Jakob Ortmann
@jakobortmann.bsky.social
160 followers 240 following 25 posts
Philosophy of Science, Evidence Based Policy, Philosophy of Social Sciences @Hannover. Doctoral research fellow at @mapsproject.bsky.social jakobortmann.com
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jakobortmann.bsky.social
Note: NATO spending targets refer to *public* spending, where as CC mitigation refers to *total* spending. So if we only compared public spending, this chart would look even more extreme.
jakobortmann.bsky.social
Putting spending targets into perspective serves as one of the most important reminders of this decade: climate action is possible, cheaper than usually framed as, and definitely cheaper than inaction.
jakobortmann.bsky.social
Determined climate action turns out really cheap in comparison. Among other things, this makes the opportunity costs of conflict stupendously gigantic - not even talking about matters of justice here.
jakobortmann.bsky.social
Here is a quick thought: The new NATO 5% spending goal may not sound like too much, but its actually much more than we would have needed to fix climate change (estimates from 2018) - see chart below.
jakobortmann.bsky.social
⏳Deadline approaching! Know any early-career scholars working on philosophy of econ or values in science? Please consider forwarding them our call for proposals at phil-econ-model-lab.org. We are assembling a group of young scholars to collaborate at the cutting-edge of these topics #philsi #econ
A screenshot of the website phil-econ-model-lab.org
Reposted by Jakob Ortmann
mapsproject.bsky.social
We are pleased to invite you to the MAPS Symposium, taking place on June 4 and 5, 2025, at Koniglicher Pferdestall. Attendance is free and open to all. We have a great lineup! Join us for two days of engaging discussions and critical reflections.
jakobortmann.bsky.social
My Performative Paternalism paper is out now - looking forward to hear your thoughts, concerns, and whatnot. Its an attempt of cashing out some of the ethical / political issues surrounding performativity of science that seem really important, yet underdeveloped in the current literature.
jakobortmann.bsky.social
Oh what an honour! Wishing them luck for the final push
jakobortmann.bsky.social
Thanks Anna! You're exactly right - thats where it started. Indebted to many brilliant people at Cambridge HPS.
jakobortmann.bsky.social
Delighted to share my first contribution to the @mapsproject.bsky.social project got accepted for publication in the EJPS! It revises epistemic & normative arguments reg. performativity of science (e.g. self-fulfilling prophecies), and reaches an uncomfortable conclusion: performative paternalism!
philpapers.org
jakobortmann.bsky.social
Today I learned that at some point our department wasn’t allowed to have any books bc books are a fire hazard. Funny enough to ban books at a uni, but I wish they said the same thing about all the paper forms they make us print, fill and sign (and then of course scan again).
jakobortmann.bsky.social
Lots of interesting problems to solve there!
jakobortmann.bsky.social
This project was kicked-off by a great paper by @inkerikoskinen.bsky.social, which I recommend reading. While social epistemology talked about opacity & trust for years, debates on AIs got major attention for (seemingly) the same issues, but without much interaction to social epistemology.
jakobortmann.bsky.social
Happy to share a new paper of mine got accepted by Synthese!
philpapers.org/archive/ORTO...
philpapers.org
Reposted by Jakob Ortmann
becklukas.bsky.social
CfP: What is the appropriate role of climate economics in decision-making and climate policy? What role do value judgments play in its models and methods? How does it relate to other disciplines?
If you have answers, submit them to our topical collection for the EJPS: philsci.eu/Phil-Climate...
European Philosophy of Science Association (EPSA) - Philosophical Perspectives on Climate Economics
philsci.eu
jakobortmann.bsky.social
Busy here discussing a great paper by @inkerikoskinen.bsky.social on the intersection of social epistemology and AI in science! Recommend: doi.org/10.1080/0269...
jakobortmann.bsky.social
True! But this still makes it consistent with a subset view in the sense that quant. evidence is special qual. evidence that by virtue of its special features has diff properties. Qualit. data already contains these relations, they are just not as cashed out. Quantification as a form of compression.
jakobortmann.bsky.social
(e.g. word count (number), mentioned X (boolean), said Y is important (boolean), etc.)

Sorry, this got longer than expected!
jakobortmann.bsky.social
For practical reasons, this context is often stripped away and you end up with data that looks and feels quantitative. But the other way works, too! An interview comes with a lot of context, but requires further processing if you wanted to squeeze some of its information in numeric data types
jakobortmann.bsky.social
(„I went to the machine and read of this value from the display, interpreting it such and such, not sure if something was off though and I went and asked my friend“; „Procedure X spat out this Excel sheet“).
jakobortmann.bsky.social
All of them are qualitative for two reasons: 1. your reason: even a simple quantitative boolean requires interpretation, just like a long-form text does. 2. if you add the context back to „raw“ quantitative data, you can turn every quantitative datum into data that also looks and feels qualitative.
jakobortmann.bsky.social
lending it to certain types of analysis. For example, you can easily aggregate number types (sums, medians) but cant do that with qualitative interviews.
jakobortmann.bsky.social
Numeric data types (or booleans, or timestamps, or geospatial types, etc.) are typically (and meaningfully) referred to as quantitative because they are different from (longer) text, audio or image data, in the sense that they require different ways of processing,
jakobortmann.bsky.social
Thanks for asking! I will need to think about this harder, but my hunch is that quantitative data is qualitative data stripped away of certain information (e.g. contextual information) for some purpose (e.g. to fit into a (database) schema; or to make it useful for a certain type of analysis, etc.).