Most of Sanskrit literature is two copies from extinction

Status: Anticipated · untested

Status is derived only from the shepherd-authored triage/prediction data above -- community submissions and claims are a separate overlay and can never change it (see the participation panel below).

This is a proposed connection between two domains, generated by a language model. It is not an article and not evidence: it sits below the evidence/publication boundary. A quantitative prediction and a named kill-dataset are attached (when registered) so the claim stays falsifiable rather than merely evocative.

Claim (verbatim)

The famous millions of South Asian manuscripts hide a simpler and more dangerous statistic: how many copies each distinct work survives in. A recopying economy driven by curriculum and ritual demand should concentrate copies on a small canon while leaving the long tail of works at one or two witnesses — a heavy-tailed copies-per-work distribution of the kind bibliographers find for European incunabula. If so, the survival of the corpus is far more fragile than the raw manuscript count suggests, and unseen-species statistics applied to the copy counts can estimate how many works have already vanished without a trace. The subcontinent's textual wealth would then be an inventory problem with a computable extinction rate, not an unfathomable ocean.

Prediction clause (verbatim)

In the NGMPP/NGMCP catalogue, the copies-per-distinct-work distribution will be heavy-tailed, with more than half of all distinct works attested by only one or two manuscripts while the top 5% of works account for over 40% of manuscripts; a Chao-type unseen-species estimator applied to these counts will imply at least as many works wholly lost as extant. Primary clause: more than half of distinct works have one or two copies; the estimator clause is secondary.

Kill-dataset (verbatim)

NGMPP/NGMCP catalogue records deduplicated to work level (using the Pandit database for work identity), with the copy-count distribution and richness estimators computed directly on the result.

Nobody has run this test. The kill-data is named above. If you can run it — or you know the paper that already settles it — claim the kill or submit the prior. Kills and priors are credited here, by name, as they come in.

In the atlas

This conjecture is bridged, as an L1 lead, onto these Inferpedia subject pages.

Provenance

Run: Fresh agent generation · model: claude-fable-5

Generated blind in a single Write with no reads, web access, or database queries; this is the second attempt for wave W14 after a prior instance died to a network error before writing its packet.

Novelty / leakage triage

anticipated in the literature — this exact test has never been run

The heavy-tailed copies-per-work distribution + unseen-species (Chao1) loss estimation is a published method for medieval European literature, but has not been run on the NGMPP/NGMCP South Asian corpus deduplicated to work level.

Kestemont et al., 'Forgotten Books: The application of unseen species models…', Science 375 (2022)

Predictions

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