The Logic of Space and Numbers

MonfortS26

There are many tools to acquire knowledge and provide answers to questions that are obstacles to understanding. There are two main kinds of questions, those that can be answered with observation, and those that can only be answered through the use of logic and subjective probability. This is where I draw the line between science and philosophy. However, logic and probability can be useful in science and philosophical inquiry can still be useful in domains where low rigor is required, even if scientific inquiry is still possible. Further in this writing I will establish a model for determining when scientific and philosophical inquiry based on the degrees of rigor necessary, but for now let’s start in the latter category, philosophical understanding.

When attempting to create a philosophical system of knowledge, one begins by gaining awareness of a problem and asking how that problem can be solved. This creates a question and the semantics of said question must be defined. From here we hypothesize what the possible answers to the question could be. The next step is to assign probability values to each of your answers. There is no formal process for this, the probabilities for unobservable answers must be subjective, but philosophical thought experiments can be helpful in the process. Throughout the process, one should think of different ways the question could be phrased for the sake of finding more specific answers and making the application of probability values easier. This is the process for establishing philosophical axioms. These established axioms can be used in deductive reasoning and need only be changed when they conflict with other existing or newly established axioms in the system. This is my model for philosophical inquiry, next is scientific inquiry.

In order to create a scientific system of knowledge, you start in the same way as the philosophical model. Awareness, leading to a question you desire to answer, with an established meaning that is constantly refined according to the pragmatic maxim. One requirement of this form of inquiry is that the answer be falsifiable. If it is unfalsifiable it is impossible to investigate with science. From there, you determine if any scientific research has been done on the subject. There are plenty of good resources for this step, including google and various search engines focused on scientific research specifically. This research should be evaluated on the grounds of whether or not it comes from a reliable source, and the level of scientific rigor exercised. Different areas of science use different criteria for rigor and this should be taken into account in your evaluation. If there is research done on the matter, ask whether or not it answers your question satisfactorily. If not, or if there is no research done on that specific question, use inductive reasoning to determine what factors might be related to the question you intend to answer and either find secondary data based on previous research using the resources stated above, or collect your own primary data. The methods used for collecting data depend on the branch of science in which the inquiry takes place. Then you use inductive reasoning to establish possible explanations of the phenomenon, using the data collected at the beginning as the premises. At this point, you apply probability values using either the classical, frequentist, or at last resort, subjective methods, to each possible explanation and use kolmogorov's axioms to evaluate the probability that an event arises. The most important aspect of determining probability comes from the ascertainment of the individual probabilities of events. Principles of ascertainability include the ability to have more than 2 probabilities, I.E. more than just true(1) or false(0), the application of frequencies, the coherence in relation to logic and science, and effective use of ampliative inference. Then you develop an experiment to test the most probable explanation. This experiment can either be a thought experiment or a scientific experiment ranging from least rigorous to most. There are 7 kinds of thought experiments, pre factual, counterfactual, semifactual, prediction, hindcasting, retrodiction, and back casting. If the experiment confirms your hypothesis you will develop an axiom based on observations that the rest of the system will rely on, which can be expanded if the domain of the formal system needs to be expanded. Another option, if one desires to add another level of rigor, is to test other hypotheses as well, in order to satisfy the principle of strong inference. If it doesn’t confirm the hypothesis, go back to the observations and pick the next most probable answer and repeat the process. This is the scientific form of inquiry.

The last form of reasoning is intuitive. Intuition is subconscious reasoning and there is not much to write on the subject. The only thing you can do to influence your intuition is to broaden your understanding of the concepts that you are evaluating on a subconscious level. This just amounts to preparing yourself for situations you may find yourself in and is conducted through the use of philosophical and scientific inquiry. Finally we delve into when different levels of rigor are appropriate.

There are three main things to consider when deciding what level of rigor is appropriate. The first one is is time. How much time do I have to learn something, and how long will each strategy take? The next factor is the importance of being right. Are there severe consequences to being wrong about this and am I willing to risk those consequences in order to save time?<(Jeff Bezos' idea) Risk management strategies are very useful with this step. The last is whether or not observation is an option in the answering of the question. Scientific inquiry necessary when you have enough time to conduct it and it is important that you are right the first time. Intuition is necessary when you don’t have time for inquiry or when it is of little importance that you are right. Finally philosophical inquiry is acceptable in all areas that fall in between the reasonable use of intuition or scientific inquiry. The last section of this paper will cover the appropriate times to add to this knowledge.

