#DataSCience

[neat-deadandlive-things]

Someone: Oh AI will save researchers so much time on database management.

Me: *bites them while recategorizing 200 data objects about indigenous North Americans which an AI had categorized as being research from the country of India.*

[manincaffeine]

Taking a life decision is really hard sometimes. After years of gap, getting back into studying feels tough. Leaving the city where I spent all my childhood and for the first time, leaving my parents behind to move to a new place and chase something bigger… it wasn’t easy. But yeah, I finally did it.

Idk where this decision will take me, but Im sure I’ll learn a lot from it. Here’s to starting a new chapter.

[turns-out-its-adhd]

AI exists and there's nothing any of us can do to change that.

If you have concerns about how AI is being/will be used the solution is not to abstain - it's to get involved.

Learn about it, practice utilising AI tools, understand it. Ignorance will not protect you, and putting your fingers in your ears going 'lalalala AI doesn't exist I don't acknowledge it' won't stop it from affecting your life.

The more the general population fears and misunderstands this technology, the less equipped they will be to resist its influence.

[altin-studies]

eid vibes

Exam diaries II.III, dop 1/100

Sunday, 15 June, 2025

Next Exam: Sampling Distributions (18.06)

I am both relieved and terrified of my sophomore year finals this year. I need so much more marks for As. ADHD has been rampant lately. I totally lost all joy in studying. Pushing through anyways...

Today's to-do: (insha'Allah)

Pray all 5 prayers F D A M I

Discrete Probability Distributions: pmf, cdf, use, pgf, mgf, mean, variance

Continuous Probability Distributions: pdf, cdf, use, mgf, mean, variance

Generating functions: pgf,pmf,cgf

Distributions function technique of finding distribution of a random variable

Distribution of minimums and maximums

Nothing is easy except for what Allah makes easy and he can make all difficult easy 🤲🏽

Hope you guys have a great time studying ~

[soleminisanction]

I got a bee in my bonnet and spent last night crunching these numbers to confirm a long-held suspicion of mine, and now I'm going to do something with them even if it's only interesting to me. So.

I went through and tallied up all of the fics AO3 currently (as of 3/27/24) has under the tags "Trans Tim Drake," "Nonbinary Tim Drake," "Genderfluid Tim Drake" and "Genderqueer Tim Drake," since I figured that cast a wide enough net without committing myself to reading every fic vaguely tagged Trans Character to figure out which character they were talking about.

I then did the same for Dick, Jason, Damian and Bruce and, after comparing those numbers against each other and against the total number of fics each character has under their general tag, followed up with Duke, Babs, Cass, Steph and Kate, and then Kon, Cassie, and Bart for good measure.

The results confirm the suspicions I was going into check and are really interesting, to me at least:

Despite having far fewer stories overall than Jason, Bruce or Dick, Tim has by far the most stories tagging him under the trans umbrella (653 out of 58,395) and is the only member of the Bats for whom at least one full percent of his stories fall under that category (1.12% to be exact.) He actually has more total trans stories than Jason and Damian combined (308 out of 71,120 and 255 out of 42,607, equaling 0.43% and 0.59%, respectively) and outstretches the 2nd place ranker, Dick, by over a hundred (who clocks in at 438 out of 79,057 -- 0.55%). Bruce amusingly has by far the most stories overall (90,305) but the fewest trans stories (185) for the lowest percentage among the boys (0.2%).

The only one who comes anywhere close to matching Tim percentage-wise is Bart, who has far fewer stories to his name but a ratio of 62 out of 5,717 for 1.08%. I was thinking maybe Young Justice might have a higher percentage than the Bats due to their strong queer fandom but that only really proved true for Bart, with both Cassie and Kon coming in at only 0.2% and 0.28% trans umbrella percentage respectively (actual count 6 out of 2,874 and 39 out of 13,746).

