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Aella
@Aella_Girl
To me, it's obvious that limited data is better than no data, and you interpret it in context, evaluate theories for why you got that data (including stuff like sampling bias, etc.) But I'm starting to suspect most people view data as being a binary support or not of a view?
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Aella
@Aella_Girl
like, to me I can publish a little bit of data and I just default assume everyone knows that I'm not drawing hard conclusions from it, it's just a piece of evidence we can discuss, but people often respond like I think I'm making a bold, irrefutable claim about reality
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Aella
@Aella_Girl
which... feels a little startling to me. Should I start placing "I'm not definitively assuming anything from this data, a little data is better than no data" disclaimer at the beginning of everything? I just had assumed sharing the sample size and source was serving that function
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Travy
@travontayjones
Replying to
@Aella_Girl
Collection of a specific dataset requires some underlying motivation related to the specifics of the data set, unless you’re an AI that chooses to collect the specific data based on random number generator.
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O5-11 “METATRON”
@NightCoffee365
Replying to
@Aella_Girl
No matter how large a conceptual obstacle course you build someone will still find a way to leap straight to a conclusion. Surface readers gonna surface read. I think your data driven work is great and I’ve never seen you misrepresent the scale.
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z🏎️ Chip Thien
@theMacroChip
Replying to
@Aella_Girl
Not sure what instances you are referring to we've shared and acted upon n=1 data since the dawn of time. Therefore, our default is to internalize and draw conclusions on data. The less formal the presentation of the data, the more likely you will need to add disclaimers