This system is a basic beginning to formalized reasoning and will constantly grow over time. If one were to accept this as objectively the best way to reason, it would not reach its full rigorous potential. However, if one were to spend their time focused solely on this, it would never actually be used. Standards must be created for the updating of this system. These include, allotted time for broadening the understanding of it, regular questioning of whether or not it could be better while in use, and attention to what may be missing. The main categories of this system that should be studied regularly are rigor, probability, experiments, logic, science, research, statistics, decision theory, risk management, biases, and fallacies.

Is there anything that anyone would think is useful to add to this?

T Clark

Is there anything that anyone would think is useful to add to this? — MonfortS26

This seems unnecessarily complicated. Maybe it would be clearer if you can give simple examples of philosophical and scientific issues addressed by your method.

Also - in my experience application of one of these methods does not start with a question, it starts with an observation, an issue, or a problem. If there is a question, it's "what's going on here?"

Janus

This is the process for establishing philosophical axioms. — MonfortS26

Haven't you already relied on axiomatic assumptions in establishing your particular take on the way philosophical questioning should proceed?

MonfortS26

This seems unnecessarily complicated. Maybe it would be clearer if you can give simple examples of philosophical and scientific issues addressed by your method. — T Clark

Questions like what is the meaning of my life?, or how SHOULD things be as opposed to how they ARE? can't be answered through observation. They can only be questioned in the mind and what I call philosophical inquiry. Questions like what is the half-life of caffeine? can be answered with scientific inquiry.

Also - in my experience application of one of these methods does not start with a question, it starts with an observation, an issue, or a problem. If there is a question, it's "what's going on here?" — T Clark

Yeah, that's a good point, I edited the OP to include that.

MonfortS26

Haven't you already relied on axiomatic assumptions in establishing your particular take on the way philosophical questioning should proceed? — Janus

Yeah, of course. But I can't think of any way to create completely grounded axioms that aren't built upon an infinite regress. Am I missing something?

fdrake

If it helps, I've worked in a few scientific research projects and am a statistician, and not once have I been asked to used Kolmogorov's axioms in a Carnap-ian quest for scientific objectivity. Much more effort is placed on designing appropriate controls and resource efficient experimental designs than anything which resembles 'applied probabilistic reasoning' in the sense you outlined it.

If the experiment confirms your hypothesis you will develop an axiom based on observations that the rest of the system will rely on, which can be expanded if the domain of the formal system needs to be expanded. Another option, if one desires to add another level of rigor, is to test other hypotheses as well, in order to satisfy the principle of strong inference. If it doesn’t confirm the hypothesis, go back to the observations and pick the next most probable answer and repeat the process... Scientific inquiry necessary when you have enough time to conduct it and it is important that you are right the first time.

You very rarely 'get it right first time', experimental effects are often subtle, and strong signals from small data-sets are very often noise.

With regard to 'infinite regress' however, Agrippa's trilemma is always going to highlight faulty reasoning in an architectonic system in some way. But some 'faults of reason' are justified in a way that makes inquiry using those faults of reason irreducible to philosophical reasoning. Science bottoms out in the real world - it deals with real abstractions - in a way metaphysics and epistemology usually don't. For example, metaphysical and epistemic concepts are rarely parametrised or operationalised; they don't need to interface with reality in the same way as scientific thoughts do. Another contrastive case - what would an epistemologist specialising in Gettier do with a survey on people's responses to Gettier Cases?

In my view, good philosophy isn't there to vouchsafe the operations of scientific thought, or to ape scientific thinking in a philosophical register - scientific thinking will continue to happen without philosophy's help. Philosophy at its best is a problematiser, a composite of overlapping and sometimes contrary metaphysical, epistemic, ethical and political intuitions which allow it to ask interesting questions.

MonfortS26

If it helps, I've worked in a few scientific research projects and am a statistician, and not once have I been asked to used Kolmogorov's axioms in a Carnap-ian quest for scientific objectivity. Much more effort is placed on designing appropriate controls and resource efficient experimental designs than anything which resembles 'applied probabilistic reasoning' in the sense you outlined it. — fdrake

That part was more about adding structure to the abductive reasoning in hypothesis formation than it was about designing the actual experiment, but I've never actually done any real research so I probably have no idea what I'm talking about. What do you mean when you refer to much more effort?

