“How old would you be if you didn’t know how old you was?”
― Leroy Satchel Paige

Leroy Robert “Satchel” Paige (July 7, 1906 – June 8, 1982) was an American professional baseball pitcher who played in Negro league baseball and Major League Baseball. His career spanned five decades and culminated with his induction into the National Baseball Hall of Fame. Wikipedia

Notes on Philosophy of Science

Scott Brodie Forsyth

2 days ago (Medium.com)

Philosophy of science can be regarded as a meta-discipline, dealing with a range of meta-questions about science and scientific practice. Philosophy of science is relevant to both the natural sciences and the social sciences, where it attempts to theorise how the world can be understood and known, as well as how knowledge can be attained. At a basic level, there can be discussions of epistemology and ontology. Etymologically, ontology means the study of being, from Greek; “on” meaning “being,” and logia meaning “the study of.” Ontology describes what exists and how essentially, what the world consists of. Epistemology has its etymological origins in the Greek words “episteme” and “logos.” Episteme can be translated as knowledge or understanding, where logos can be understood as argument or reason. Epistemology thus describes the study of how the world is known or perceived. Moreover, within philosophy of science, a broad distinction can be made between naturalism and constructivism. Constructivism is based on the notion that the social sciences deal with a reality that is socially and linguistically constructed. Ontologically, constructivism relates to social phenomena and social relations that must be considered as phenomena continuously constituted via language and the social. Naturalism emphasises the idea of the sciences addressing a genuinely objective existing reality. From an ontological perspective, naturalism views social phenomena as part of the natural world. When discussing naturalism, natural laws and causality make up key factors. The goal is to pursue an explanatory scientific approach where theories are tested and understood through systematic and causal explanations.

Ontological objectivity describes how truth is independent of the opinions of subjects. An example of ontological objectivity is “Jupiter has a larger surface area than Mercury.” This statement is true regardless of what others may think about it. Epistemological objectivity describes truths such as “The Danish Parliament has 179 members,” which, for example, focuses on facts about society. These social issues are not as subjective as “what is your favourite colour,” but arise from shared beliefs and constructions. John Searle works with social facts, which can be described as epistemologically objective. From Searle’s point of view, within a certain level of social reality, causality can indeed be addressed. According to Searle, there is a kind of epistemological objectivity, suggesting that it might be possible to establish regularities. However, Searle does not advocate for unified science as such. Searle distinguishes between natural science and social science. In relation to the latter, social rules can be broken, whereas natural laws cannot be broken. Searle focuses on the everyday social reality. Thus, how people’s social life appears as natural and necessary, even though it is arguably not. Searle deals with society’s rules of the game, i.e., how these rules arise and how they can be broken down. Some of the basic concepts found within Searle’s works are collective intentionality, rules, and deontic content. Social facts are ontologically subjective but epistemologically objective. Social facts can be described as ontologically subjective because their existence is based on collective intentionality. At the same time, social facts are epistemologically objective. For example, knowledge can be gathered about whether a means of payment is considered valid. Social rules say something about knowledge, capacity, and will, whereas natural laws are exceptionless. It may happen that social rules are not followed; in contrast, natural laws will repeatedly appear without exceptions. Social rules may not be followed due to insufficient knowledge about them, or simply a lack of will to follow the social rules.

Ontologically, the world can be considered as social, consisting of social building blocks and constructions according to Searle. Epistemologically, knowledge is recognised through social facts. From a methodological standpoint, some theorists argue that it is the social reality, and justify primarily an interpretive methodology, while others advocate some form of unified science. Epistemological social constructivism is based on the idea that the social leads to ideas about the world, whereas ontological social constructivism claims that ideas create our (social) world. Searle writes about the construction of social reality, where ontological social constructivism appears, thus the social world that occurs as a result of cognition and action. Searle also notes when talking about contingency, it describes that things are different, but since things are as they are, according to Searle, it has a character, whereby predictions to the level of explanation are probably made. Contingency implies that something is historically specific and could therefore be different. Contingency cannot be described as mere chance but in relation to the given circumstances.

Logical positivism, in contrast, offers a distinct perspective on addressing scientific challenges. While social constructivism emphasises the role of cognition and action in shaping the social world, logical positivism takes a different route in tackling scientific inquiries. Logical positivism employs the verification principle as a demarcation principle. The verification principle entails that statements can be verified through observations or logical propositions; other statements must be considered unscientific. According to logical positivism, scientific practice should be structured according to the verification principle. Thus, there is a rejection of metaphysical or speculative claims such as Hegel’s world spirit. Statements other than analytic and synthetic can be considered meaningless or metaphysical from this philosophy of science standpoint, including normative statements. Logical positivism, however, can be criticised for leading towards confirmation of statements instead of examining what contradicts them. Furthermore, one cannot infer from “some” or “many” to “all”.

When we make inductive generalisations based on past observations, we are assuming that these past instances are representative of all future instances. Here, we may speak of the problem of induction, as described by Hume, in questioning whether induction leads to knowledge about future events. Inductive thinking involves the problem or assumption that past observations indicate how a phenomenon will unfold in the future. Considering induction and deduction: Induction involves drawing general conclusions from empirical data, whereas deduction begins with a theory wherein a hypothesis is formulated — a preliminary assumption about the field of investigation. Then empirical data is collected to test the hypothesis based on the empirical material. According to Hume, most of our knowledge is not based on mathematics and geometry (deduction) but on empirical observations (induction). However, the problem with observations is that necessary causal connections can be predicted or believed according to Hume. He also highlights the sceptical question of causality, stating that although a person may have an idea of causality or necessary connections, when this idea is tentatively linked to specific sense impressions, in reality, there are just several different isolated sense impressions following one another.

