How to detect a plausible interpolation? Part – 1 of 5

Ancient Indian literature has interpolations and also transliteration/transcription errors.
This is a trivially true statement.
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What can a researcher do to identify, deal with, and work around these errors or insertions?
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Step -1
First and foremost, and ONLY as a first approximation, treat ‘it’ as authentic and factual. Make sure that casual and careless opinions, of experts, authorities, Gurus, university chairs and friends, do not influence you otherwise.

Assumption:
It is fair for me to assume that you are trying to solve a problem and to solve the problem, you have proposed a theory and this specific reference (observation, statement, assertion) from ancient Indian literature is either corroborating or conflicting with the consequences of your theory.

Step -2
If this is not the case, go back and ask the question why you are discussing if a specific observation from ancient Indian literature is interpolated or not.

Remember:
All (no exception) observations are to be interpreted in the context of a ‘specific’ theory and all theories are generated/proposed in the context of solving a ‘specific’ problem.
So stop wondering if a given observation is ‘interpolated’ or not. First find a problem to solve and then a theory (albeit tentative) to solve that problem. It is good to remember that all theories are tentative and they remain so forever.

Step -3
If a specific observation corroborates with your theory, don’t spend time wondering if that observation is interpolated or not. If your theory is wrong, other observations will falsify it anyways.

Step – 4
If a specific observation does not corroborate your theory, either your theory is wrong or that observation is either interpolated or has transliteration/transcription error(s).

Step -5
Continue testing rest of observations against the consequences predicted by your theory. Make a list of observations that were not corroborated by your theory.

Step – 6
If you end up with many observations (What is many depends on total number of observations relevant for your theory) that are not corroborated by your theory, consider revise/modify your theory or propose altogether a new theory. Repeat steps 3-6

Step – 7
At this point, one would have a small set of observations that are not corroborated by one’s theory.
While we will never know for sure if a certain observation is interpolated or not, there are few methods that we can apply to each such ‘plausibly interpolated’ observation.

We will discuss some of these methods in next part(s) of this series.

To be continued…

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