In my view, good philosophy isn't there to vouchsafe the operations of scientific thought, or to ape scientific thinking in a philosophical register - scientific thinking will continue to happen without philosophy's help. Philosophy at its best is a problematiser, a composite of overlapping and sometimes contrary metaphysical, epistemic, ethical and political intuitions which allow it to ask interesting questions. — fdrake

Wouldn't that question asking and answering behavior be required for the first few steps of the scientific method? How are you defining philosophy and science?

MonfortS26

Science bottoms out in the real world - it deals with real abstractions - in a way metaphysics and epistemology usually don't. For example, metaphysical and epistemic concepts are rarely parametrised or operationalised; they don't need to interface with reality in the same way as scientific thoughts do. Another contrastive case - what would an epistemologist specialising in Gettier do with a survey on people's responses to Gettier Cases? — fdrake

This is why I separated philosophical and scientific inquiry. Even in cases like normative ethics, which seem to me to be statements based on the way people think the world should be, there is no way to really ground any of the arguments in reality. But there is a way to determine the way things are and build a logical argument guided by your desires to determine the way you think things should be.

fdrake

↪MonfortS26

That part was more about adding structure to the abductive reasoning in hypothesis formation than it was about designing the actual experiment, but I've never actually done any real research so I probably have no idea what I'm talking about. What do you mean when you refer to much more effort?

As in, more thinking time is spent:
(1) Designing experiments that benefit from orthogonality and have block structures which act as controls for various possible effects.
and
(2) Figuring out a good operationalisation of a concept.
than
(3) Reasoning probabilistically about concepts.

This is because: most of the time the ways you can analyse the data are fixed/induced by the experimental design and how variables are operationalised.

Will give a few examples. If you can take repeat measurements from a single person (or thing) to test something, typically you do that because it provides more precise and less confounded estimates of a treatment's main effect. EG: If you're trying to measure how hard a mental ask is to do, the difference between their pupil diameter during the task and their average pupil diameter before it is a good measurement. That kind of thing could only be observed from experimental practice, and whether it's right or wrong depends on the real world and the experimental set up more than the truth of some theory of cognitive load.

Another example is from Freakonomics, people looking at the average donation per donut to take from a basket of donuts in work-places with different median income. The 'abductive leap' in this case is the claim that this is a measure of generosity of people in white/blue collar jobs.

It's also quite common now for people to skip much of the theorising and measuring stages now, and instead to let a computer do most of your thinking for you. The 'abductive leap' when you're using machine learning algorithms are smaller parts of the study than the operationalisation of variables - for example, you choose the set of kernels for a convolutional neural network analysis, then the data 'fits itself', as it were.

Wouldn't that question asking and answering behaviour be required for the first few steps of the scientific method? How are you defining philosophy and science?

I don't know if I could offer a good definition of philosophy or of science. Regardless, there are a lot of differences between the two. The use of probability theory to evaluate hypotheses - not just in the due course of experimental analysis and design - is at best an idealisation of what scientists do. No one thinks in accordance with the Kolmogorov axioms.

sime

This is why I separated philosophical and scientific inquiry. Even in cases like normative ethics, which seem to me to be statements based on the way people think the world should be, there is no way to really ground any of the arguments in reality. — MonfortS26

Even assertions of metaphysics and ethics must be reducible to empirical propositions about how the world really is. For to assume otherwise is to assume that verbal behaviour has non-physical causes.

When a religious person earnestly asserts that "God Exists", to doubt the factual accuracy of what he is saying is in some sense to misunderstand what he is saying. For the only meaningful scientific problem is to ascertain the environmental stimuli that upon interacting with the person's brain provokes his assertion. Thereupon identification of the environmental stimuli, we can interpret the religious person's assertion "God Exists" as his empirical measurement of said environmental stimuli.

