This is so, you can test it yourself if you want
Under your approach, the goal is achieving consensus. Under my system, the goal is to provide replicability and show that it actually works.
I think we have to separate two ideas here.
There’s the data you get from an experiment
There’s the conclusions you can draw from that data.
I would agree that the data does not depend on the calibration of particular people. But the conclusions you get from that data DO need to be calibrated. Furthermore, other scientists may want to do experiments based on those conclusions… their decision to do that will really be based on how likely they think the conclusions are accurate. The process of science is building new conclusions on the basis of those old conclusions—if it’s just about gathering the data, you never gain a deeper understanding of reality.
There’s the conclusions you can draw from that data.
In the word “conclusions” you conflate two different things which I wish to keep separate.
One of them is subjective opinion/guesstimate/evaluation/conclusion of a person. I agree that the calibration of the person whose opinion we care about is relevant.
The other is objective facts/observations/measurements/conclusions that do not depend on anyone in particular. That’s not just “data” from your first point. That’s also conclusions that follow from the data in an explicit, non-subjective way. A study can perfectly well come to some conclusions by showing how the data leads to them without depending on anyone’s calibration.
The answer to doubts about the first kind of conclusions is “trust me because I know what I’m talking about”. The answer to doubts about the second kind of conclusions is “you don’t have to trust me, see for yourself”.
The process of science is building new conclusions on the basis of those old conclusions
I continue to disagree. In your concept of science the idea of testing against reality is somewhere in the back row. What’s important is achieving consensus and being well-calibrated. I don’t think this is what science is about.
In your concept of science the idea of testing against reality is somewhere in the back row. What’s important is achieving consensus and being well-calibrated. I don’t think this is what science is about.
Let’s stop using the word “science” because I don’t really care how we define that specific word.
Let’s change it instead to “the process of learning things about reality” because that’s what I’m talking about. I think it’s what you’re talking about as well, but traditionally science can also mean “the process of running experiments”—and if we defined it that way, then I’d agree that calibration isn’t needed.
The other is objective facts/observations/measurements/conclusions that do not depend on anyone in particular. That’s not just “data” from your first point. That’s also conclusions that follow from the data in an explicit, non-subjective way.
I can’t think of an example where conclusions are proven true from data in a specific, non-subjective way. Science works on falsification—you can prove things false in a specific, non-subjective way (assuming you trust completely in the protocol and the people running it), but you can’t prove things true, because there’s still ANOTHER experiment someone could run in different conditions that could theoretically falsify your current hypothesis. Furthermore, you may get the correlation right, but may misunderstand the causation.
Don’t get too caught up on this example, because it’s just a silly illustration of a general point, but say you made a hypothesis that “An object falling due to gravity accelerates at a rate of 9.8 meters/second squared”. You could run many experiments with data that fit your hypothesis, but it’s always possible that an alternative hypothesis that “Objects accelerate at 9.8 meters/second squared—except on Tuesday’s when it’s a full moon”. Unless you had specifically tested that scenario, that hypothesis has some infinitesimal chance of being right—and the thing is, there’s no way to test ALL of the potential scenarios.
That’s where calibration comes in—you don’t have certainty that objects accelerate at that rate due to gravity in every situation, but as you prove it in more and more situations, you (and the scientific community) become more and more certain that it’s the correct hypothesis. But even then, someone like Einstein can come along, find some random edge case involving the speed light where the hypothesis doesn’t hold, and present a better one.
We just had different goal posts. You learned science as “running an experiment”—I learned science as “Doing background research, determining likely outcomes, running experiments, sharing results back with the community”. That’s why I tabooed the word, to make sure we were on the same page.
Are we in agreements about the basic concept, if we agree that we have two different definitions of science?
Do tell. Where and how did you “learn science” this way?
Throughout elementary and middle school (early education here in the US) through textbooks with diagrams like this
What is the “basic concept”?
That experiments can give you mostly non-subjective data about one experiment, but to draw broader conclusions about how the world works you have to combine the data from many experiments into a subjective estimate about how likely a hypothesis is.
That does not strike me as an adequate basis for deciding what science is or is not.
Words mean different things to different people… as I said, I’m not interested in arguing over the “proper” definition of this word. I’m interested in clarifying the process through which experiments lead to new knowledge about the world. You can call this process “not science” and I won’t argue—it’s not an interesting argument to me.
