Have you not learned how to wipe your ass?
So, when I was sub-250lbs, I never, ever got poop on my hands. Then once I hit 250 I got poop on my hands maybe once a week. Now at 280 I get poop on my hands almost every time I use the restroom, and I was just wondering if any other larger guys experienced this? I assume it's due to a lack or mobility combined with additional trunk/torso girth, rendering me less effective in the wiping situation.
Have you not learned how to wipe your ass?
Is this a Sticky?
Ha.
What do you think Coan was talking about when he cued people to “open their taint?”
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A more detailed and comprehensive treatment may be warranted, although Coach Broggi has made a useful video contribution on the topic:
How to Use the Bathroom | Grant Broggi
Coach Rippetoe videos twice have addressed the paper over/under question (spoiler alert: "over", at 0:11), and appears to favor folding, rather than wadding:
Ask Rip #12 | Starting Strength Channel
House Arrest Skills - How to Install Your Toilet Paper Roll with Mark Rippetoe - YouTube
We look forward to additional videos!
The free market has already solved this problem:
https://www.amazon.ca/Toilet-Tools-C...36491557&psc=1
Rip, it seems your two-factor model is taking hold in that other kind of training - of statistical algorithms upon data.
It is now recognized that, for a given domain of data (e.g. visual images), that an algorithm's behavior consists of a task-independent part (e.g. discerning the objects in an image) and task-specific part (e.g. answering whether a pictured squat is to depth or not). Training the first part (in the parlance, "pretraining" or "self-supervised learning") is very time consuming. The second part ("fine-tuning") is less taxing, but does require examples of the input-output behavior to be mimicked ("supervision").
This bifurcation arose from practical considerations: there are only a handful of organizations with the computational resources to perform the first step, and there is limited "supervision" to guide the second step. But now, some researchers think there's something more fundamental about the split.
In short, the modern practice of artificial intelligence / machine learning has technical analogues to strength (which improves all downstream tasks) and independently-performed strength training - even though the training of organisms and the training of algorithms are seemingly unrelated. And yes, I'm posting in this thread, which needs serious help.