentrification ?
Oh, bug off.
Since I began rescuing animals about a decade ago, I’ve heard a lot of stupid crap, and the stupid crap I’d like to address today is the “it’s only an animal” comment. You know them, the people who respond to friends grieving over a lost pet with impatience and comments like this.
These people think they have their priorities straight, and anybody who grieves over an animal doesn’t. After all, it’s not like a person died. It’s just an animal.
Here’s the deal: these people do not have their priorities straight. Because if they did, they’d shut their face and support their friend through their grief—because even if you think an animal’s life or suffering doesn’t matter, your friend’s grief does matter. Nobody ever, not once, ever in the history of the world ever stopped feeling grief because somebody told them to. They just learned to hide it, which is about the comfort and convenience of those around them, nothing else.
People who treat their friends like their problems are dumb or inconsequential are bad friends.
Beyond that, I don’t have any need to prioritize what I love or care for. I’m not Sophie in Sophie’s Choice—thank heaven. The love I give to a dog or a cat or a lizard is not a lizard-or dog- or cat-sized amount of love taken out from the finite amount of love I have available, gone forever, squandered on an animal when it could have gone to a precious human. My ability to love gets bigger, not smaller, the more I do it. My time and energy may be finite, so I can’t take care of everything and everybody—and love may involve recognizing those limits —but my capacity for love is, I’ve found, pretty damn capacious.
If yours isn’t…well, that must be nice….I guess.
I can simultaneously be sad a gorilla is shot dead to protect a child AND be overjoyed the child is ok. I’m rich and complex in how I love and care.
If you are not…ok.
But don’t judge my kind by your kind.
Attention conservation notice; if you want to skip the rant-y bits, skip to the two numbered points.
So SCOTUS this week did everything women said they were going to only to be met with “OH SHUT UP THAT WON’T EVER HAPPEN STOP BEING SO HISTRIONIC YOU DUMB BITCHES” and here we are.
The court has been captured by religious minorities in the US who are also welll-funded. The Court has always, however, been stupidly undemocratic, and it should be reformed.
Five of the six people who voted for the garbage we got this week (STATE’S RIGHTS…but not with guns) and (ERMERGERD YOU CAN’T FORCE PEOPLE TO GET A VACCINE IT’S A BIG GIANT MEDICAL PROSHEDURRRR but giving birth? Meh, NBD, right?) were appointed by presidents who lost the popular vote.
So here’s a start on how to fix it:
1. End lifetime appointments. Replace it with a well-enumerated 8-year term. That way when you get complete duds like Clarence Thomas or Anthony Scalia, they eventually cycle out and those of us who read their opinions aren’t stuck reading their garbage reasoning and terrible writing for decades.
2. Select judges at random from the circuit courts instead of through presidential appointments. That way you get judges that have been in a court room instead of the fed society professor types. I am a professor type, I think profs can do great things and I have no patience for the whole academic practitioner sandbox fights, but in this case, various law schools have a stranglehold on the court, and it’s time that stopped.
Yes, a lot of those circuit court judges are also religious weirdos but it’s a much bigger pool and it decreases the likelihood that the fed society can do what they did with Amy Coney Barrett—groom them from undergrad to do exactly what she just did—and Brett Whatshisface—brought to us by his lifetime of relentless ass-kissing.
I don’t think necessarily that expanding the court changes what needs to be changed. There are an endless line of fed society drones with their palms out willing to sell out women and minorities to feather their nest with a SCOTUS appointment. I don’t think it makes any difference to have the votes go 16 to 13 as long as SCOTUS is a sinecure for conservatives from Yale and UChicago and the religious unis.
I lurve the idea of teaching students lots of methods for solving math problems because I just plain love math problems and I can’t help but think that there has got to be a better way of teaching concepts than the humorless, awful, dry, disempowering way I was taught. Follow the blue box. OR ELSE. You will be WRONG. WRONGITY WRONG WRONG WRONG. Oh, don’t fret, dear, girls aren’t good at math anyway. Yeah, maybe because boys in my childhood were the only people raised with the kind of self-esteem and security that lets you face that kind of instruction.
ANYHOO, I will watch “new math” tutorials online until my eyeballs bleed because they are so fun and I am so curious. I decided over the weekend to take a whack at the visual line-factoring method that is variously referred to as “Japanese multiplication.” I really couldn’t find out whether it was Japanese or not, or who was the originator of it; most websites are focused on teaching you the how and why of it, not the history of it. But whoever made it up, good job.