MonfortS26

When a religious person earnestly asserts that "God Exists", to doubt the factual accuracy of what he is saying is in some sense to misunderstand what he is saying. For the only meaningful scientific problem is to ascertain the environmental stimuli that upon interacting with the person's brain provokes his assertion. Thereupon identification of the environmental stimuli, we can interpret the religious person's assertion "God Exists" as his empirical measurement of said environmental stimuli. — sime

That's kind of my point. I don't think there is a misunderstanding when the statement 'God exists' is proposed though. Questioning gods existence is only productive through the lens of philosophical inquiry because it is, as far as we know, impossible to test in reality. As you stated though, questioning peoples reasoning in their belief in God and finding its cause is possible to investigate. This is where I draw the line between ontology and meta-ontology. Same with ethics and meta-ethics. It's not possible to find ethical truths because it mostly comes down to an opinion on the way the world should be. It is, however, possible to conduct experiments on why people hold moral beliefs in the first place. Most meta-philosophy is testable but most philosophy itself is not.

T Clark

With regard to 'infinite regress' however, Agrippa's trilemma is always going to highlight faulty reasoning in an architectonic system in some way. But some 'faults of reason' are justified in a way that makes inquiry using those faults of reason irreducible to philosophical reasoning. Science bottoms out in the real world - it deals with real abstractions - in a way metaphysics and epistemology usually don't. For example, metaphysical and epistemic concepts are rarely parametrised or operationalised; they don't need to interface with reality in the same way as scientific thoughts do. Another contrastive case - what would an epistemologist specialising in Gettier do with a survey on people's responses to Gettier Cases? — fdrake

This is a very interesting paragraph. I was having trouble following this whole discussion, but I think this summarizes it very well, although, as usual, you pretty it all up with your high falutin "words" and "ideas." Actually, once I looked all the words up, your language really helped make the ideas clearer. How did we ever live without the internet?

But....I don't think I agree with some of your conclusions.

With regard to 'infinite regress' however, Agrippa's trilemma is always going to highlight faulty reasoning in an architectonic system in some way. But some 'faults of reason' are justified in a way that makes inquiry using those faults of reason irreducible to philosophical reasoning. — fdrake

Maybe I've misunderstood you. To me, justification of faults of reason is philosophy. Epistemology.

Science bottoms out in the real world - it deals with real abstractions - in a way metaphysics and epistemology usually don't. For example, metaphysical and epistemic concepts are rarely parametrised or operationalised; they don't need to interface with reality in the same way as scientific thoughts do. — fdrake

Parameterization and operationalization are philosophy. Epistemology. Interfacing with reality is philosophy. Ontology. Philosophy is the ocean in which the little fishies of science swim.

Another contrastive case - what would an epistemologist specialising in Gettier do with a survey on people's responses to Gettier Cases? — fdrake

Isn't that exactly what people like you, Apokrisis, and others with good understandings of concrete, down-to-earth science bring to the forum? Nothing can make a philosophical argument fall apart faster than application of knowledge about the real world. Also, although I think being a philosopher specializing in Gettier would be a horrible experience, I think if I were one, I would be very interested in the survey.

Really helpful post.

T Clark

This is because: most of the time the ways you can analyse the data are fixed/induced by the experimental design and how variables are operationalised.

Will give a few examples. If you can take repeat measurements from a single person (or thing) to test something, typically you do that because it provides more precise and less confounded estimates of a treatment's main effect. EG: If you're trying to measure how hard a mental ask is to do, the difference between their pupil diameter during the task and their average pupil diameter before it is a good measurement. That kind of thing could only be observed from experimental practice, and whether it's right or wrong depends on the real world and the experimental set up more than the truth of some theory of cognitive load. — fdrake

I'll say it again - experimental design is philosophy. Epistemology. Yes, I'm getting sick of this parallelism. I won't do it anymore. This is something I do all the time in my work as an engineer. In order to do my work credibly, I need to understand and be able to explain what I know and how I know it. I need to be able to justify it. To me, that's not science.

fdrake

↪T Clark

Maybe I've misunderstood you. To me, justification of faults of reason is philosophy. Epistemology.

Hm. I think it's worthwhile figuring out what methodological concerns look like in philosophy discussion, and what methodological concerns look like in a science. Maybe that'll be more informative.

The kind of criticisms someone doing philosophy can level at another's writing:
every fallacy ever, insufficient emphasis on what's seen as a key issue, reframing attempts, parodies, sarcasm, every possible counter-argument. Philosophers can even invent new errors in thought and interpret other philosophical ideas in their light - like transcendental illusions in Kant; how can someone do metaphysics when the kind of necessity that links objects of thought doesn't have to resemble the kind of necessity that links the objects thought about (reasons vs causes etc)? Another related idea is reification, where relationships between people masquerade as relationships between things; like seeing the relationship with a clerk at a kiosk as one of money transfer despite there being a lot more social texture to it. This isn't an exhaustive list.

