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My writing setup

Recently, after finishing writing a co-authored paper, it turned out that doing references is still absolutely terrifying for some of my colleagues, and I realized that the way I have set up my process is actually much less popular (at least in philosophy) than I realized - hence I thought that sharing what works for me might help some people working in Humanities figure out a process that works best for them. A lot of the things have grown over time, so probably could be simplified in some way, but I’m waiting for another procrastination period to tweak it some more.

In general the process looks like this: I’m writing papers and notes in Markdown using VSCode (previously Atom, before GitHub pulled the plug on the project) with some plugins as my go-to editor, handling citations through Zotero with some plugins, and use pandoc to export to more readable formats and generate citations and sometimes do final tweaks on Overleaf. I’ll go through each step below. The notes should be sufficiently detailed as I intend to use this post also as a reference sheet for my future self!

Reference database

Zotero is probably not that much better from alternatives like Mendeley, for me the selling point was that it’s free, open source, not Elsevier-owned and much more intuitive than Mendeley with which I played for a while and just couldn’t make sense of.

Input of citations is a blast, you can import papers by their DOI, books by their ISBN, arxiv preprints with their IDs and it works hassle-free in like 90% of cases. If you need to add something manually it’s also quite easy, and for book chapters I just add the book through ISBN and then change its type to Book Section and add missing data, like chapter title and authors.

I use one main add-on: Better BibTex for Zotero. This is to keep the citation keys meaningful to me and consistent over time (and different computers), as well as to set an automatic export into a bib file for further steps of the process.

Importantly, I have a single, very large, and a bit private file for references, hence whenever I have to upload it to the journal or elsewhere, I use JabRef to filter only cited entries into a separate library which then gets submitted.

First drafts

Markdown is my go-to choice of a file format, as it is plain-text, future proof format, that makes me quite confident I will be able to access my notes and drafts in a few years time (provided I’ll find them, as organizing files is not my strong suite…). I use the Visual Studio Code for writing, with several extensions: Markdown All in One, Word Count and, crucially, Pandoc Citer for autocompletion of bibtex citation keys (remember to put path to the bibtex file in square brackets in extension settings!).

Pandoc

Whenever I have to share a version of the paper, I’ll process it in Pandoc into a more accessible format, this is pretty straightforward and works out of the box.

Google Docs

The setup so far works for single authored papers. For sharing with others I use mainly Google Docs, which has all necessary tools for collaborative writing (version history, tracking changes, comments). Overleaf might be a way to go here as well, but requires paid subscription for tracking changes.

Overleaf

Given that journals’ LaTeX templates tend to require a very specific setup of LaTeX environment and getting them to compile locally is a pain, I have given up on maintaining a local installation and opted for Overleaf, which works perfectly well out of the box for most purposes. Then I will potentially download the final TeX file to process it with JabRef, as indicated above.

stackedit.io

For collaboration directly on a markdown file, I have been using the online editor stackedit.io, which allows connecting it to Google Drive, where the file is hosted, and has some basic conflict resolution implemented (though I worked in turns and did not test it thoroughly, so no guarantees). Probably Notion can be used as well for this purpose. Both have the

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Counting with cilia: The role of morphological computation in basal cognition research

In this paper (available here), I argue that existing criticism about what is “morphological computation” due to Müller & Hoffmann is in fact a debate on what “computation” is and doesn’t provide much insight into the “morphological” part. I analyze their view to show that it is a semantic approach to computation, and then propose that alternative mechanistic view helps us understand better scientific practices in research fields adjacent to basal cognition, more precisely - research on morphogenesis.

This paper has a quiet, secondary goal, which is to show that basal cognitive processes could be understood in terms of computation. This is important beacuse in my view it streamlines the connection between basal cognition research and computational neuroscience. Furthermore, it substantiates what could be meant by “computational enactivism”, a view that I’m very sympathetic towards, and would love to explore in greater detail in the future.