The method is explained very well here. In sum, you draw out lines for each digit of each number in one direction, and then you draw outline lines for each digit of the multiplier crossing the first, and then you add the intersections of the lines that occur at specific locations: the hundreds, tens, and ones.
I didn’t happen upon this site until I had been noodling around a little bit and gotten myself in a little trouble, and then that site made sense: it’s not an efficient method for numbers with large digits: I got myself in trouble pretty fast getting ambitious with 973 x 819. It’s not that it doesn’t work; it’s that it’s a PITA to draw all those damn lines and count up all the intersections, and it gets messy. AHA. So THAT’S why all the exemplars are things like that 321 x 123.
It’s not an efficient method of calculation, but it is a very good way to understand what is actually happening with multiplication. Using this method, you see how factors work. So you don’t really need to do examples with the larger digits–you can just use the standard algorithm or a ubiquitous calculator if you want to calculate efficiently.
Sorry I have been MIA. I’ve been having procedures that suck.
Ok, there is no way this “Spoiler” question gets answered just with primary outcomes simply because of things like momentum and other things that are pretty intangible, but I remember a lot of kvetching from Bernie camp about Warren. My own position on this is that
- Primaries are there to let people get on the big national stage, get their name out there, etc, and that a lot of the kvetching about Warren as a spoiler amounted to “Girls shouldn’t run for public office, let alone for the big chair” and
- If you can’t win the primaries, decisively, then you are going to get routed in the generals.
but I always planned to go back and look at the states where not having Warren in the race would have made a difference for Sanders. I put together data from Wikipedia—I am assuming these are probably fine. If they aren’t, then let me know a better source. From this I patched together a Google sheet that got so messy I am loathe to share it. If you really want it, email me.
I’m going to go forward with the assumption that every single Warren vote would have gone to Sanders and not Biden or Bloomberg, which is a pretty big assumption, but I don’t actually have a good reason to parse the votes any differently.
It looks like Biden walked off with a total of 19,080,152 votes and Sanders got 9,680,042, so that the overall vote gap was 9,400,110. Warren got 2,831,566. So the aggregate level isn’t even interesting, even if you dump in Bloomberg at 2,493,523. (Sanders plus Warren plus Bloomberg would put the gap between Biden and Sanders at 4,075,021. Why in heaven’s name did people vote for Bloomberg? Why do people think rich buttheads from New York are good candidates? Why? And BTW, I am not in any way of the mind that rich buttholes from California would be any better. )
So going state by state, I calculated the gap between Biden and Sanders and compared it to Warren’s vote take. Then I compared: which was bigger? I threw out states with caucuses because those are weird and I threw out states that Sanders won. I found there were six states where Warren not being in the race might have helped Sanders: Maine, Massachusetts (the state she reps), Minnesota, Oklahoma, Texas, and Washington. But, Bloomberg actually beat Warren in Texas and Oklahoma–in Texas, he beat her by kind of a lot.
The plot below shows the votes needed and votes available if you kick out either Warren (W) or Bloomberg (B). So there are two states that stand out: Texas and Massachusetts and they split between Warren and Bloomberg.
So who was the spoiler for Sanders? I think the argument is that the people who voted for Bloomberg would never vote for Sanders, and that Bloomberg was a spoiler for Biden if anybody. But I’m not sure about that–Trumpism is populism led by a rich guy from New York, and I don’t think the left is immune from becoming enamored of rich dudes from New York. Nobody asked whether Bloomberg had any business running, and nobody that I followed ever ragged on him to endorse Sanders the way Sanders people went after Warren to do so. Misogyny, of course.
But also, I think a lot of the Bernie people just didn’t watch Bloomberg too terribly closely, and it’s one of the blindspots that I think needs to get some attention. Bloomberg is arguably more of a center-right candidate that Barack Obama was. The idea that somehow challengers from the left would drain much from Sanders, as well as the grumbling about “centrist democrats”–a straw man construct that online lefties like whip for their (legitimate) gripes with the Democrats–masks the fact that the center among Democrats is actually pretty big swath of difference in policy positions if you are going to count Warren as a “centrist” when Democrats like Bloomberg are getting the vote take they are.
I don’t have any data things to relate today, just a recommendation.
The Repair Shop is…”reality tv”, very light, about the heirloom restorers who work at the Weald and Downland Living Museum in Singleton, West Sussex. I LURVE it. I love to watch people make and fix things. It’s the only kind of reality TV I can stomach.