As mentioned, one of the greatest problems with logical positivism is its tendency to seek confirmation of statements rather than examining what contradicts them. Karl Popper sought to solve this issue. One of his significant contributions to the philosophy of science is proposing a deductive and logically valid method for inferring between theory and observations. Popper’s approach reverses the issue by initiating scientific inquiries with a falsifiable theory (T), and then conducting observations (O) to test the theory. This philosophy of science is termed critical rationalism, which has falsification as its demarcation criterion. Critical rationalism is based on formulating a theory or hypothesis in order to be able to falsify it. Scientific statements must therefore be falsifiable. Science, according to critical rationalism, appears as a continuous process. Thus, there is no final truth, but instead, the scientific approach proceeds through ongoing theorisation, empirical testing, and adjustments to refine the scientific understanding of the world.

Popper highlights falsification as a basis for science and sets up a deductive logic: if the theory (T) is true, then the observation (O) must be true. In formulating a theory (T), it may also turn out through observation (O) that the theory (T) is false. Scientific investigation thus begins with a theory (T), and then it is tested through observation (O) to determine if the theory (T) is true or false. If observations (O) are not true, the theory (T) can thus be falsified. Popper’s demarcation criterion for scientific validity is that the theory proposed must be capable of being falsified. Based on this reasoning, Popper criticises Freud’s psychoanalysis and Marx’s social analysis, as part of their theories may be difficult or impossible to falsify. A reason for the social sciences to adopt critical rationalism lies in dealing with the replication crisis, characterised by researchers facing challenges in reproducing similar results within canonical projects. This crisis often manifests when attempts to replicate the findings of initial studies fail. Additionally, critical rationalism offers a valuable framework for addressing the phenomenon of post-rationalisation, wherein unexpected statistically significant correlations are rationalised.

In formulating critical rationalism and the principle of falsification, a fundamental assumption appears in Popper that theories can be tested on an objective reality independent of the formulated theory itself. It is assumed that, based on an observation, it can be directly evaluated whether the observation supports or contradicts the formulated theory. A similar assumption appears in logical positivism, although with the significant difference that the verification criterion appears as a demarcation line. However, this assumption is challenged by the Duhem-Quine thesis, which argues that scientific hypotheses cannot be tested empirically in isolation. It is pointed out that all observations ultimately appear as theory-laden, and therefore, an ultimate verification or falsification cannot be achieved. The Duhem-Quine thesis can be said to emphasise that observations always occur within a theoretical framework. It is not possible to test a given hypothesis in isolation, as every time a hypothesis is tested, a number of additional assumptions or hypotheses are presupposed. Hypotheses should therefore not be understood in isolation, but within a broader theoretical framework.

In the social sciences, attention can be turned to public administration, where a hypothesis is formulated that bureaucrats act budget-maximising — trying to attract larger amounts to their organisation. This hypothesis can be formulated based on public choice theory, which assumes rational bureaucrats trying to maximise self-interest. Testing this hypothesis proves to be quite challenging, as measuring budget maximisation could involve surveys, observations, and much more. Budgets or documents from a given organisation could also be examined. But the question is, do these factors test the hypothesis accurately enough? In such a study, from both a methodological perspective and the Duhem-Quine thesis, it is seen that there are numerous assumptions and hypotheses associated with the formulated hypothesis; that bureaucrats act budget-maximising. When testing a hypothesis, therefore, not only the hypothesis itself is tested, but a collection of assumptions and hypotheses. In other words, it can be difficult to know exactly which idea, hypothesis, or assumption produces a particular result.

On the other hand, within the context of public administration research, a pragmatic approach would suggest considering the specific problems and challenges faced by bureaucrats in their day-to-day activities. Contrary to logical positivism or critical rationalism, the concept of truth according to pragmatism is grounded in the idea that a statement or assertion should contribute to solving problems. It is important that statements or ideas are “useful” rather than thinking of a statement as corresponding “one-to-one” with what appears in the world. If an idea, for example, does not solve the problems, it must therefore be challenged and spur new pragmatic inquiries. A statement is thus deemed true if it is useful in the long run. The truth value of a statement is thus assessed according to its pragmatic utility. However, it can be problematic for the concept of truth in pragmatism to determine when something is useful, and for whom? Pragmatism is rooted in the idea that knowledge production should be tied to solving human problems in the world. There is scepticism towards positivism’s ontology. According to pragmatism, the world is under constant development, and therefore new forms of experimentation and knowledge must arise. Pragmatic knowledge and truth are therefore understood through specific events and situations.

Thinkers within pragmatism include figures such as John Dewey, Charles Sander Pierce, and William James. Despite their philosophical differences, events are here understood here as temporally fixed and emphasise the uniqueness of various phenomena in the world, whereas situations emerge as those encountered by humans in the world in a given context, thereby determining the understanding of the world. The ontological basis for pragmatism is non-reductive or non-scientistic naturalism. Therefore, the natural sciences do not exclusively define nature; instead, everything is part of the world and nature on equal footing. At a sufficiently abstract level, it can be argued that unity of science is supported in pragmatism. Epistemologically, the world must be understood through a particular problematic situation, which, through pragmatic investigative processes, leads to understanding and solving a given problem. Science is therefore driven by the purpose of solving specific problems in the world. If the knowledge in question does not solve the problems, it must therefore be challenged and inspire new pragmatic investigations. Pragmatic investigations can also involve ensuring specific values. For example, John Dewey examined how democracy could be practised in education via his famous work, “Democracy and Education.” The pragmatic theory of truth states that a statement is true if it is useful in the long run. The truth value of a statement is assessed according to its pragmatic utility.

