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Why should proponents of alternative theories learn accepted science first?


rah

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I must say I find this to be quite an extraordinary statement. Can I ask what, precisely, you meant by "better off"?

That it is not a very good idea to start learning about fringe ideas without having a grasp on accepted models that have stood the test of time. If the idea is completely incorrect and it's your starting point you will spend a lot of time invested in learning nothing.

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I must say I find this to be quite an extraordinary statement. Can I ask what, precisely, you meant by "better off"?

In the sense that one should have some idea of standard accepted physics before looking into more fringe ideas.

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Why?

 

It saves the time and effort of formulating models that cannot possibly agree with how nature behaves. If you have no idea about e.g. conservation of energy, or the second law of thermodynamics, you may come up with some rather fanciful conjecture, but it will all be for naught.

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It saves the time and effort of formulating models that cannot possibly agree with how nature behaves.

 

This argument is based on the assumption that the behaviour of nature is completely descibed by standard accepted physics. This is not the case.

 

It is not possible to determine, a priori, whether any particular model will agree with how nature behaves. It doesn't make sense to state that a particular model "cannot possibly agree" with how nature behaves before testing it. It only makes sense to state that a particular model "cannot possibly agree" with standard accepted physics.

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This argument is based on the assumption that the behaviour of nature is completely descibed by standard accepted physics. This is not the case.

 

Not at all. It is founded on the fact that we do have accepted physics that describes lots of natural phenomena. If one wants to push our knowledge then having a good idea about what we do know is essential.

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Why?

First, you do not want to "re-invent the wheel". Secondly, you would not want to have a theory that contradicts what is well established. Thirdly, you want to take advantage of the accumulated knowledge we have. For instance there are many mathematical principles that one can apply to help construct models, conservation laws and symmetries are a good example of this.

 

It is like trying to write a poetry book before you have even picked up a dictionary.

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You don't want to go against what has been observed. Our best models within their relevant domains match the observations, therefore if you do not agree with the model you do not agree with the universe and the universe always wins.

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You don't want to go against what has been observed. Our best models within their relevant domains match the observations, therefore if you do not agree with the model you do not agree with the universe and the universe always wins.

 

ajb used the phrase "what is well established", not "what has been observed". You've interpreted ajb's phrase to mean "what has been observed" but that's not necessarily correct. There are other interpretations of the phrase "what is well established" in this context.

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This argument is based on the assumption that the behaviour of nature is completely descibed by standard accepted physics. This is not the case.

 

It is not possible to determine, a priori, whether any particular model will agree with how nature behaves. It doesn't make sense to state that a particular model "cannot possibly agree" with how nature behaves before testing it. It only makes sense to state that a particular model "cannot possibly agree" with standard accepted physics.

 

Not at all. It only requires the models we have adequately describe nature within their scope of applicability, and/or that we have collected empirical data about how nature behaves. If a new model contradicts an existing one, and that existing model properly predicts/describes nature, by the transitive property the new model contradicts nature. If a new model disagrees with existing data, it is wrong.

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To become well established it must make accurate predictions of what is observed.

 

What has been observed is not necessarily everything that can be observed. The fact that a model can be used to make predictions does not mean that the model is necessarily a complete description of nature.

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What has been observed is not necessarily everything that can be observed. The fact that a model can be used to make predictions does not mean that the model is necessarily a complete description of nature.

And no one has described them as complete. I even specified with their domain...

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I would state that you need to develop critical thinking skills along with understanding mainstream physics. What also is important, and perhaps even moreso, is to understand why past theories were thrown out as well as the history that went with them. If the history of science shows anything, it is that we tend to go through the same processes when it comes to developing theories. Be careful to consider that even experts don't have the same opinions on the significance of certain results. http://arxiv.org/ftp/astro-ph/papers/0609/0609591.pdf

 

I think what is stated in the following Yale video starting at 14:30 is poignant:

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It only requires the models we have adequately describe nature within their scope of applicability

 

What do you mean by "adequately"?

 

And no one has described them as complete. I even specified with their domain...

 

swansont has stated that if a new model contradicts an existing model, the new model cannot be an accurate description of nature. This implies that the existing model was a complete description of nature.

 

If the existing model is an incomplete description of nature then there is always the possibility of new observations that contradict the model. Hence, there is the possibility of a new model that contradicts the existing model but which accurately describes nature.

 

To state that any new model which contradicts an existing model, cannot describe nature is the same as stating that the existing model is a complete description of nature.

 

There is no complete description of nature. It is not possible to judge the correctness of a model's description of nature by comparing it to another model, unless the other model is a complete description of nature. It is only possible to judge the correctness of a model by comparing it to observations.

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What do you mean by "adequately"?

 

 

 

swansont has stated that if a new model contradicts an existing model, the new model cannot be an accurate description of nature. This implies that the existing model was a complete description of nature.

 

If the existing model is an incomplete description of nature then there is always the possibility of new observations that contradict the model. Hence, there is the possibility of a new model that contradicts the existing model but which accurately describes nature.

 

To state that any new model which contradicts an existing model, cannot describe nature is the same as stating that the existing model is a complete description of nature.

 

There is no complete description of nature. It is not possible to judge the correctness of a model's description of nature by comparing it to another model, unless the other model is a complete description of nature. It is only possible to judge the correctness of a model by comparing it to observations.

The models match the observations in their own domain. Therefore in that domain they can be used to easily critique any new model. There is no requirement for completeness as long as you know the limits of the theory.

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The models match the observations in their own domain. Therefore in that domain they can be used to easily critique any new model. There is no requirement for completeness as long as you know the limits of the theory.

 

Here you are essentially saying "for all behaviours of nature correctly described by the model, the model is a correct description of nature". This is a tautology; it actually says nothing.

 

Your argument does not involve comparing one model to another. The essence of your argument is "if a model is not logically consistent, then it cannot be a correct description of nature".

 

(As an aside, it's worth noting that this is actually an assumption.)

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You're failing to see that models are constrained. Take Newtonian mechanics it works for every day events, that is it's domain (formally this is far more precisely defined). If your model describes something within that domain but disagrees with Newtonian mechanics it's safe to assume it also disagrees with observations because Newtonian mechanics matches the observations.

 

It is a step away from direct comparison with observations because that is significantly more complicated and less available.

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Here you are essentially saying "for all behaviours of nature correctly described by the model, the model is a correct description of nature". This is a tautology; it actually says nothing.

 

No, it's simply a true statement that you are restating without context. Models can either agree with nature or not agree (this being science, we tend to quantify how well they agree or disagree). Defining how you characterize a model does not say nothing, though that accusation does provide an excuse not to address the point.

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