[jerf]

"The article author suggests that the Korean laws may not have gone far enough."

That's a really scary line of logic though. "We did a thing, and there was no effect. We propose that to obtain the desired effect we should do even more of the thing that had no effect."

That's undisprovable.

It's possible that doing the thing that produced no results even harder could have some positive effect, but the world is probably even more full of things that produced no results but if pushed harder will have negative effects. Part of being a real scientist is acknowledging that this can only be interpreted as evidence against the idea that forcing shorter work hours will make people happier, no matter how cognitively or emotionally challenging it is. That's being a scientist.

(To forstall the two obvious replies: Consider the difference between the words "evidence" and "proof". And once again, let me underline the scientific dangers in "We tested for X->Y and found no evidence for it, but we're still going to assert that X->Y." This logic doesn't just apply to "work hour reduction", it applies to all null results, of all kinds.)

[Goronmon]

>That's a really scary line of logic though. "We did a thing, and there was no effect. We propose that to obtain the desired effect we should do even more of the thing that had no effect."

Is it scary? I mean, if I go from getting no exercise to spending 30 seconds a day exercising, but see no change in my weight, should I therefore conclude that exercising is pointless? Or should I try exercising more and also maybe be more careful with my eating habits?

I think the scary thing is when people try to take complicated subjects and distill them down to shallow talking points.

[spindritf]

You cannot simply extrapolate from smaller intervention but it does lower the prior for a larger one, of course. Maybe unless you have a specific hypothesis which predicts a non-linear effect.

Also, exercising will actually do very little for your weight because calories have became too cheap and readily available to burn them off. You can eat more by accident than you will use in a fairly vigorous workout.

[Bahamut]

That is not how a true scientist thinks. Effects are not necessarily linear. For example, in order to see some effects in quantum mechanics, a threshold must be passed. Or in physics, a certain amount of force to overcome the minimum threshold as a result of friction.

Problem solving isn't such a simple operation. One must be careful with logic.

[jerf]

See my other post. You are not entitled to simply leap to the conclusion that because we did not see a predicted effect, that we must have simply not reached the threshold. There is still the distinct possibility that we're entirely wrong about what will happen if we increase the input.

Basically, everybody here is not thinking with their science hats. They are thinking with their social engineering/political hats, where a government action to forcibly reduce working hours simply must have positive benefits, essentially axiomatically, and if we're not seeing them yet we must simply not be trying hard enough yet, a classic social engineering mindset. But that's not a scientific mindset. There's no guarantee this intervention must have positive results. There's no guarantee the axiom is actually true.

[eropple]

> It's possible that doing the thing that produced no results even harder could have some positive effect, but the world is probably even more full of things that produced no results but if pushed harder will have negative effects. Part of being a real scientist is acknowledging that this can only be interpreted as evidence against the idea that forcing shorter work hours will make people happier, no matter how cognitively or emotionally challenging it is. That's being a scientist.

Real science, huh? A mild change in X did nothing, so you should assume a major change in X will do nothing?

Ever looked at a reaction graph?

[josinalvo]

If you are testing A vs notA, and you exclude some scenarios in which A is true (and dont exclude anything else), that is (by definition) evidence for notA and against A. (at least by a bayesian definition)

Now, might be that the priors for A were very large, and A is still the most likely hypothesis. But the evidence just received reduced those priors

-----------------

(I know that the case in point does not fit the rather strict requirements of the first paragraph. But I think the affirmation "the hypothesis that reducing the workload improves the life of the worker, while still very likely, is now a bit less likely" is true in this case.)

(The phrase in " " sounds odd to me. If I knew numbers, it would be much better to say P(A) was 95% and now is 90%)

[jerf]

"A mild change in X did nothing, so you should assume a major change in X will do nothing?"

Wrong direction. We are not entitled to take a result that a minor change had no effect on the target variable and treat that as evidence that a major change must do the thing we expect it to do. We must accept this as evidence that in fact the major version of our change will, at the very least, do something other than what we expected; our theory made predictions and our theory predicted wrong. This is not a thing to be glossed over lightly! Forcing further reductions in hours may very well have some other net-negative benefit, for instance.

You are all, frankly, making exactly the mistake I'm talking about, and doubling down on it.

[brudgers]

A more charitable reading of the comment might have taken the phrase "not have gone far enough" in terms of the policy achieving its objectives. Regulating work hours was the means, not the ends.