When discussing scientific theory and truth, we encounter various perspectives that influence our understanding of the world. These perspectives span from problem-solving in a given context (pragmatism) to investigations of truth through falsification (critical rationalism) and confirmation (logical positivism), as well as how we perceive the social world of money, law, and institutions (constructivism). In light of the developments in science, Thomas Kuhn undertook an approach to the theory of science from a more historical perspective. Kuhn, who questioned the rationality and cumulative nature of science, presents in his book, “The Structure of Scientific Revolutions,” a central thesis that science consists of periods of stable growth characterised by revisionary revolutions. Kuhn, who approached the theory of science from a more historical perspective, studied scientific development, from which he developed his understanding of science as non-rationally conducted, unlike thinkers within critical rationalism and logical positivism, who assumed that development was logical, as a result of verification (logical positivism) or falsification (critical rationalism). Kuhn argues that for scientific paradigms reflecting a given theoretical framework, there are theoretical and empirical anomalies that gradually make it difficult to maintain a particular paradigm. These paradigm shifts occur relatively rarely according to Kuhn, but when they do, they are of a revolutionary nature. Kuhn argues that scientific development does not appear to be rational or logical, but instead, scientific paradigms enjoy relative stability, followed by revisionary revolutions. However, it is often seen according to Kuhn that researchers try to explain anomalies within their current theoretical framework.

In classical economics, utility theory claims that the perceived value of gains and losses is equivalent. However, with the paradigm shift to behavioural economics (including prospect theory as developed by Daniel Kahneman and Amos Tversky), it turns out that gains and losses are not equivalent. The concept of “loss aversion” can be introduced, where the perceived value of loss is higher compared to gain. For example, a loss of $100 is perceived as a greater loss than the gain of $100. The behavioural economic paradigm here breaks with the classical economics’ assumptions that losses and gains are equivalent because market actors perceive a greater loss in utility from losses than utility gain from gains, even though it is the same amount.

When discussing science, considerations about values ​​in science must also be taken into account. Epistemic values ​​deal with knowledge and truth, including how we acquire, evaluate, and apply knowledge. Epistemic values ​​include values ​​such as reliability and truth. Non-epistemic values ​​can involve ethical, aesthetic, or emotional dimensions, concerning everything from justice to beauty. Distinguishing between these two forms helps articulate which values ​​relate to knowledge, knowledge acquisition, and cognition (epistemic values), and values ​​that relate to human morality and worldview (non-epistemic values). An example of an epistemic value ​​could be that a researcher has a dataset that highlights a trend among a defined population group, whereas a non-epistemic value ​​could be the researcher’s moral considerations about the political influence of publishing this research. Some scholars argue that researchers should incorporate non-epistemic considerations into the publication of their research, while others believe that researchers should only consider epistemic values, that is, what the scientific study actually shows.

According to Kasper Lippert-Rasmussen, if value judgments can only be justified by another value judgement, the latter value judgement must also be justified. In relation to scientific value relativism, it must be emphasised that there is a value judgement that can only be justified with reference to another value judgement. In such cases, there are two options; either the second value judgement can be justified by the first, or a third value judgement must be presented. Both of these situations can cause problems. Since the first scenario constitutes a circular argument, while the second option leads to infinite regress. In a nutshell, circular reasoning occurs when what needs to be proven is assumed. The conclusion thus follows a circular process. An example of circular reasoning could be stated as (A) “The Bible is true because it follows God’s word” and (B) “God’s word is true; it is written in the Bible.” The logical fallacy points out that A is true because B is true, and B is true because A is true, and thus, circular logic ensues. Infinite regress, on the other hand, explains an infinite process whereby the first value judgement is justified by another value judgement, and then a third, fourth, and so on infinitely. This leads to infinite regress, as the value judgments are justified by reference to additional value judgments, continuing infinitely. It is a justification chain without any actual endpoint.

Another prominent figure, who considered the role of values in science, Max Weber, pointed out that values ​​can be relevant in the social sciences in the sense that values ​​should be made objects of investigation. The second meaning of values ​​according to Weber is the so-called value relevance, that values ​​have an impact on what research communities choose to research in the first place. The third way in which values ​​become relevant in the social sciences, according to Weber, is related to goals and means, for example, how to best achieve a given goal. As the fourth way, values ​​become relevant by incorporating meaning, whereby a systematic analysis of the consequences of central values ​​and concepts can be conducted. According to Weber, meaning analysis can also lead to criticism, which is the fifth category describing how values ​​appear to be relevant in the social sciences. Weber writes about how values ​​in Protestantism, in interaction with capitalism, lead to the spread of rationalisation throughout society. Rationalisation involves a historical movement towards a world that can be more effectively controlled through calculation. It describes a process by which traditional values, emotions, and motivations are replaced by rationality and instrumental reason. Society is thus moving towards a higher degree of scientific thinking, calculation, and instrumentalisation. To summarise. First, values ​​can be relevant in the social sciences in the sense that values ​​should be made objects of investigation. Here, it can be examined how values ​​affect actors in a given field of study. Secondly, values ​​may have an impact on what research communities choose to research in the first place. Finally, values ​​become relevant by incorporating meaning, whereby a systematic analysis of the consequences of central values ​​and concepts can be conducted. Meaning analysis can also lead to criticism, which is the fifth category describing how values ​​appear to be relevant in the social sciences.