Philosophers almost have a blank slate to write others' sins on and beat them over the head with.

Experimental science is a little more constrained. Studies can be criticised for confounding, inappropriate sample size or statistical power for the expected effect size, unsatisfied assumptions for any stage of the analysis, poor construct validity (not measuring what you think you're measuring). Imprecise measurements, shoddy error analysis. The general theory behind an experiment can be subjected to a philosophical analysis, but the experimental component of science needs different critical tools. This isn't an exhaustive list.

I think there are also moves a thinker can make in science which are philosophically spurious. Will given an example.

A neuroscientist, Charles Bonnet noticed that people with ocular/retinal or neural pathologies related to vision had a propensity to hallucinate. The hallucinations were purely visual, no other senses were involved. People who had the hallucinations described them as involuntary and occurring seemingly at random, but were more likely to occur when their sufferer was stressed or tired in the evening. From that they were involuntary, Bonnet hypothesised that the hallucinations have more in common with vision alone than with mental visualisation. This was later shown to be the case (somewhat), as hallucinating people with visual pathway damage had neural correlates shown in an FMRI scan which were more similar to people doing ocular tasks than those envisioning objects 'in the head'.

What justifications could Bonnet have ultimately given for his leap of insight? Was there anything logically sufficient from observing the reports of hallucination prone people with ocular damage to force the conclusion that hallucinations are more similar to vision itself than envisioning upon any rational mind? I doubt it, what inspired Bonnet to adopt his conclusion was the disanalogy between envisioning and vision. Specifically, the property of involuntariness that hallucinations and vision share.

The classificatory decision Bonnet made could be represented post-hoc through some formal logical operations, but the thing is Bonnet's decision would have occurred without this translation exercise. Reasoning through loose disanalogies to a generalisation and classification of something is something that's justified for Bonnet but would make for poor philosophical argumentation.

EG the patchwork of his beliefs probably looked something like this:

(1)Bonnet observes reports that people with visual pathway damage hallucinate.
(2)These hallucinations seem and are reported as involuntary.
(3)Envisioning tasks are usually voluntary.
(4)The hallucinations are not a mechanical part of envisioning tasks. (2,3, disanalogy)
(5)The hallucinations are not voluntary. (2,3,4, treating 3 as 'always' rather than 'usually')
(6)Vision can be partitioned into acts of seeing and acts of envisioning.
(7)The hallucinations are seen. (disanalogy with envisioning, 6)
(8)Hallucinations are seen in the same way as ordinary vision. (analogy from 2, 7)

This isn't a logically valid argument, and importantly the moves between steps in the argument aren't done through formal logical entailment - they follow in a rough and ready way characteristic of empirical reasoning of any sort. I think it's more likely that Bonnet had a 'cloud' of concepts similar to those represented in the above list, and that cloud suggested taking the action to hypothesise (8). What would be a fault of reason in philosophy was used scientifically to draw a sensible conclusion.

T Clark

This isn't a logically valid argument, and importantly the moves between steps in the argument aren't done through formal logical entailment - they follow in a rough and ready way characteristic of empirical reasoning of any sort. I think it's more likely that Bonnet had a 'cloud' of concepts similar to those represented in the above list, and that cloud suggested taking the action to hypothesise (8). What would be a fault of reason in philosophy was used scientifically to draw a sensible conclusion. — fdrake

Sorry, and believe me I'm not trying to be difficult, but what you've described isn't part of the scientific method. It's one process for generating hypotheses. I agree, that's not necessarily, or even generally, logical. As I indicated, you've described a process for coming to know something. To me, that means it's epistemology. The scientific method is epistemology. I do this every day at my work and I'm very conscious of it as a process, a set of principles, rules.

For what it's worth, reading your response, I keep thinking - if fdrake says I'm wrong about this, I must be. But it still seems right to me.

fdrake

↪T Clark

I don't think you're being difficult!

I think you're treating method as methodology though. Philosophical analysis of how Charles Button came to hypothesise, correctly, that hallucination was more similar to vision than mental imagery is part of philosophy, maybe part of epistemology or philosophy of science. That's methodology.

