Has anyone ever tried to construct cluster maps of essential reads at the cores of all canons together? Ie instead of using terms like “Greek classics”, “enlightenment thinkers”, “critical theory”, “Frankfurt school” just a graph of “people who cite this cite this also”
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The textual territory of the “life of the mind” is bigger than say Bloom’s idea of western canon, but is not infinite, though it would have a long tail. I think a survey with a few 100 titles on it would capture 80% of intellectual background of 3-sigma of moderate/heavy readers.
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I think I’d conduct such a survey in 2 phases.
Phase 1, get survey group to inventory and report self-assessed “best known” books in personal canon. Merge, count, and prune to say 200 titles.
Phase 2, same/larger group is surveyed about the whole list
Then graph/cluster
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Phase 2 survey would be something like a 0-5 scale:
0: never heard of it
1: heard of it
2: Wikipedia gloss
3. Browsed/part read
4. Read casually
5. Read critically, informed by its home tradition/influences
Plus maybe a love/hate bit to capture tribalism for the >2s
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Only constraints: at least 20 years old, max 1 core representative book in the case of genre authors (otherwise this becomes a genre flood)
No restriction to academic ideas of “canonical”... we want to map canons not see through lens of existing dominant brand-name canons
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This would be quite a demanding survey to do right
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Interesting that everybody is jumping to the conclusion that I’m after genealogical maps of writerly influence. No I’m after readerly maps of idea-association. Crowd’s collective headcanon rather than genealogy or intellectual history as reconstructed by scholars of traditions.
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The crowd’s reading/citation maps should not be understood as crude estimates or ersatz versions of writer genealogies or intellectual histories. They are an alt non-Straussian idea of canoncity. One I suspect is more robust and better in key ways. Readerly ethnomethodology.
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If you get a script that scrapes wikipedia's 'Influences' and 'Influenced' lists you could get pretty far in this.
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This is the function of the canon. Posterity has done the filtering for you. IMO, time is better spent on reading, re-reading, and re-re-reading these works than Big Data crunching them.
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