Elizabeth Anderson does not completely oppose the influence of values but instead asks whether these values can be positively directed towards epistemic values such as knowledge and truth. Thus, values can play a constructive role in understanding the world. According to Anderson, moral and political values ​​are equally distant from the truth, as some values ​​can be beneficial in guiding an investigation. However, she points out that a problem arises when values ​​are held dogmatically, leaving no room for open consideration or the ability to revise previous beliefs. For example, if a study were to be conducted on divorce, the traditional assumption that divorce is bad for all parties involved can be contrasted with the feminist assumption that based on emotional experiences, divorces can in some cases be experienced as liberating for women and children (or men). Anderson’s point is that reliance on value judgments can end up functioning as assumptions or influencing a proposed hypothesis. Anderson thus points out that bias and values ​​do not necessarily oppose understanding the world; however, a dogmatic attitude is problematic. Anderson’s argument can certainly be criticised from various epistemological perspectives, one of the most significant criticisms being that non-epistemic values ​​should be excluded from influencing scientific inquiry. Heather Douglas argues that researchers should consider the societal consequences of their research and consider non-epistemic values ​​in their decision-making process. This is because, according to Douglas, researchers have a moral responsibility for the potential effects their research findings may have on the surrounding society. To elaborate on this viewpoint, Douglas introduces several concepts related to objectivity and research ethics. Here, she writes about aspects to consider such as convergent objectivity, which means that research from different sources and perspectives should converge towards similar results to achieve credibility and reliability. Research should, according to Douglas, thus remain objective, even though it does not exclude the researcher’s awareness of potential consequences.

In light of these considerations on objectivity and research ethics, it is important to delve into the philosophical underpinnings of knowledge itself. One such perspective is offered by Plato, whose definition of knowledge states that a subject (S) knows that a proposition (P) is true if and only if: 1) S believes P, 2) S is justified in believing that P is true, and 3) P is true. Knowledge can be considered as a person having knowledge of a proposition (P) being true based on three conditions. Firstly, the person must be convinced of P. Secondly, it is necessary that the person is justified in their belief, and finally, P must be true. However, this definition can be criticised, among other things, based on the Gettier problem, which necessitates an additional condition: 4) that point 2 is not fulfilled accidentally. In connection with the last condition, there must be a clarification of what it means for something to appear as justified accidentally. The discussion of what it means to decide if something appears as accidental is ongoing in the academic community. But the Gettier problem shows overall that the three conditions, as described initially, do not constitute a sufficient basis for knowledge. Further, converging between analytical and synthetic knowledge, analytical knowledge is derived from logic and definitions, so analytical propositions are true by virtue of their meaning, for example, “all bachelors are unmarried men.” Synthetic propositions are true because they can be verified, for example, “Jens is a bachelor.” Synthetic knowledge is thus based on the collection of true propositions. Analytical truths are based on logic or their meaning. An example of an analytical truth is that “all bachelors are unmarried.” Synthetic truths are not only determined by internal truths but also by the nature of the world. An example of this is “sea water is salty.” Synthetic truths can also include political statements such as the democratic peace thesis, which states that “democracies do not go to war with each other.”

One can also distinguish between epistemic and pragmatic reasons. The former, epistemic reasons, can be described as the reasons that appear based on having evidence to believe that a proposition (P) is true. When discussing the existence of God, one could argue that there can be a pragmatic reason to believe in God, but it does not necessarily imply that there is evidence for believing that P is true — epistemic reasons. There are also many ways in which truth can be conceived and defined. For example, correspondence theory indicates that truth is grounded in our statements and science reflecting how the world is. The proposition (P) must therefore correspond to reality. What the theory says is that P must correspond to things as they appear in reality — independent of the statement made. For example, there can be correspondence between saying “the earth is round” and the actual shape of the earth. This theory also fits well with fact objectivism. A critique of the theory can arise by questioning how it is judged that a statement corresponds to reality. As an attempt to solve this problem, Ludwig Wittgenstein can be highlighted, who argued that if a picture is taken out in reality, there is a reality relationship — or likeness — between reality and the picture. Similarly, when talking about sentences, there can be a likeness between sentences and reality, e.g., “the cat is lying on the mat.” However, Wittgenstein later ended up rejecting this theory. Coherence theory indicates that the criterion for truth becomes that the statement must align with other beliefs about the world. Here, the aim is towards the greatest possible coherence or logical agreement. A statement must be judged as to whether it is true in relation to other statements. For example, Jupiter’s movement can be explained in the context of a statement about gravity. A statement consists of coherence relations, including a statement being coherent only if they are consistent with each other — but sentences can also be consistent without an inherent connection. Therefore, more than just consistency between two statements is needed. An example of coherence could be: Socrates is mortal, all humans are mortal. Socrates is human.

Consensus theory describes how a statement is true if consensus can be reached about the statement in question. A statement is considered true here if consensus can be reached about the statement. The criticism here can be, who should there be consensus among? For example, when looking at COVID vaccines, it can be asked whether there should be consensus among medical professionals or consensus among anti-vaccine groups and medical professionals. What does it mean for a statement to be true for group 1 but false for group 2? And how do we deal with this problem? This theory also fits as a perspective on fact constructivism. Pragmatic truth theory, on the other hand, describes how a statement is only true if it appears useful from a long-term perspective. A statement is true if it is useful in the long run. The truth value of a statement is assessed according to its pragmatic utility. The pragmatic truth theory can thus be understood as an approach to the world where knowledge and understanding that are useful are sought — so what is the pragmatic value? A criticism of this could be to ask when something is useful and for whom it is useful? For example, a theory could be useful for some people but not useful for others.

