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.
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