The method that the philosophy is talking about isn't a philosophical method, though. Will apply it philosophically and see what happens:

(1) Mystics on PF typically have little to no understanding of science.
(2) Mystics on PF typically believe that their viewpoints are supported by science or are truer to science than science is.
(3) It's pretty likely that someone who's saying their viewpoint (on the level of worldview) is scientific or scientifically inspired is glossing over far too many things. (1,2, observed correlations and analogy)

In some sense 'having a scientifically inspired worldview and glossing over most things' is pretty close to 'having a mystical worldview and little understanding of science', and for me it's a behavioural maxim or equivalence principle between certain styles of posting. I doubt that other people will see such a strong analogy between (2) and (3), but nevertheless the difference in scope. I don't think this is a particularly good piece of reasoning, but I think it's very similar in character - analogical and full of maybe-equivocations maybe-insights - to the 8 pointed one I detailed above. If I spent more time fleshing out its constitutive equivocations, it would be in better standing. I'm just hoping you'll see what I mean.

A suggestive idea might be: methodology is closer to philosophy than method.

T Clark

A suggestive idea might be: methodology is closer to philosophy than method. — fdrake

I always thought "methodology" was just a fancy way of saying "method" that makes you sound smarter. Now, looking it up, I see the difference. I'm going to think about the things you've written and get back to you.

For what it's worth, when I'm at work and trying to understand what I know and how I came to know it, it feels philosophical. I use the same frame of mind and approach I do here.

T Clark

I think you're treating method as methodology though. Philosophical analysis of how Charles Button came to hypothesise, correctly, that hallucination was more similar to vision than mental imagery is part of philosophy, maybe part of epistemology or philosophy of science. That's methodology. — fdrake

I clean up properties with soil, groundwater, and river sediment contaminated by chemicals. Those chemicals cause present or potential future risks to humans or environmental “receptors.” They also may damage other values – e.g. esthetics, usability. When I get involved in a site, there have usually been several or many previous investigations. Those generally involve installation and logging of soil borings and groundwater monitoring wells; collection of soil, groundwater, and river sediment samples; in place and laboratory testing for soil physical properties (strength, permeability, grain size distribution); topographic mapping; laboratory chemical analysis of soil, groundwater, and sediment samples, and more. My job is to take this information and run it through a standard evaluation process:

Identification of a problem and notification
Preliminary data gathering, identify data gaps
Site investigation – see previous paragraph
Risk assessment
Preparation of Site Conceptual Model (SCM)
Establish of Remedial Action Objectives (RAOs) i.e. goals for site cleanup (e.g. reduce risks to human health to acceptable levels and standards to be used to evaluate achievement of goals (e.g. soil cleanup criteria typically expressed as concentrations of contaminants in soil, groundwater, or sediment.)
Identify and evaluate remedial technologies that will achieve the RAOs. Select a remedy.
Designing the remedy
Constructing the remedy
Operating the remedy
Closing the site.

In some ways, the SCM is the most important part of this. A site conceptual model is just a description, image of the site which lays out all the information gathered during the investigations. To me, the most useful way of presenting a SCM is visually, using figures. Data tables are also needed. There will also be calculations e.g. groundwater flow direction and velocity, contaminant degradation rates, averages. On the figures, you can show the locations of the sources of the contamination and how it moves and is presently distributed across the site. You can also show the locations of existing and potential receptors.

The first thing you find when you complete a draft SCM is data gaps, so, if you can convince your client to spend additional money, you go back in the field to collect additional data. More borings, more samples, an updated survey. Then you revise the SCM and go on to the rest of the process.

So, is this method or methodology? During the work, I think about this all the time – where am I in the process, is the SCM adequate for decision making, have I successfully completed this step, what have I left out, how will I use this two steps down the line.

fdrake

↪T Clark

I imagine your bullet points are method, but your post is methodology. Of course, doing things well should teach someone methodological lessons upon reflection. Can it be codified into a flow-chart? If so - it's a method.

Can describe the steps in doing a standard statistical analysis (hypothesis test on model parameters) of some data in a similar way:

(1) Describe data collection method and problem data is being used to study.
(2) Identify derivable statistics for problem and their distributions.
(3) Aggregate derived statistics into a statistical model appropriate for research question.
(4) Model fitting - instabilities? weirdness? go to (1) .
(5) Model checking - violated assumptions? go to (1)
(6) Fit checking - what purpose is the model to be given?
(7) Impact assessment - what does the model mean for the problem at hand?
(8) Interpretive conclusions? Ambiguities? Quantificational results? Improvements for further study?
(9) Return to (2) until all avoidable violations and weirdness have been removed or accounted for and fit is adequate.