Considering the minimalist truth theory, it describes how a statement (P) is true if and only if P. This theory of truth therefore does not focus on truth in terms of coherence or utility. The theory is minimalist, arguing that “p holds: ‘p’ is true if and only if p.” Moving on, the epistemology of standpoint theory describes how the knowledge that can be acquired is linked to non-epistemic factors. Marxists argue that the non-epistemic factors that apply depend on whether one belongs to the working class or the bourgeoisie. Briana Toole argues that non-epistemic factors are relevant in the context of examining social identities, whether a given person belongs to an oppressive or oppressed group. Here, Toole illuminates two factors: how knowledge is situated and the examination of epistemic oppression or exploitation through the situated knowledge thesis. The situated knowledge thesis states: “there exist statements, p, for which whether an epistemic agent is in a position to know p depends on non-epistemic social facts about the agent.” Toole argues that there are non-epistemic facts, for example, whether a given person belongs to a minority or majority, here referred to as social identity. For example, there may be a discussion about whether a particular statement is an expression of “gaslighting.” For instance, if one is heterosexual and tells jokes about homosexuals, it can be questioned whether this is an expression of “gaslighting” or not, according to Toole’s argument. According to the situated knowledge thesis, it can be argued that there is a hermeneutic injustice or asymmetry, where the dominant group also possesses a privileged epistemic situation according to Toole. Epistemic oppression occurs, for example, when women are excluded from the research world or queer individuals are not allowed to enter certain workplaces. Epistemic oppression can be described as a persistent epistemic exclusion of a particular group, which often finds itself in a vulnerable situation or minority position. Thus, power balance may appear disproportionate.

In science, there are also ways in which the state of affairs is explained. The explanandum includes what is sought to be explained, while the explanans is what explains. Explanandum revolves around what is sought to be explained — i.e., what may be relevant to investigate. Explanans explains the explanandum. Token explanandum involves a singular point or event. Here, there is a singular explanation. An example of token explanandum in political science may relate to questions about why women voted more left-wing than men in the Swedish election. Type explanandum involves general trends and explanations. Here, an explanation for a general trend can be investigated; why women are increasingly voting left-wing in the recent elections in Sweden. A bad explanation relies on false assumptions, explanans does not explain explanandum, and explanans does not provide knowledge that calls for explanation. In connection with causal explanations, one can discuss how Hume highlights the problem of induction. According to Hume, a person can observe a series of events, but whatever the causality is, it is not directly experienced. Therefore, Hume’s philosophy calls for questioning whether causality can be included in explanations. Approaches popular in the scientific approach may involve causal inference, where causal dependencies are followed through statistical examination of the world. Here, inferences can be made from data about populations. Additionally, randomised control trials can be conducted, where a control and treatment group are established to examine the causality of the treatment. The process of randomisation and comparison between the control and treatment groups helps to exclude spurious relationships. Carl Hempel listed three components involved in a causal explanation: 1) triggering cause, 2) a series of initial conditions, and 3) one or more laws. This explanatory model is based on the regularity theory of causes.

There may also be questions about regularities in science. Laws can be described as regularities that occur. This can be contrasted with purely coincidental occurrences. In social science, there may be questions about whether there are laws in social science or “law-like regularities.” Unlike natural laws such as gravity, it can be argued that while natural science can predict 100 out of 100 times that an apple will fall from the tree, social science cannot necessarily identify such strong regularities. The laws in social science are therefore not like those in the world of physics or chemistry; they are not universal. In social science, “regularities” appear more in a specific context, where temporality, culture, system, etc., can be considered. According to the deductive-nomological model, everything still appears as inductive. Finding evidence for hypotheses would require inductive forms of argumentation. Many social science researchers do not give up on exploring causal regularities. This includes looking at types of explanations, statistical and quantitative methods, and randomised experiments. Process tracing and the construction of narratives are an example of token explanation — combining evidence and exploring causal mechanisms.

In July 1898, France and Britain were on the brink of war over territory, but surprisingly, the expected war did not break out. Sharon Crasnow presents three lawful hypotheses for the “Fashoda incident”: 1) neorealism explanation, asymmetric power balance, 2) democratic peace theory, and 3) informational asymmetry. Crasnow writes about narrative as explanation, arguing according to process tracing that narrative constitutes the cognitive work of making an explanation credible. Here, consideration of alternative hypotheses is facilitated, and the relationship between the given evidence and explanation is classified. Another form of explanation is purpose explanation, which involves referring to internal effects. Humans act as rational agents seeking to maximise self-interest. This means that according to this model of understanding, people act based on a purposeful rationale. There are two different kinds of functional explanations. One described by Lamarc is the direct function, while the other via Charles Darwin is based on the indirect function. For example, if one looks at the long neck of the giraffe, the direct functional explanation would be that this trait is functional in eating leaves from the trees. Darwin, on the other hand, has an indirect functional explanation, which describes how the giraffe has evolved through evolution, as it leads to survival and reproduction. Functional explanations could be in political science that nationalism is good for cohesion among people. Jon Elster examines when an acceptable functional explanation emerges. In this context, Elster presents a framework:

• Y is an effect of X
• Y is beneficial for Z
• Y is unintended by the actors producing X
• Y (or at least the causal relationship between X and Y) is unknown to the actors in Z
• Y maintains X through a causal feedback mechanism going through Z

In addition to different types of explanations, social science also grapples with the dichotomy between methodological individualism and holism. Methodological individualism rejects so-called superindividual social facts. According to this approach, social phenomena can be reduced to aspects of individual interaction. This approach thus focuses on observable individuals to examine the social world in accordance with the requirements of empiricism. In this way, a foundation for observable investigations is established. Methodological individualism can also be described as being linked to unity science and the possibility of reducing social phenomena to individual psychological, biological, chemical, and physical phenomena. Methodological individualism is found in economics. For example, Adam Smith argued that individual economic actors engage in a market of rational individual production and consumption behaviour. What motivates the cobbler, the baker, and others are the conditions for sale and purchase in the market according to Smith. A concept formulated by Smith, “the invisible hand,” describes through a metaphor how the market is self-regulating according to a spontaneous order. Here, one can speak of individuals maximising self-interest, and market equilibrium based on supply and demand for prices, labour, and more.

