01 - What is Science
>1800 Years, Greek astronomer Ptolmey = Geocentric astronomy, also known as Ptolemaic astronomy
1542, Copernican Revolution = Polish astronomer Nicolas Copernicus (1473-1543) published a book attacking the geocentric model of the universe, gave Heliocentric model which placed the stationary earth at the centre of the universe with the planets and the sun in orbit around it.
Johannes Kepler (1571-1630) and Galileo Galilei (1564-1642) = planets move in ellipses, and their speeds. Telescope & Law of free fall.
Rene Descartes (1596-1650) French philosopher, mathematician, and scientist = developed a radical new 'mechanical philosophy', according to which the physical world consists simply of inert particles of matter interacting and colliding with one another.
Isaac Newton (1643-1727), whose achievements stand unparalleled in the history of science. Newton's masterpiece was his Mathematical Principles of Natural Philosophy, published in 1687.
1859 Darwin's The Origin of Species.
What is Philosophy of Science?
Methods of enquiry. Question the assumptions scientists take for granted.
Science and Pseudo Science:
- Karl Popper, an influential 20th-century philosopher of science, thought that the fundamental feature of a scientific theory is that it should be falsifiable. Predictions can be tested.
Popper accuses Marixists and Freudians on trying to explain away false results but holding on to theory. He called it pseudo science. But then Adam-Leverrier held that Newton was right, and postulated a new planet called Neptune. Thus Popper's idea was plausible, but falsified.
Paul Feyerabend (1924–94) : critics of the positivist interpretation of science. Feyerabend’s most central idea was “epistemological anarchism”.
In Against Method (1975), he argued that any principle of Scientific Method has been violated by some great scientist – Galileo is one example amongst many others. So, if there is a Scientific Method at all, it can only be – “Anything Goes”.
In Farewell to Reason (1987), Feyerabend attacked the very idea of scientific rationalism. Science must become subordinate to the needs of citizens and communities.
02 - Scientific Reasoning
Darwin's theory of evolution, Africa and South America were together, Universe keeps expanding - All thories which employed reasoning, not empirical experiments.
Deductive Inference - Based on Premisses of inference and Conclusion (which can be examined)
Inductive Inference - Based on Premisses of inference and Conclusion (which cannot be examined) }} Ex: Down's syndrome patients have an extra 47th chromosome.
Humes's Problem (1711-1776) = Inductive Reasoning cannot be rationally justified at all. He began by noting that whenever we make inductive inferences, we seem to presuppose what he called the 'uniformity of nature' (UN). If we could prove that UN is true, then the non-uniform universe would be a logical impossibility. But we cannot prove it via empirical data, because it would need Inductive reasoning and assumes UN by itself,
Philosophers have responded to Hume's problem in literally dozens of different ways; this is still an active area of research today. Some people believe the key lies in the concept of probability.
Peter Strawson, argued that induction is so fundamental to how we think and reason that it's not the sort of thing that could be justified. Can you justify that law is legal?
Inference to the best explanation (IBE) =
Premisses - The cheese in the larder has disappeared, apart from a few crumbs. Scratching noises were heard coming from the larder last night => Therefore, the cheese was eaten by a mouse
This is non deductive. But on balance, looks plausible given the data.
Gilbert Harman, Philosopher considers IBE to me more fundamental of inductions.
When faced with multiple plausible explanations, the best explanation is the most parsimonious one.
Probability and Induction
Probability as a frequency interpretation? What's the probability of finding life on Mars? Subjective Interpretation of Probability? Probability as a matter of subjective opinion?
At the root of Hume's problem is the fact that the premisses of an inductive inference do not guarantee the truth of its conclusion. But it is tempting to suggest that the premisses of a typical inductive inference do make the conclusion highly probable.
03 - Explanations in Science
What is Scientific Explanation?
- Carl Hempel, 1950s, American philosopher = "Covering Law Model of explanation" : The conclusion states that the phenomenon that needs explaining actually occurs, and the premisses tell us why the conclusion is true. The task of providing an account of scientific explanation then becomes the task of characterizing precisely the relation that must hold between a set of premisses and a conclusion, in order for the former to count as an explanation of the latter. Hence 1) Premise should entail the conclusion, hence argument should be a deductive one 2) Premisses should all be true and 3) the premisses should contain of at least one general law or "laws of nature". SO 1 FACT, 1 GEN Law.
[explanans] General laws & Particular facts => Phenomenon to be explained [explanandum]
Counter Explanations - Either bonafide scientific theories which don't meet the covering law model [law is too strict] OR those that meet the criterion but are just improbable [law is too liberal] ex : m shadow is so and so because sun is at an elevation does not explain that flagpole is 15 m because of sun and it's shadow? Explanation and Prediction are not sides of coin here.