It is hokey, but it’s awfully sweet to see how attached people are to the material things of their family history. I have absolutely nothing like that from my family, and Andy has only one or two things. I want to be best friends and have tea with the ladies who fix teddy bears. I want to to ask ask Suzie Fletcher, who fixes leather, if she wants to be my girlfriend (whooooo! Leather! Wheee!)
Mostly, it’s nice and wholesome and it is very, very reassuring to me at the moment that broken things might be repaired.
It also makes me think about material culture and the things that are worth treasuring.
By way of getting something visual on this post that I don’t have to steal off the inter webs, here is my attempt to save something–I made Andy candy corn socks for Halloween a few years ago, but an evil moth got in and at holes in them. So I darned them. I am pleased with them.
Hey, Jay Blades, if you need a fabric restorer, look me up.
I was part of the Gen X world who experienced that brief moment in time when the US educational system decided it was going to become like a normal country and start using metric. I absolutely loved it. It made so much sense, and to this day, I can move readily between volume, distance, and weight measures quite readily.
The problem has *always* been Celsius. It means nothing to me. I don’t mean doing the conversion. I can do that. It’s just in reading or conversation, I just don’t have a sense of whether a measurement in Celsius is relatively hot or relatively cold. I have always felt very bad about this, and always assumed someday I’d have a better grasp of it. But it hasn’t come.
One of my most wonderful students Dustin Wong who has traveled at lot but is I believe originally from Singapore overhead me describe this problem, and he said to me “Fahrenheit means nothing to me.” Since I’m pretty sure Dustin is 40 times smarter than me (Dustin actually has a legit shot at TRULY being the Smartest urbanist in the room), his comment made me feel much better.
I was stuck at the cancer center waiting and waiting and waiting for my imaging appointment and I decided to take myself in hand and try to learn what Celsius means relative to my own understanding of temperature (what I call “the Lisadex”) and Fahrenheit. Also, I decided to do a silly font because waiting at the cancer center is depressing and blows.
The result follows:
I couldn’t really find a dataset I wanted to fiddle with this week, and I’m feeling rotten, so I just did a little drawing of some empires. Now, I just Googled around for some general timelines, and I think one reason why the Mayan Empire is so long is the way people have constructed the definition of the Mayan Empire, but it’s still old. It might be that it is more like 3,000 (like Egyptian) but…I did what I did.
Mostly, I got kind of interested in the over-emphasis that the Roman Emperors get. If you include Byzantium, yes, the time period is long, but I guess I still don’t see Byzantine leaders studied and storied as much the emperors of the western empire. The Republic by this accounting actually held out at little bit longer. The Emperor period seems longer I think just because there are so many Emperors, largely because they murdered each other left and right.
Anyhoodily I’m sure there empire in SE Asia and throughout Africa that deserve a bar here, these are just the ones that popped into my head when I was drawing this morning. (Keep in mind, these are compared for no reason other than I am stuck in bed feeling like garbage today.
If you have one you want to me do, feel free to email me.
LA Metro is just finishing up a project that is very dear to my heart because I think it’s pretty important. Transit advocates sometimes fall into a trap sometimes–some transit lovers are uncritical and they will advocate for projects that really maybe never need to be built. Bad projects do exist, and the suck resources away from the agency. As a result transit skeptics find it easy to write off advocates.
Another problem advocates face, particularly in Los Angeles where transit riders are such a minority, is helping people understand why some projects really are damn good projects. I’ve found that to be the case with the Regional Connector: often, when somebody asks me why it’s such a nice new part of the network, I find myself describing how different trips will be possible with no or fewer transfers. Unfortunately, stated that way, the regional connector sounds like it’s solving a “me” problem–that is a problem that irritates me and the few people who are like me, but isn’t really objectively an improvement.
One nice way of characterizing the improvement is simply that kids in East LA will be able to take a one-seat ride to the ocean. That should matter to people–it does to me.
Nonetheless I’ve dipped in out of graph theory attempts to characterize why the regional connector is so nice from a *network possiblity* perspective. In transit, we have tons and tons of ways of measuring outputs (passengers, etc) and some inputs (usually monetary, but operator-hours, etc). But advocates have few ways of discussing the physicality of the network in short, summary measures. And I’m not suggesting that we should always just look at one metric to understanding a network–we should use a bunch, but I do think there are some key calculations that help me show just how nice the regional connector is for the network.