When discussing behaviourism or evolutionary psychology — which are distinct directions — it can be argued that these fields ontologically are grounded in a naturalistic and methodological individualistic understanding of the world. Epistemologically, there is a focus on an empirical understanding of individual behaviour. There is a pragmatic value in being able to reduce everything to the individual level. The reduction thesis is central to methodological individualism. According to methodological individualism, social entities do not have agency. It is only individuals who are treated as agents. The principle of exhaustiveness describes how individuals and their relationships are exhaustive in order to investigate social phenomena. Thus, the social world consists of individuals according to this principle. The principle of determination describes how individuals determine the social world through actions. Reference to individuals constitutes a condition for an explanation and examination of social phenomena.

On the other hand, methodological holism opposes “individualistic reduction”; in fact, science should be “non-reductive.” Methodological holists will also point out that unlike natural science, which has natural laws, social science does not have these same kinds of laws, and therefore, social science must more closely examine the world holistically. The core assertion of methodological holism is therefore that even though social phenomena may depend on individuals, social science cannot be reduced to individual behaviour. This individualistic understanding of the world is therefore not sufficient to investigate social facts. When natural and social sciences are compared, it can be argued, according to this approach, that methodological holism is something that creates a distinction between social science and the natural sciences. Social facts are understood as social non-reducible phenomena. It can be said that there is more focus on the whole than on the parts or individuals themselves. For example, Émile Durkheim found that even though suicide is an individual act, there is a social influence or explanation that affects the individual’s decision about suicide. Therefore, it can be argued that methodological holism can more effectively accommodate social reality.

In social science, the multiple realisability argument states that there are various ways in which a social phenomenon can be realised. There are thus countless ways in which a given social phenomenon can occur. Phenomena can thus arise from many different combinations. But why is multiple realisability relevant? First and foremost, the argument shows that there is no specific constellation of individual phenomena that explains a social fact. The supervening phenomenon can be realised in several different ways. This blocks the reduction of individual and social phenomena. Multiple realisability thus challenges parts of methodological individualism. For example, the reduction to individual actions in a given field of study is opposed. Arsenal, the football club, for instance, can according to methodological individualism be reduced to individuals, e.g., football players. But here, there is a risk of oversimplifying the football club, as it could be expressed through many different constellations. In principle, all the “insides” of Arsenal could be replaced, and it would still be the football club, Arsenal.

Social sciences tend to, from an individualistic standpoint, think of people as rational actors. This is seen, for example, in rational choice theory or classical economic theory. However, evolutionary psychology, for example, does not subscribe to the idea that humans are rational actors. Moreover, there is not always a sharp distinction between individualism and holism in investigating a phenomenon. For example, an educational or career choice can be reduced to an individualistic phenomenon, but at the same time, from a holistic standpoint, there are norms, culture, and ideas about what constitutes a good career. Sometimes the distinction between individualism and holism can probably be partially graded. Considering a methodologically individualist approach, we can introduce B.F. Skinner as an example; a behaviourist known for his laboratory experiments where he stimulated animals (e.g., rats, monkeys, and pigeons) to exhibit complex behaviour. These studies represent a key concept in behaviourist thinking about human behaviour as conditioned by stimuli and respective positive and negative responses from external environments.

Ontologically, behaviourism starts from a naturalistic and methodological individualistic perspective, whereby individual biological organisms emerge as the primary focus. The social world is thus part of the physical world and therefore also causally determined. Epistemologically, the social world is thus recognised through the observation of individual actors’ behaviour. Skinner’s behaviourism arose within neuroscience. Considering Ivan Pavlov’s famous experiment with dogs (“Pavlov’s dogs”), it involves a systematic investigation where a bell rang every time the dogs in the experiment were fed. In this way, the dogs began to associate the sound of the bell with the presence of food, and thus, they salivated without seeing or smelling the food when the bell rang. Pavlov’s classical conditioning describes a type of learning whereby a conditioned stimulus (e.g., the sound of the bell) can lead to a conditioned response (e.g., production of saliva). This requires, as described in Pavlov’s study, that the dogs must first learn to associate the food with the sound of the bell. Radical behaviourism requires that there is behavioural evidence for psychological hypotheses. Centrally, there is the assumption that positive reinforcement (e.g., pleasure) leads to repetition, while negative responses (e.g., pain) lead to avoidance.

Continue reading Epistemologies and Worlds →

ChatGPT-4 Goes Off the Rails Defending Claims Over Evidence

Tony Berard

Dec 26, 2023 (tonyberard.medium.com)

I was wondering if God uses some sort of algorithm to arrive at truths, could it be subject to the Incompleteness theorems of Godel? Obviously, God’s algorithm is more complex than the Peano axioms of arithmetic, but all the same, it is still an algorithm.

