Come On, Feel the Noise (#72)

Setting the table for an idea exchange with you, my lovely readers.

As I finish the end battle stages of a cursed summer cold¹ - a virus that ultimately wasn’t too bad for the first one in three years, but which completely stole my usual writing time (and energy) from me this past week - I find myself diving into my stash of old drafts for a helping hand for today’s post.

In this case, an unpublished question I had asked myself last fall.

So, with plagued hat in hand, I hope you enjoy this musing - enough to consider adding your own voice in the comments below, as I think it makes for an interesting start for a conversation.²

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In science, and particularly in research, there is a certain way that one is encouraged to share ideas.

Passive, third person, at a distance.

The underlying argument is one should remove as much “noise” as possible from the reader’s interpretation of the events that took the scientist from idea generation to hypothesis building to hypothesis testing. By removing the “noise”, it should be clear to the reader that a certain series of steps was completed, which then led to the results under discussion and further idea generation.

On the surface, this is good. A reader should be able to review the logic and events that led to the outcome, so that they may view it with their own critical lens.

What this cautious approach to science writing also does, though, is completely strip the underlying humanity from the work. And that is a loss.

My argument isn’t that we create new science based on opinion, personal belief, or baseless conjecture - for that’s the trademarked domain of unhinged social media posts by questionable relatives - but that it is impossible to fully understand the experiment without an acknowledgement of the innate biases that colour the choices we make in what we report and how we report it.

We need to move from passive to active to a truly active voice, encouraging authors to go all in and lay their biases on the table for the house’s evaluation. This would provide more valuable information to the reader, shedding light on why a research practice was used or why a topic was prioritized.

One could even argue that more rigour is found in the scientist’s acknowledgement and statement of individual biases, as the reader can determine and evaluate the value.

But what do you think?

How important is it for science to get rid of the “noise”? How much “noise” is the right amount?

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1. And somehow, it’s still thankfully not COVID, according to three rapid tests I’ve done. (Although I acknowledge I may have had it in the past three years and somehow was asymptomatic.)

2. And I came to this determination not under the influence of cold medication, so all errors in my argument are my own and not attributed to pseudoephedrine.