Cassie's numbers correspond with the fact that women just, do not get a lot of these stories, at all, even compared to the general lack of attention they're paid by fanfiction spheres in general. Steph and Kate both clocked in at falling 0.17% under the trans umbrella (29 out of 16,638 for Steph, 5 out of 2,897 for Kate); Cass got 0.13% (21 out of 15,769) and Babs only 0.07%, the lowest percentage out of anyone I calculated for (11 out of 15,785). Duke's showing was a respectable 0.55% (34 out of 6,166) which puts him about even with the rest of the boys.

All of which I just went through to confirm a gut instinct I've had for a while: even in light of the noticeable trend in fandom towards increased visibility for trans and other queer-gendered people over the last decade and a half or so, it's a notable Thing for the DC comics fandom to explore with Tim Drake in specific.

And that doesn't even take into account things like the over 200 "Tim Drake is Catlad | Stray" fics, which almost always have some element of queered gender or at least femme'd sexuality to them, far outstripping any of the other Robin boys' spins in that AU (those counts stand at, respectively: Damian - 11, Dick - 33, Jason - 79, Tim - 242). Or the 11 fics logged under the "Tim Drake is Batgirl" tag, a category that doesn't even exist for any of the other male Robins.

(What makes that last one extra hilarious to me that most people don't know one canonical version of Tim has been a member of the Batgirls.) Part of me wants to use that parenthetic detail as a segway to ramble about the various canon snippets I think probably contributed to this, from Tim being presented as "the pretty one" who most often gets the "looks like his mother" comments to the fact that he is the only male Robin who's ever cross-dressed for an undercover mission and even though it only happened once the Internet will never forget Caroline Hill.

But this post is long enough as it is and I don't really have a point beyond I think this is interesting and cool so I'm going to leave off here for now and put my numbers under a cut so people have the raw data to look at if they'd like to.

TL;DR - Based on the numbers, the internet believes Tim Drake is more likely to be trans than any other member of the Bat-family or Young Justice, and I think that has interesting implications about his character and fandom. It's neat.

Data Taken: 3/27/24

Tim Drake: 58,395 Trans Tim Drake: 513 Nonbinary Tim Drake: 46 Genderfluid Tim Drake: 89 Genderqueer Tim Drake: 5

Dick Grayson: 79,057 Trans Dick Grayson: 399 Nonbinary Dick Grayson: 15 Genderfluid Dick Grayson: 23 Genderqueer Dick Grayson: 1

Jason Todd: 71,120 Trans Jason Todd: 286 Nonbinary Jason Todd: 17 Genderqueer/Genderfluid Jason Todd: 5 (4 have both tags and are the only ones tagged Genderqueer Jason Todd)

Damian Wayne: 42,607 Trans Damian Wayne: 215  Nonbinary Damian Wayne: 37 Genderfluid Damian Wayne: 3 Genderqueer Damian Wayne: 0

Bruce Wayne: 90,305 Trans Bruce Wayne: 180 Nonbinary Bruce Wayne: 5 (2 also tagged Trans Bruce Wayne) Genderfluid Bruce Wayne: 1 Genderqueer Bruce Wayne: 1

-

Total Trans Umbrella Tim Drake: 653 Total Trans Umbrella Dick Grayson: 438 Total Trans Umbrella Jason Todd: 308 (313 if you count the GQ tag separately) Total Trans Umbrella Damian Wayne: 255 Total Trans Umbrella Bruce Wayne: 185 (187)

Percentage Trans Umbrella Tim Drake: 1.12% (1.11825) Percentage Trans Umbrella Dick Grayson: 0.55% (0.55403) Percentage Trans Umbrella Jason Todd: 0.43% (0.43307 or 0.44010) Percentage Trans Umbrella Damian Wayne: 0.59% (0.59849) Percentage Trans Umbrella Bruce Wayne: 0.2% (0.20466)

----

Duke Thomas: 6,166 Trans Duke Thomas: 20 Nonbinary Duke Thomas: 14 Genderfluid Duke Thomas: 0 Genderqueer Duke Thomas: 0

Barbara Gordon: 15,785 Trans Barbara Gordon: 11 Nonbinary Barbara Gordon: 0 Genderfluid Barbara Gordon: 0 Genderqueer Barbara Gordon: 0