ChatGPT-4

Your question raises fascinating points regarding the nature of divine intelligence and the limitations of human logic as framed by Gödel’s Incompleteness Theorems. To consider this, let’s first understand the key concepts:

1. Gödel’s Incompleteness Theorems: These are two theorems of mathematical logic that demonstrate inherent limitations in every consistent axiomatic system capable of modeling basic arithmetic. The first theorem states that no consistent system of axioms whose theorems can be listed by an algorithm is capable of proving all truths about the relations of the natural numbers. The second states that such a system cannot demonstrate its own consistency.

2. Peano’s Axioms: These are axioms for the natural numbers proposed by the mathematician Giuseppe Peano. They form the foundation for much of modern mathematical logic and number theory.

3. “God’s Algorithm”: This is a more speculative concept. In this context, it seems to refer to the idea of a divine or ultimate algorithm that God might use to understand or create truths. This is not a formal concept in mathematics or theology but rather a metaphorical or philosophical one.

Now, applying Gödel’s Incompleteness Theorems to the concept of “God’s Algorithm” is intriguing but complex:

• Limitations of Human Logic: Gödel’s theorems apply to any formal system that is powerful enough to include arithmetic. If “God’s Algorithm” is akin to such a system, then in principle, it would be subject to the same limitations: there would be truths it could not prove, and it could not prove its own consistency.
• Nature of Divine Intelligence: Many theological perspectives view God’s knowledge and understanding as fundamentally different from human logic and reasoning. From such a viewpoint, it’s conceivable that divine intelligence operates on principles that are not constrained by human logic or mathematical theorems like Gödel’s.
• Metaphysical and Philosophical Considerations: The application of Gödel’s theorems to the concept of God enters the realm of metaphysics and philosophy. It raises questions about the nature of truth, the limits of human understanding, and the characteristics of a hypothetical divine intelligence.

In conclusion, while Gödel’s Incompleteness Theorems provide profound insights into the limits of formal systems in mathematics, applying these concepts to a metaphysical understanding of a divine intelligence like “God’s Algorithm” leads us into speculative and philosophical territory. It’s a fascinating intersection of logic, philosophy, and theology, but one where definitive answers are elusive.

So, a Christian can just claim, “Whatever truth is needed to be reached, it is of no consequence how difficult it is to ascertain such a truth because God just does it and sees the truth.” And, this claim is not challengeable because such an attempt to ascertain the likelihood of the process yielding such a truth is “elusive” as you say?

ChatGPT-4

Your follow-up question touches on the interplay between faith, theology, and rational inquiry, particularly in the context of Christian belief. When a Christian (or adherents of any faith) claims that “God just does it and sees the truth,” this statement is rooted in faith and the theological understanding of the nature of God, rather than in empirical or logical analysis.

Here are a few points to consider:

1. Faith-Based Beliefs: In many religious traditions, including Christianity, certain beliefs are accepted on faith. Faith, in this context, is belief in something beyond the bounds of empirical proof or logical reasoning. When a Christian says that God understands or reveals truth in a way that transcends human understanding, this is an expression of faith.
2. The Nature of Theological Claims: Theological claims often involve assertions about the nature of the divine that are not easily testable or verifiable using empirical or logical methods. For example, the claim that God can see or understand all truths is a theological one, grounded in the attributes of omniscience and omnipotence often ascribed to the Christian God.
3. Limits of Rational Inquiry in Theology: Rational inquiry, including logic and empirical investigation, has its limits, especially when applied to metaphysical or theological concepts. While these tools are powerful for understanding the natural world, they may not fully encompass or explain the nature of the divine or the supernatural.
4. Challenging Faith-Based Claims: While faith-based claims are not typically subject to the same kind of empirical verification or logical scrutiny as scientific claims, they can still be explored and discussed philosophically and theologically. Debates and discussions about the nature of God, the existence of the divine, and the interaction of faith and reason have been central to theology and philosophy for centuries.
5. Respecting Different Perspectives: In discussions about faith and reason, it’s important to recognize and respect the differing approaches people take. For some, faith provides a foundation of belief that transcends logical explanation; for others, the pursuit of empirical and logical understanding is paramount.

In summary, a Christian claiming that God comprehends truths beyond human understanding is expressing a faith-based view that is not easily challengeable through empirical or logical means. This doesn’t mean the claim is beyond discussion, but rather that it exists in a realm where faith and theology play a central role, distinct from the realms of empirical science and logic.

So, a Christian can just say to the mathematician, “Put your Incompleteness theorem away because no boundary applies to God.”?

ChatGPT-4

Yes, in a theological or faith-based discussion, a Christian might assert that Gödel’s Incompleteness Theorems, or any other mathematical or logical boundaries, do not apply to God. This viewpoint arises from the theological understanding of the nature of God, especially in Christian doctrine, which often includes beliefs in God’s omnipotence (all-powerful) and omniscience (all-knowing).

Here are some key points in this context:

1. Theological Perspective on Divine Nature: In many religious traditions, God is perceived as being beyond or above human logic and understanding. From this perspective, God’s capabilities and understanding are not limited by the rules that govern the created universe, including mathematical theorems or physical laws.
2. Distinction Between Divine and Human Logic: In theology, the logic and knowledge of God are often considered fundamentally different from human logic and knowledge. As a result, limitations that apply to human reasoning, such as those highlighted by Gödel’s Theorems, would not constrain a divine being.
3. Faith vs. Empirical Logic: This kind of statement reflects a faith-based position rather than an empirically-based or logically-derived one. It’s important to recognize that in matters of faith, believers often accept certain principles (like the omnipotence of God) that are not subject to the same standards of proof or disproof as in scientific or mathematical inquiry.
4. Dialogues Between Faith and Reason: While such a statement might be valid within the framework of religious belief, it’s also important to acknowledge the value of dialogues between faith and reason. Many theologians and philosophers have endeavored to bridge these domains, exploring how religious beliefs intersect with, contrast, or complement logical and empirical understanding.
5. Respect for Different Worldviews: In discussions that involve both religious beliefs and scientific or mathematical concepts, it’s crucial to respect the different approaches and worldviews. A statement like “no boundary applies to God” reflects a religious worldview, which is different from a scientific or mathematical worldview.

