"The study failed to replicate" is something I often hear, usually with the implication the original study must have been bad, or had something wrong with it. This is a bad misunderstanding of what failure to replicate means.
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It's worth noting: some Western scientists thought this meant the Russian results were wrong. Turns out it was the Westerners who were wrong. (The Q of sapphire was a hot topic, as it was thought to be relevant for the detection of gravitational waves. So, not small stakes.)pic.twitter.com/UVP36d9eVw
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A tempting response is to say "Oh, the paper should have included more detail." But first-rate experiments often include a mindboggling number of details that have to be gotten right. Figuring those out is (rightly) the decades-long task of an entire community doing followup work
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If you don't believe this, look at the miniscule details Collins paper on the Q of sapphire. Or write out a list of all the possible noise sources in your power supply that might muck up an experiment. (I'll be waiting when your list passes 100 items.)
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The "failure to replicate = bad" narrative is tempting. But it's a dramatic misunderstanding & oversimplification of how science works. I wish people had better mental models, to understand that failure to replicate is often instead merely a step along the way to understanding.
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End of conversation
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Tacit knowledge is not accounted for in software development. We don't know how to capture tacit knowledge. Machine learning seems to capture it. But, only with an explicit view.
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Amazing read! “All this was discovered by trial and error and made for unusual laboratory notebook entries such as, `Suspension 3: Fred-greased Russian thread; Suspension 12: switched from George-grease back to Fred-grease' and so forth.”
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