Conceptual notes are made during the analytical reading of a book and "give answers to questions about the truth and significance of the book."

This distinguishing factor is a more useful one than those in other systems.

Compare this with the idea of Beatrice Webb's "analytic notes" versus "synthetic notes" or "scientific notes" which she describes in My Apprentice (1926).

see: - https://hypothes.is/a/Fb3Y4Au1Ee2p_sdveWOJKw - https://hypothes.is/a/WGPrOAoOEe2WJV9yx2SVZg - https://hypothes.is/a/2gdRwgoMEe2mdccJDX6zTw

Web considers "analytic note taking" to be the raw data collection and arrangement (in the same vein of creating databases in the computer science space, which didn't exist when she did her work) upon which historical work is based.

She views "synthetic notes" as observations of behaviours and writings which probably more closely resembles the idea of "literature notes" (Ahrens) or "source notes" (Allosso). Some of the difference is that she's viewing her notes as a tool for her particular work (sociology) rather than as a broader enterprise which might be used in all fields.

Webb's synthetic notes are also likely bound up in her idea of Herbert Spencer's "synthetic philosophy" of thinking, which may require some more reading of these sections on my part to better distinguish her specific meaning.

Webb didn't seem to have a version of "permanent notes" in her conceptualization. Perhaps this is an indication that the evolution of the note really only occurred as it was placed into published writing. This may potentially preclude the reuse of the evolved ideas unless they are separately re-subsumed into one's note collection.

Ahrens' conceptualization of the zettelkasten has all the writing, revision, and evolution work occurring in the slip box itself so it's always available and reusable. Many modern note taking and writing systems would seem to elide this part. (Is this true in practice? Can we provide examples?)

A great analytic resource!

Mazumdar, S., & Thakker, D. (2020). Citizen Science on Twitter: Using Data Analytics to Understand Conversations and Networks. Future Internet, 12(12), 210. https://doi.org/10.3390/fi12120210

https://www.mdpi.com/1999-5903/12/12/210

Sulik, J., & McKay, R. (2021). Studying science denial with a complex problem-solving task [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/huxm7

Erlich, A., Garner, C., Pennycook, G., & Rand, D. G. (2021). Does Analytic Thinking Insulate Against Pro-Kremlin Disinformation? Evidence from Ukraine [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/4yrdj

Steven Goodman: Statistical methods as social technologies versus analytic tools: Implications for metascience and research reform (Video). (n.d.). Metascience.com. Retrieved 2 September 2020, from https://metascience.com/events/metascience-2019-symposium/steven-goodman-statistical-methods-versus-analytic-tools/

Hohn, R. E., Slaney, K. L., & Tafreshi, D. (2020). An Empirical Review of Research and Reporting Practices in Psychological Meta-Analyses. Review of General Psychology, 1089268020918844. https://doi.org/10.1177/1089268020918844

Martel, C., Mosleh, M., & Rand, D. (2020). You’re definitely wrong, maybe: Correction style has minimal effect on corrections of misinformation online. https://doi.org/10.31234/osf.io/w3tfb

Parsons, Sam. ‘Reliability Multiverse’, 26 June 2020. https://doi.org/10.31234/osf.io/y6tcz.

Shane, Matthew S. ‘The Motivation to Empathize Scale - Indexing Virtuous and Nonvirtuous Motives to Empathize’, 9 June 2020. https://doi.org/10.31234/osf.io/e7gxu.

Cavojova, V., Šrol, J., & Mikušková, E. B. (2020, April 15). Scientific reasoning as a predictor of health-related beliefs and behaviors in the time of COVID-19. https://doi.org/10.31234/osf.io/tfy5q