Cassandra Cain: 15,769 Trans Cassandra Cain: 15 Nonbinary Cassandra Cain: 6 Genderfluid Cassandra Cain: 0 Genderqueer Cassandra Cain: 0

Stephanie Brown: 16,638 Trans Stephanie Brown: 27 Nonbinary Stephanie Brown: 2 Genderfluid Stephanie Brown: 0 Genderqueer Stephanie Brown: 0

Kate Kane (DCU): 2,897 Trans Kate Kane: 4 Nonbinary Kate Kane: 0 Genderfluid Kate Kane: 1 Genderqueer Kate Kane: 0

-

Total Trans Umbrella Duke Thomas: 34 Total Trans Umbrella Barbara Gordon: 11 Total Trans Umbrella Cassandra Cain: 21 Total Trans Umbrella Stephanie Brown: 29 Total Trans Umbrella Kate Kane: 5

Percentage Trans Umbrella Duke Thomas: 0.55% (0.55141) Percentage Trans Umbrella Barbara Gordon: 0.07% (0.06968) Percentage Trans Umbrella Cassandra Cain: 0.13% (0.13317) Percentage Trans Umbrella Stephanie Brown: 0.17% (0.17429) Percentage Trans Umbrella Kate Kane: 0.17% (0.17259)

----

Kon-El | Conner Kent: 13,746 Trans Kon-El | Conner Kent: 19 Nonbinary Kon-El | Conner Kent: 19 Genderfluid Kon-El | Conner Kent: 1 Genderqueer Kon-El | Conner Kent: 0

Bart Allen: 5,717 Trans Bart Allen: 40 Nonbinary Bart Allen: 20 Genderfluid Bart Allen: 1 Genderqueer Bart Allen: 1

Cassie Sandsmark: 2,874 Trans Cassie Sandsmark: 4 Nonbinary Cassie Sandsmark: 2 Genderfluid Cassie Sandsmark: 0 Genderqueer Cassie Sandsmark: 0

-

Total Trans Umbrella Kon-El: 39 Total Trans Umbrella Bart Allen: 62 Total Trans Umbrella Cassie Sandsmark: 6

Percentage Trans Umbrella Kon-El: 0.28% (0.28371)  Percentage Trans Umbrella Bart Allen: 1.08% (1.08448) Percentage Trans Umbrella Cassie Sandsmark: 0.2% (0.20876)

[coolhideoutparadise]

Trans Lady looking for a serious relationship 💋😘 how do I look

[kkelenca]

A colleague has a student collecting data on bad handwriting, if you could take 2 minutes to decide between some 1s and 7s ✍🏻👀

[dionyssuus]

poll time! please share!

[pseudonaivete]

Thanks, day ruined

[herpersonafire]

Hey everyone! enjoying my (two) week break of uni, so I've been lazy and playing games. Today, working on Python, I'm just doing repetition of learning the basics; Variables, Data types, Logic statements, etc. Hope everyone has a good week!

[wyyrmwood]

This is WAY different from my usual art, but I'm posting it anyway! I start GIS masters soon and before then I'm practicing making maps in Esri tutorial projects. I'm trying to do one a day, or at least like every other day. This Arctic Sea Ice Decline map took me around 4-5 hours to make, and I changed it from the instructions because I wanted clearly defined decade chunks rather than a gradient map of ice presence over time lol (also just wanted to see if I remembered how to do it). The tutorial provides data sets to use and it's my job to assemble and analyze the raw data and visualize it using ArcPro into something recognizable.

but yea expect to see more little maps n such I suppose

[ayjadasblogforeverything]

Cardinal-O-Mat Data Science

Soooo I wanted to learn something data sciency. And I stumbled over David Kriesel's Wahl-O-Mat analyses and wanted to do the same but different. I, like you maybe, have stumbled over the cardinal-o-mat. Logical conclusion: Let's do data science without mama (I'm so sorry!) but with the cardinal-o-mat! (Of course, I also have done this with the Wahl-O-Mat.)

