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Should You Always?

Should you always “Trust the Natural Recursion”? Are the research articles always correct?

“Trust the Natural Recursion.” It is a term used in programming implying one have themselves placed trust in previous workers. When you write a recursive function, you are most likely receiving the result of previous invocations of the function. You have to trust that predecessors have done their job correctly and continue adding your part into the overall work. Likewise, the successors will trust your invocations of the function and continue their work.

Why am I bringing this up? Because, likewise, research articles, DRI, RDA, and all sorts of health guides are produced in a similar fashion. A researcher needs to constantly compare and refer to the other people’s works. Sometimes, it is possible that the same exact experiment cannot be reproduced (classic example: Little Albert Experiment due to ethical issues). Thus, the interpretations and discussions are based on the existing data of the past experiment.

But are the research articles and their data always correct that you should undoubtedly trust everything you see? Well mistakes do happen despite papers are usually reviewed and rejected multiple times before publication.

One incident happened in 1985 FAO/WHO reports of EAR of Amino acid requirements. Instead of inputting the EAR value, someone inputted the RDA value for the Methionine + Cysteine column. Nonetheless, no one noticed the mistake. 20 years later, 2005 DRI report took the miscellaneous protein loss into account and established the new AA requirements. Almost all AA requirement significantly increased except Methionine +Cysteine. Thus, the error was finally revealed.

Don’t get me wrong. I am saying don’t trust anything. I just want to say that not because it is a research paper, it is 100% correct. Have independent thinking and make reasonable and educational judgement.

Originally, I was going to write about the decimal placing error for Iron content in Spinach. But there was never any decimal-point mistake according to McGill Office for Science and Society.


Linda J. Wykes’ NUTR 307 Metabolism and Human Nutrition Lecture

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