I would suppose that if one had better model of traction control then soaps would not slip from hands. Jugglers are doing grabbing very accurately. Trying to grab 3 objects at once as a non-juggler will result in one of the objects slipping away largely because the object tracking is overwhelming.
I think my model for soap is approximately as detailed as my models for rocks or sticks, but the soap remains harder to pick up. That seems like a fact about the soap, rather than about my model of the soap.
If one is slipping on a ice road its too much speed for the driving conditions. On the other hand its possible to drift even on hot dry asphalt. A stun driver might burn rubber but have centimeter control to make the car go exactly where he wants. Intoxicated people slip more for standard walking tests (an DUI has different people have different control levels on the same environment so that seems to be a property of the drivers rather than the roads). You can also break from run to a stop by sliding on your two feet (for example on a gravel road). When you do this you are not often called to be “slipping”.
Also freudian slips are called slips. Usually the formed words are perfectly understandable ie fully pronounced. A lot of slip words are not challenging on the basis of their letters. And for example japanese people slipping more on english R and L is not really a property of the letters themselfs as other nationalities “grip” on them more strongly.
Extending the analog made me realise that “optimal gripping” that John Vaervake is so much a fanboy of, fits the pattern. And in that vein of memes, having arguments whether a feature is subjective or objective can be confusing if the phenomenon in question is transjective. Whether a being can effectively relate to a feature of the world depends upon the shape of both. “Slip” in this picture can be thought of as ineffectualness or wastefulness in the relatedness, an inferior stance for which a better relationship exists and is known.
I no longer believe that I understand what point you are trying to make, but a few remarks that each seem relevant to at least one of those examples:
Slipperiness is a continuum, not a binary trait.
Slipperiness is just one factor that affects your probability of success. For instance, a skilled ice-skater has less chance of falling down than a newbie, but a given patch of ice is equally “slippery” for both. (As I use the word.)
I could buy that slipperiness is a function of two surfaces interacting, rather than something that a single surface can unambiguously be said to possess. (Though knowing just one of the inputs seems to provide a lot of information about the output; e.g. wet soap is unusually slippery when combined with lots of other surfaces, not just a few.)
All of the above seem to me to be fully compatible with my original model of slipperiness as a control problem rather than a modeling problem. Climbing a steep hill is harder than climbing a gentle slope for reasons that have nothing to do with epistemology. Climbing a slippery hill is also harder for reasons that have nothing to do with epistemology.
You think it is more important to emphasise the control problem and I think that modelling is better / there is no need to priotise control. Its going to be coupled because control will utilise feedback so its hard to tease appart.
In principle I could look at the sole of my shoe with a microscope and do the same for the ground. However often I decide not to gather this information (which is a quite sensible decision) and choose to be ignorant about the microstructures. Rather I use a quick sketch of guess of the statistical properties. The cost of the ignorance is that reality does take the details into account, so in that aspect I lose (partially) track of reality. Unexpected behaviour is when that model leakage becomes apparent to me.
With the iceskating it provides a very clear example of a clear surface between metal and ice burshing against each other. This is where slipperyness should shine but if the skater retains control we don’t call this slipping. There is also the phenomenon where the ice unexpectedly lacking in slipperiness can make a skater trip (slips due to stickyness have their own unique name). I am really not exited about the concepts that would asssign “inherent difficulty” to parts of terrain so easy/hard not a fan of (stuff like friction coefficients are real though). With ice for example a skater can travel unhindered in smooth ice and has trouble covering bumpy ice while a pedestrian maintains easy access in bumpy ice and slips on smooth ice. This is a counterexample on newbie vs pro iceskater.
I would suppose that if one had better model of traction control then soaps would not slip from hands. Jugglers are doing grabbing very accurately. Trying to grab 3 objects at once as a non-juggler will result in one of the objects slipping away largely because the object tracking is overwhelming.
I think my model for soap is approximately as detailed as my models for rocks or sticks, but the soap remains harder to pick up. That seems like a fact about the soap, rather than about my model of the soap.
If one is slipping on a ice road its too much speed for the driving conditions. On the other hand its possible to drift even on hot dry asphalt. A stun driver might burn rubber but have centimeter control to make the car go exactly where he wants. Intoxicated people slip more for standard walking tests (an DUI has different people have different control levels on the same environment so that seems to be a property of the drivers rather than the roads). You can also break from run to a stop by sliding on your two feet (for example on a gravel road). When you do this you are not often called to be “slipping”.
Also freudian slips are called slips. Usually the formed words are perfectly understandable ie fully pronounced. A lot of slip words are not challenging on the basis of their letters. And for example japanese people slipping more on english R and L is not really a property of the letters themselfs as other nationalities “grip” on them more strongly.
Extending the analog made me realise that “optimal gripping” that John Vaervake is so much a fanboy of, fits the pattern. And in that vein of memes, having arguments whether a feature is subjective or objective can be confusing if the phenomenon in question is transjective. Whether a being can effectively relate to a feature of the world depends upon the shape of both. “Slip” in this picture can be thought of as ineffectualness or wastefulness in the relatedness, an inferior stance for which a better relationship exists and is known.
I realize this is not the most important point but man I love that your name is Slider and you’re having this convo.
I no longer believe that I understand what point you are trying to make, but a few remarks that each seem relevant to at least one of those examples:
Slipperiness is a continuum, not a binary trait.
Slipperiness is just one factor that affects your probability of success. For instance, a skilled ice-skater has less chance of falling down than a newbie, but a given patch of ice is equally “slippery” for both. (As I use the word.)
I could buy that slipperiness is a function of two surfaces interacting, rather than something that a single surface can unambiguously be said to possess. (Though knowing just one of the inputs seems to provide a lot of information about the output; e.g. wet soap is unusually slippery when combined with lots of other surfaces, not just a few.)
All of the above seem to me to be fully compatible with my original model of slipperiness as a control problem rather than a modeling problem. Climbing a steep hill is harder than climbing a gentle slope for reasons that have nothing to do with epistemology. Climbing a slippery hill is also harder for reasons that have nothing to do with epistemology.
You think it is more important to emphasise the control problem and I think that modelling is better / there is no need to priotise control. Its going to be coupled because control will utilise feedback so its hard to tease appart.
In principle I could look at the sole of my shoe with a microscope and do the same for the ground. However often I decide not to gather this information (which is a quite sensible decision) and choose to be ignorant about the microstructures. Rather I use a quick sketch of guess of the statistical properties. The cost of the ignorance is that reality does take the details into account, so in that aspect I lose (partially) track of reality. Unexpected behaviour is when that model leakage becomes apparent to me.
With the iceskating it provides a very clear example of a clear surface between metal and ice burshing against each other. This is where slipperyness should shine but if the skater retains control we don’t call this slipping. There is also the phenomenon where the ice unexpectedly lacking in slipperiness can make a skater trip (slips due to stickyness have their own unique name). I am really not exited about the concepts that would asssign “inherent difficulty” to parts of terrain so easy/hard not a fan of (stuff like friction coefficients are real though). With ice for example a skater can travel unhindered in smooth ice and has trouble covering bumpy ice while a pedestrian maintains easy access in bumpy ice and slips on smooth ice. This is a counterexample on newbie vs pro iceskater.