The Cluster Heatmap

Here we have a cluster heatmap. (Isn't she pretty? Actually not so much, there's a lot of grey there...)

On the right side, you can see the names of the cardinals, and on the bottom, you can see the names of the theses. (I was too lazy to make them look pretty.) Red means disagree, blue means agree (for colorblindness reasons). Grey means either that the cardinal was explicitly neutral to the question or that there was simply no data on his position regarding the thesis in the cardinal-o-mat.

The theses are as follows (in order of appearance in the cardinal-o-mat):

I'll spare you and not list all the cardinals' names.

female_deacons: Women should be admitted to the diaconate.

same_sex: Same-sex couples should continue to be allowed to receive blessings outside of liturgical celebrations.

celibacy: Priestly celibacy should become voluntary.

vetus_ordo: The celebration of the Old Latin Mass should remain restricted for the sake of church unity.

vatican_china: The secret agreement between the Vatican and the People's Republic of China on the appointment of bishops should be upheld.

synodal_church: The Catholic Church should be a synodal church in which more emphasis is placed on participation, inclusion and joint decision-making.

climate_change: The Catholic Church should get involved in climate protection because it is committed to God's creation and the protection of the most vulnerable.

humanae_vitae: The Catholic Church should reconsider its position on contraception.

communion_unmarried: Divorced and remarried persons should be admitted to communion in individual cases.

german_synode: The German Synodal Way, aiming at reforming the doctrine of faith and morals, should be regarded positively overall.

covid: Church closures and vaccination recommendations during the Covid-19 pandemic were right.

islam: Interfaith dialogue with Islam is important.

What do we see here?

Roughly speaking, the closer two cardinals or two theses are shown in the map, the more similar they are, and the further apart in the map, the more dissimilar. Because of this closeness of similar cardinals/theses, we get these blocks of blue and red (kinda. I mean, it could be much worse.).

I want to emphasize that I did not sort this by hand. Rather it was sorted by an algorithm with respect to a certain metric (here the Jaccard metric), which measures the "distance" between the cardinals and theses. The method used is (divisive) hierarchical clustering. At each step, a cluster is divided into two subsets such that their distance is maximized. You can see these steps in the lines on the top and left side. This is called a dendrogram.

What do we learn from this?

Damn good question! The amount of things to learn is somewhat limited, if we look at the amount of neutrals and non-opinions, also considering I did not seperate those two.

Since this is a non-serious setting, I think we can reasonably infer that a cardinal that has spoken in favor of a couple of the theses is also generally more open to those he has not voiced an opinion on, and similarly for the conservative ones. If you look at it like this, then it becomes quite clear that the blue, so the generally more open minded cardinals are in the majority. I would have loved to have a cardinal-o-mat for the previous conclave, because I have the hypothesis that there, the conservative cardinals might have had the majority and I would love to test this.

Something I find funny is that one of the theses that is most liked is the synodal_church one, which is about participation and joint decision making. One of the least liked ones is the german_synode one (only one agreement, thx Marx my homie), which tries to do exactly the participation and joint decision making.

I don't know what else we learn from this, I just think that a cluster heatmap is a neat way of visualising the positions of the cardinals wrt to the theses and since it is somewhat sorted, we learn something about their relation with each other.

If you can explain to me why there is this red block in the left bottom corner, please do! I thought it might have something to do with the metric I used but the map always looks similar or worse.

Also, maybe someone can explain to me which metric to use when.

[bidotorg]

It's #BiScienceFriday and today we're doing a deep-dive into some delicious data!

[altin-studies]

one churro with chocolate sauce (๑ᵔ⤙ᵔ๑)

30 December 2024, Monday

Uni diaries II day 51/-

Mondays are low effort days. Today I-

Prayed 5/5

Had a nutritious breakfast but late lunch and no dinner

Attended 3 classes

Helped make club poster

Went printer servicing (need new cartridges)

Bought new earphone (⁠•⁠‿⁠•⁠)

Read for 1+ hour (Proven Guilty by Jim Butcher)

Walked 4.5k steps

Slept well (7 hours)