So, are you saying that the outcome of science is a set of subjective estimates that most people agree with?
I’m not sure… what do you mean by “the outcome of science?”
I think we have to separate two ideas here.
There’s the data you get from an experiment
There’s the conclusions you can draw from that data.
I would agree that the data does not depend on the calibration of particular people. But the conclusions you get from that data DO need to be calibrated. Furthermore, other scientists may want to do experiments based on those conclusions… their decision to do that will really be based on how likely they think the conclusions are accurate. The process of science is building new conclusions on the basis of those old conclusions—if it’s just about gathering the data, you never gain a deeper understanding of reality.
In the word “conclusions” you conflate two different things which I wish to keep separate.
One of them is subjective opinion/guesstimate/evaluation/conclusion of a person. I agree that the calibration of the person whose opinion we care about is relevant.
The other is objective facts/observations/measurements/conclusions that do not depend on anyone in particular. That’s not just “data” from your first point. That’s also conclusions that follow from the data in an explicit, non-subjective way. A study can perfectly well come to some conclusions by showing how the data leads to them without depending on anyone’s calibration.
The answer to doubts about the first kind of conclusions is “trust me because I know what I’m talking about”. The answer to doubts about the second kind of conclusions is “you don’t have to trust me, see for yourself”.
I continue to disagree. In your concept of science the idea of testing against reality is somewhere in the back row. What’s important is achieving consensus and being well-calibrated. I don’t think this is what science is about.
Let’s stop using the word “science” because I don’t really care how we define that specific word.
Let’s change it instead to “the process of learning things about reality” because that’s what I’m talking about. I think it’s what you’re talking about as well, but traditionally science can also mean “the process of running experiments”—and if we defined it that way, then I’d agree that calibration isn’t needed.
I can’t think of an example where conclusions are proven true from data in a specific, non-subjective way. Science works on falsification—you can prove things false in a specific, non-subjective way (assuming you trust completely in the protocol and the people running it), but you can’t prove things true, because there’s still ANOTHER experiment someone could run in different conditions that could theoretically falsify your current hypothesis. Furthermore, you may get the correlation right, but may misunderstand the causation.
Don’t get too caught up on this example, because it’s just a silly illustration of a general point, but say you made a hypothesis that “An object falling due to gravity accelerates at a rate of 9.8 meters/second squared”. You could run many experiments with data that fit your hypothesis, but it’s always possible that an alternative hypothesis that “Objects accelerate at 9.8 meters/second squared—except on Tuesday’s when it’s a full moon”. Unless you had specifically tested that scenario, that hypothesis has some infinitesimal chance of being right—and the thing is, there’s no way to test ALL of the potential scenarios.
That’s where calibration comes in—you don’t have certainty that objects accelerate at that rate due to gravity in every situation, but as you prove it in more and more situations, you (and the scientific community) become more and more certain that it’s the correct hypothesis. But even then, someone like Einstein can come along, find some random edge case involving the speed light where the hypothesis doesn’t hold, and present a better one.
“The process of learning things about reality” is much MUCH larger and more varied than science.
That ain’t where goalposts used to be :-/
We just had different goal posts. You learned science as “running an experiment”—I learned science as “Doing background research, determining likely outcomes, running experiments, sharing results back with the community”. That’s why I tabooed the word, to make sure we were on the same page.
Are we in agreements about the basic concept, if we agree that we have two different definitions of science?
Do tell. Where and how did you “learn science” this way?
What is the “basic concept”?
Throughout elementary and middle school (early education here in the US) through textbooks with diagrams like this
That experiments can give you mostly non-subjective data about one experiment, but to draw broader conclusions about how the world works you have to combine the data from many experiments into a subjective estimate about how likely a hypothesis is.
That does not strike me as an adequate basis for deciding what science is or is not.
So, are you saying that the outcome of science is a set of subjective estimates that most people agree with?
Words mean different things to different people… as I said, I’m not interested in arguing over the “proper” definition of this word. I’m interested in clarifying the process through which experiments lead to new knowledge about the world. You can call this process “not science” and I won’t argue—it’s not an interesting argument to me.
I’m not sure… what do you mean by “the outcome of science?”