I first encountered some measures in Vulcan Vuchic’s 2005 textbook. He’s got a *boatland* of cool network characterization and performance measures in there. I set my class on working with some of them–I used the Madrid network for a class project because I had some students in there who would insist on just counting nodes and lines in the toy networks I gave them instead of using the equations, and Madrid has a very complex network that would cross your eyeballs if you tried brute force the count.
I got to thinking that one way to help us understand how the Regional Connector serves as a nice additional is to simply look at the new trips it makes possible. This would just be a matter of looking at the transit lines, the stations, and their connections–but if you know the proper number of stations, you know the possible origins and destinations. To get the proper number of stations, you count them all up and remove the duplicates:
Then, to sort the O-D possibilities, you just use that N and N-1:
Here’s what you get when you do this for three LA rail network states: Current potential trips (O-D pairs), when the Regional Connector comes online, and after Metro finishes all the new bits of the Purple Line and Crenshaw (All). (Note the base network includes the Orange Line, and that I set up the Regional Connector lines based on the promised new stations, Chinatown station being open, and Metro’s planned goals for interlining the Gold Line (I’m sorry, I never remember their letter names) and the Expo line for that East LA to Santa Monica Ride and Blue line to Gold line headed north).
Now these network measures are obviously partial. It might be cool, for example to weight all these O-D possibilities by existing and projected ridership by station (I don’t have those data because Metro thinks I’m a gangster or because I don’t know where to find them, one or the other.)
And, just by way of illustrating that, there’s another idea that Vuchic suggests–the notion of directness. you can figure out how many O-D pairs are possible without a transfer with:
In each network state, delta goes down–let’s interpret that. In theory, it would be nice for delta to be a relatively large number (between 0 and 1). The larger the number, the more one-seat trips you are offering. In our case, the amount of OD pairs just jumps so much that the delta goes down: in the order given above, from 0.18 now to 0.15 with the regional connector to 0.10 with all the new line openings in the next few years. Delta becomes much less an issue with greater frequencies. Again…this is just one measure it’s not meant to say the network on the whole is worse off–it’s that this one measure, directness, declines with the new lines. It makes sense.
Sorry my equations are wonky but I am no mood to futz with making everything perfect-looking.
So good-O to whoever thought up the Regional Connector. It’s a goodie. I raise my glass to y’all.
I can’t guarantee this is all 100 percent perfect because I’ve had kind of a bad week, but it is interesting enough to share. Hope you enjoyed.
All good things,
There’s been some conjecture that Covid lockdowns were the death blows that finally killed off American transit, which is, as David Levinson pointed out, always in a state of permanent financial crisis.
I had my students do some digging around to look at the ridership figures from various agencies, and one of my brilliants students, Christopher Winkels, dug up a spreadsheet from APTA.
I struggled a bit with this simply because everything these days is struggles but also because I don’t want to overstate or understate what is going on. By way of explanation, all of these data are December ridership figures. Things started opening up in 2021, and so the best comparison of the come-back I had in the data I felt would be December 2020—middle of the pandemic—to December 2021.
The pre-pandemic by way of comparison is an average of the past three Decembers (2016 to 2019).
What agencies are selected? The ones Lisa was interested, which means all of the big ones, some decent-sized southern systems, and Utah. Why Utah? Dunno. Thought it might be interesting.
Sorry about the over-plotting, but honestly, this was as good as it got.
What is this showing? Well this was my first at the data, what we see here are two points–Dec 2020, and December 2021. They are not compared to each other. Instead ridership in both years is displayed as a percent of the pre-Covid (2019) ridership. I think of this as how well each agency’s ridership has recovered. As we’d expect, 2020 values are smaller, and most agencies seem to be bouncing back decently, so that it’s possible that by next year they could be pretty close to their pre-COVID levels. (They might be there now for all I know; I diddled around so damn long with these data, we might have new data by now.)
What is going on with BART? Did I screw up those data points?
I think the above graphic is really the way to be thinking about where ridership is at and where it is going, but I also data going back 2002 and I felt like I had to use it. Be patient about this one loading: I slowed it down so that I could read it.
These kinds of post usually bring out the mansplainers in droves about how I should have all these differently, what the right way to do them is, and for any dude who feels the need to bug me with those comments…absolutely nothing is keeping you from making your own graphics the right way, the “you” way, Chief. I did these to see if I could learn from them and just decided to share them for sheets and giggles. I think I have a better handle on what’s up, YMMV. Go get ’em.