In summary, from a religious perspective, especially within Christianity, it’s not uncommon to assert that divine nature transcends human logic and limitations like those described in Gödel’s Incompleteness Theorems. However, such assertions are based on faith and theological understanding rather than empirical or logical proof.

So, in the final analysis, faith trumps reason, empirical knowledge, evidence, and proof just because they claim it?

ChatGPT-4

The relationship between faith and reason, including empirical knowledge, evidence, and proof, is a complex and nuanced topic that has been debated and discussed for centuries in philosophy, theology, and other fields. It’s important to understand that faith and reason are often seen as different ways of knowing and understanding the world, each with its own strengths and limitations. Here are some key points to consider:

1. Different Domains of Knowledge: Faith and reason can be viewed as different domains of knowledge. Reason, along with empirical evidence and scientific inquiry, is grounded in observation, experimentation, and logical analysis. Faith, on the other hand, is often based on spiritual, religious, or personal beliefs that may not be empirically verifiable.
2. Complementary Rather Than Opposing: Many thinkers have argued that faith and reason can be complementary. In this view, each can offer insights into different aspects of human experience and understanding. For example, science can explain how the natural world operates, while faith can provide meaning, purpose, and ethical guidance.
3. Philosophical and Theological Perspectives: Throughout history, philosophers and theologians have proposed various ways to reconcile faith and reason. Some argue that there are truths that can only be known through faith, while others believe that reason and empirical evidence are paramount in understanding the world.
4. Faith’s Role in Individual Beliefs: For many people, faith is a deeply personal and foundational aspect of their worldview and identity. It can provide a sense of meaning, community, and moral guidance. In such cases, faith may be held as primary, even in the face of contradictory empirical evidence or logical arguments.
5. Limits of Empirical Knowledge: It’s also worth acknowledging that empirical knowledge and reason have their limits. There are questions about existence, morality, and meaning that may not be fully answered by empirical science alone.
6. Cultural and Historical Context: The balance between faith and reason can vary greatly across different cultures, historical periods, and individual beliefs. What one culture or individual may consider a matter of faith, another might approach with empirical reasoning.

In the final analysis, whether faith “trumps” reason is not a universally agreed-upon conclusion but depends on individual perspectives, cultural backgrounds, and the specific context of the discussion. In many cases, people find ways to integrate both faith and reason into their understanding of the world. The interplay between these two domains continues to be a subject of ongoing discussion and exploration in many fields.

Ok, so what is your thought when someone still believes and makes claims about a fully debunked thing like astrology?

ChatGPT-4

When addressing beliefs in practices like astrology, which have been debunked or discredited by scientific inquiry, it’s important to approach the topic with a blend of understanding, critical thinking, and awareness of the psychological and social factors that influence such beliefs. Here are some thoughts and considerations:

1. Psychological and Social Factors: Belief in astrology often stems from psychological and social needs. People may find comfort, guidance, or a sense of control in astrology, especially during uncertain or difficult times. Understanding this can help in approaching the topic empathetically.
2. Cognitive Biases and Heuristics: Human cognition is influenced by various biases and heuristics. For example, the Barnum effect describes how individuals can find personal meaning in vague, general statements — a common technique in astrological readings. Awareness of these biases can help in understanding why people might continue to believe in astrology despite its lack of empirical support.
3. Cultural and Historical Context: Astrology has a long history and is deeply embedded in many cultures. This cultural significance can contribute to its continued appeal and acceptance, independent of its empirical validity.
4. Educational Approach: When discussing astrology with someone who believes in it, it’s often more effective to engage in a respectful and educational dialogue rather than outright confrontation. Providing information about how scientific methods work, and why astrology doesn’t hold up under scientific scrutiny, can be more persuasive if done in a non-confrontational manner.
5. Value of Critical Thinking: Encouraging critical thinking and skepticism is key. This involves questioning claims, seeking evidence, and considering alternative explanations. Critical thinking allows individuals to assess beliefs like astrology more objectively.
6. Respecting Autonomy and Choice: While promoting scientific literacy and critical thinking is important, it’s also crucial to respect individual autonomy and the right to hold personal beliefs. People have various reasons for their beliefs, and while we can provide information and perspectives, the choice to believe or not believe ultimately rests with the individual.
7. Distinction Between Belief and Action: There’s also a distinction between holding a belief and taking action based on that belief. While someone might enjoy reading their horoscope for entertainment, it becomes more concerning if they are making significant life decisions based solely on astrological predictions.

In summary, while astrology is not supported by scientific evidence and is considered a pseudoscience, understanding why people believe in it requires empathy and an awareness of the psychological, social, and cultural factors at play. Discussions about such beliefs can be more productive and respectful when they focus on education, encourage critical thinking, and respect individual autonomy.

Kurt Godel and Albert Einstein — two giants in thinking.

To conclude this in human terms, I think God would be constrained by the Incompleness Theorems because God must use some sort of logic or heuristical method to arrive at truths. It can even be well above what humans or AI can do, but it is still some kind of method, and as such, bound by the limitations of having truths that God cannot ascertain.

Thanks for reading me.

Written by Tony Berard

I have lately been constructing arguments against God and the supernatural. I have proven that stuff doesn’t exist with science equations. I aspire to be great.