The kind of inquiry that looks at commonalities between your list and my list is methodological. The kind of inquiry that our lists describes is application of a method.

T Clark

The kind of inquiry that looks at commonalities between your list and my list is methodological. The kind of inquiry that our lists describes is application of a method. — fdrake

This is a really interesting discussion and it's made me think differently about the issues. When it comes down to it, call it method or methodology, I think they are inseparable, at least for me. What we have been calling methodology is as much a part of my day-to-day thinking about the work I do as is what we are calling method.

Which brings us back to the original point - I think making a sharp distinction between scientific and philosophical questions is artificial.

fdrake

↪T Clark

I agree that sharp distinctions between the two are artificial. But, what kind of things are in scientific thinking but not philosophy and vice versa?

T Clark

But, what kind of things are in scientific thinking but not philosophy and vice versa? — fdrake

Let's see.

Clearly philosophical but not scientific - What is the true nature of reality.
Clearly scientific but not philosophical - What is the structure of DNA.
Both? - What do I know, how do I know it, and how do I know I know it.

Scientific questions can have yes or no answers. Philosophical questions never do. Is that right? Do I really believe it?

Science is about knowing stuff. Philosophy is about the process of knowing. Not sure if that's right either.

I really like statistics. It's so much fun to screw everything up by misusing them and it's so hard not to misuse them. I bought a book once - "Probability, Statistics, and Truth." It turned out to be a pretty standard basic level statistics book, but I really loved, still love, the title. In a way I think it illustrates the point I've been trying to make. More accurately, it evokes the feeling I'm trying to describe - a sense of the philosophicalness of science. Maybe it's because I'm an engineer. Engineering is applied science. Science is applied philosophy. I don't see, feel, how you can really separate them.

fdrake

↪T Clark

Clearly philosophical but not scientific - What is the true nature of reality.
Clearly scientific but not philosophical - What is the structure of DNA.

I'm not sure I agree with this. "How does DNA work?" has an influence on "What is the true nature of reality?", ontology in the broadest sense is the study of being - and it would be very surprising if the structure of (domains of) beings had no influence on the broadest metaphysical questions.

At various points in the history of philosophy, philosophers have sought to answer the broadest metaphysical questions in - and their current epigones would hate this formulation - in an intrinsically reductive way.

The highest questions in Plato are answerable only to ratiocination about abstract ideals.

The highest questions in Aristotle are addressed by appealing to an imposition of form on matter and the categorisation of general types of causes which determine how things unfold; to understand a thing is to understand its categorisation into a pre-developed schema.

Kant and those who followed his Copernican Revolution seem unaware of the irony of seeking the general structure of being in the way minds condition and understand their percepts.

In Hegel too, the understanding of things becomes the understanding of things; through the logico-historical necessity of a developmental trajectory of human consciousness towards greater and greater generality, scope and reflexivity.

In all of these approaches, questions about how things are in the broadest sense turn into questions of a single topic; and human intellect has a privileged role in disclosing the necessities and vagaries of this topic.

Levy Bryant characterises this theme thusly:

Through the Copernican Revolution (Kant's intellectual system), philosophy is rescued of the obligation to investigate the world and now becomes a self-reflexive investigation of how the human structures the world and objects. It is in this respect that philosophy becomes a transcendental anthropology and any discussion of the objects of the world becomes, ultimately, an anthropological investigation. For the object and the world are no longer a place where humans happen to dwell, but are rather mirrors of human structuring activity. It is this that Hegel will ultimately attempt to show in The Phenomenology of Spirit with his famous “identity of identity and difference” or “identity of substance and subject”. If Hegel is able to show that the object, which appears to be so transcendent to and alien to the subject, is ultimately the subject, then this is because the object is already a reflection of the sense-bestowing activity of the subject. — Levy Bryant, Larval Subjects

Perhaps we can add subordination of questions to contemplation of forms and subordination of questions to hylomorphic classification to this list of approaches which seek to replace the plurality of questions implicit in 'what is the general structure of things?' with questions in a single topic. That way, we need not study how things are, we just need to fit their behaviour to a pre-developed system of categories.*