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Bayesian theories of consciousness: a review in search for a minimal unifying model

This paper (available here) has grown from my attempt to figure out what is “the predictive processing view” on consciousness and realization that not only there are a lot of alternatives, but also they exist parallel to one another, apparently with some of the authors not aware of a lot of the research being done concurrently. So I wrote a term paper charting a map of those approaches and then expanded it into the final form, submitting it to a special issue on theories of consciousness.

In the paper I use the Wanja Wiese’s idea of “minimal unifying models” as a way to frame the similarities which run across alternative accounts of consciousness, stemming from the same theoretical Bayesian core. I argue that what these models have in common is the roles they ascribe to the formal concepts of “precision” and “complexity” of generative models, and I show how each approach (that I was aware of at the time of writing that paper—I have not caught up since) differs in most of the details.

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CogSci 2021 - additional materials

Here you can find link to the poster:

This browser does not support PDFs. Please download the PDF to view it: Download PDF.

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PDF

Work on this project has been funded by the Ministry of Science and Higher Education (Poland) research Grant DI2018 010448 as part of “Diamentowy Grant” program.

Readable size references:

Filimon, F. (2015). Are All Spatial Reference Frames Egocentric? https://doi.org/10.3389/fnhum.2015.00648

Grush, R. (2004). The emulation theory of representation.

Grush, R. (2007). Skill theory v2.0. https://doi.org/10.1007/s11229-007-9236-z

Hohwy, J. (2020). New directions in predictive processing. https://doi.org/10.1111/mila.12281

Laflaquière, A., & Garcia Ortiz, M. (2019). Unsupervised emergence of egocentric spatial structure from sensorimotor prediction. https://arxiv.org/abs/1906.01401

Moser, E. I., Kropff, E., & Moser, M.-B. (2008). Place Cells, Grid Cells, and the Brain’s Spatial Representation System. https://doi.org/10.1146/annurev.neuro.31.061307.090723

Pouget, A., Deneve, S., & Duhamel, J.-R. (2002). A computational perspective on the neural basis of multisensory spatial representations. https://doi.org/10.1038/nrn914

Rorot, W. (2020). Explaining “spatial purport of perception”. https://doi.org/10.1007/s11229-020-02678-0

Wydmuch, M., Kempka, M., & Jaśkowski, W. (2018). ViZDoom competitions: Playing doom from pixels. https://arxiv.org/abs/1809.03470

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SPP 2021 - additional materials

Here you can find link to the poster:

This browser does not support PDFs. Please download the PDF to view it: Download PDF.

</embed>

PDF

Readable size references:

Filimon, F. (2015). Are All Spatial Reference Frames Egocentric? https://doi.org/10.3389/fnhum.2015.00648

Grush, R. (2004). The emulation theory of representation.

Grush, R. (2007). Skill theory v2.0. https://doi.org/10.1007/s11229-007-9236-z

Hohwy, J. (2020). New directions in predictive processing. https://doi.org/10.1111/mila.12281

Laflaquière, A., & Garcia Ortiz, M. (2019). Unsupervised emergence of egocentric spatial structure from sensorimotor prediction. https://arxiv.org/abs/1906.01401

Moser, E. I., Kropff, E., & Moser, M.-B. (2008). Place Cells, Grid Cells, and the Brain’s Spatial Representation System. https://doi.org/10.1146/annurev.neuro.31.061307.090723

Pouget, A., Deneve, S., & Duhamel, J.-R. (2002). A computational perspective on the neural basis of multisensory spatial representations. https://doi.org/10.1038/nrn914

Rorot, W. (2020). Explaining “spatial purport of perception”. https://doi.org/10.1007/s11229-020-02678-0

Wydmuch, M., Kempka, M., & Jaśkowski, W. (2018). ViZDoom competitions: Playing doom from pixels. https://arxiv.org/abs/1809.03470

Read More