But what is lost from this kind of approach is the domain specificity of the questions. For example, life as conceived by an anthropologist differs from life as conceived by a molecular biologist and differs again from an ecologist or a zoologist. A virologist would have different problems and a different conception of life embedded in those problems. We can trace a middle path, avoiding dogmatic metaphysics but seeking the insights into general questions that the studies of entities and their dynamics have. These different conceptions and their attendant entities are an example of philosophical study - what can we say of life? Are there any general features? What are the conceptual apparatuses we can use to disclose and track things about life?

I agree that it is true that every inquiry has some philosophical implications, but I don't agree that that allows us to dissolve the distinctions between philosophy and other inquiries. If too much is indexed to a particular type of inquiry, much is irrevocably lost from methodological issues.

*edit: of course, it the best insights from these reductive philosophical inquiries should be preserved, and they are still worth studying.

fdrake

↪T Clark

There are differences in 'how do I know what I know?' in philosophical terms and scientific ones. 'is this argument I found in a biology paper valid?' is the kind of thing philosophy could give you insight on, 'is this argument sound?' is the kind of thing you'd need some philosophical chops and biological chops to answer. 'are the premises true?' are likely to be questions of biology alone.

Cavacava

↪fdrake

Do you think that knowledge 'that' is subordinate to knowledge 'how'?

That learning how to ride a bike exceeds any propositional statement regarding this fact.

T Clark

There are differences in 'how do I know what I know?' in philosophical terms and scientific ones. 'is this argument I found in a biology paper valid?' is the kind of thing philosophy could give you insight on, 'is this argument sound?' is the kind of thing you'd need some philosophical chops and biological chops to answer. 'are the premises true?' are likely to be questions of biology alone. — fdrake

I haven't forgotten about your posts and I'm not ignoring them. I'm not sure what I think yet. I'm letting my thoughts think me.

fdrake

↪T Clark

Take your time.

↪Cavacava

I'd go further and say 'knowing that X' is a mostly artificial construction, it's a philosophical after-image. To me knowing that seems equivalent to retrojecting a set of competences, beliefs and evaluations which are summarised by 'X knows that P'. It may still be true that {"X knows that P" is true iff X knows that P}, but what knowing that consists of depends on what is known that.

EG: I know that my fridge doesn't have milk in it; why? I didn't buy milk and fridges don't fill themselves. In giving an account for why I know that P, I've supplanted a few reasons that fit in with some contextual cues and an exercise in imagining how I would/could be wrong (then framing that I couldn't through some implicit 'ad absurdum' in 'fridges don't fill themselves').

I think propositional content itself (the right hand side of "X knows that P" is true iff X knows that P) is also formed by some kind of retrojection. This is encoded in the triviality that X knows that P when and only when X can say in truth X knows that P. An exercise in conjuring a proposition to have an attitude towards.

You can contrast this with knowing how, in which an individual has to be able to do the thing not just be able to say truthfully that they can do the thing. This makes me suspicious; where was the proposition in my actions before it was a target for knowing that? I've never found one out in the wild.

T Clark

I'm not sure I agree with this. "How does DNA work?" has an influence on "What is the true nature of reality?", ontology in the broadest sense is the study of being - and it would be very surprising if the structure of (domains of) beings had no influence on the broadest metaphysical questions. — fdrake

I don't agree. I put this in as one of my pet peeves in the recent discussion, although it is not really a peeve, it's a serious philosophical question. The nature of DNA has nothing to do with the true nature of reality. Ontology is metaphysics. Metaphysical statements are not facts, not true or false. This is another one of those subjects on my list of discussion topics. I think it's next in line.

I agree that it is true that every inquiry has some philosophical implications, but I don't agree that that allows us to dissolve the distinctions between philosophy and other inquiries. If too much is indexed to a particular type of inquiry, much is irrevocably lost from methodological issues. — fdrake

I love this whole post, especially the quote from Levy Bryant, although I can't tell whether, from your point of view, I'm supposed to. I need to read everything at least three more times. Clearly, I don't rise to the level of even an epigone. Love the word. Lots of opportunities to use it as an insult on this forum. Thanks for that.

MonfortS26

How can civics coexist with epistemology in a productive way?

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