Explanation & Causality
Causality will reject the flagpole prediction anamoly cited above. Causality is assymetric and hence the relation between explanation and prediction. Empiricists like Hume are highly suspicious of causality.
Theoretical Identifications are those which do not have causality in scientific experiments, Ex - Water is H20.
Explanation and Reduction
How can a science that studies entities that are ultimately physical not be reducible to physics? the answer lies in the fact that the objects studied by the higher-level sciences are 'multiply realized' at the physical level?
04- Realism Vs anti-realism [Instrumentalism]
Realism holds that the physical world exists independently of human thought and perception.
Idealism denies this - it claims that the physical world is in some way dependent on the conscious activity of humans.
This is a debate of Metaphysics.
Scientific Realists hold that the aim of science is to provide a true description of the world.
Anti-realists hold that the aim of science is to provide a true description of a certain part of the
world - the 'observable' part. They say unobservable part is fiction, just convenient tools or instruments to describe the observable, ex - "Phlogiston theory of combustion".
Maxwell - where do you draw the line between observable and unobservable? it's s vague distinction. Van Frassen - But Vague doesn't mean useless like the distinction between bald and hirsute men.
The Under-determination Argument
Anti-realists then argue that the observational data 'underdetermine' the theories scientists put forward on their basis. It means that the data can in principle be explained by many different, mutually incompatible, theories. In the case of the kinetic theory, anti-realists will say that one possible explanation of the observational data is that gases contain large numbers of molecules in motion, as the kinetic theory says. - there will always be a number of competing theories that can account for that data equally well. Underdetermination leads naturally to the anti-realist conclusion that agnosticism is the correct attitude to take towards claims about the unobservable region of reality.
05- Scientific Change and Scientific Revolution
1963 : Thomas Kuhn, an American historian and philosopher of science. In 1963 Kuhn published a book called The Structure of Scientific Revolutions, unquestionably the most influential work of
philosophy of science in the last 50 years.
Logical Positivist philosophy of science
LOGICAL POSITIVISM - The original logical positivists were a loosely knit group of philosophers and scientists who met in Vienna in the 1920s and early 1930s, under the leadership of Moritz Schlick. (Carl Hempel, was closely associated with the positivists, as was Karl Popper.). Science for the positivists was a paradigmatically rational activity, the surest route to the truth that there is.
This was primarily because they drew a sharp distinction between what they called the 'context of discovery' and the 'context of justification'.
The context of discovery refers to the actual historical process by which a scientist arrives at a given theory.
The context of justification refers to the means by which the scientist tries to justify his theory once it is already there - which includes testing the theory, searching for relevant evidence, and so on.
The positivists believed that the Context of discovery was a subjective, psychological process that wasn't governed by precise rules, while the Context of Justification was an objective matter of logic. Philosophers of science should confine themselves to studying the latter, they argued.
Without a clear distinction between theories and observational facts, the rationality and objectivity of science would be compromised, and the positivists were resolute in their belief that science was rational and objective.
THE STRUCTURE OF SCIENTIFIC REVOLUTIONS
Examples of scientific revolutions are the Copernican revolution in astronomy, the Einsteinian revolution in physics, and the Darwinian revolution in biology.
Kuhn coined the term 'normal science' to describe the ordinary day- to-day activities that scientists engage in when their discipline is not undergoing revolutionary change. Central to Kuhn's account of a normal science is the concept of a paradigm.
A PARADIGM consists of two main components: firstly, a set of fundamental theoretical assumptions that all members of a scientific community accept at a given time; secondly, a set of exemplars' or particular scientific problems that have been solved by means of those theoretical assumptions, and that appear in the textbooks of the discipline in question.
Ordinarily we assume that when scientists trade their existing theory for a new one, they do so on the basis of objective evidence. But Kuhn argued that adopting a new paradigm involves a certain act of faith on the part of the scientist.If a given paradigm has very forceful advocates, it is more likely to win widespread acceptance.
Surely scientists are meant to base their beliefs on evidence and reason, not on faith and peer pressure? Kuhn's account of paradigm shifts seems hard to reconcile with the familiar positivist image of science as an objective, rational activity. One critic wrote that on Kuhn's account, theory choice in science was a matter of "mob psychology"!
This 'cumulative' conception ofscience is popular among laymen and scientists alike, but Kuhn argued that it is both historically inaccurate and philosophically naive. Moreover, Kuhn questioned whether the concept of objective truth actually makes sense at all. Truth itself becomes relative to a paradigm.
Incommensurability and the theory-ladenness of data
Kuhn had two main philosophical arguments for these claims.
- Firstly, he argued that competing paradigms are typically 'incommensurable' with one another. Incommensurability is the idea that two paradigms may be so different as to render impossible' any straightforward comparison of them with each other - there is no common language into which both can be translated. As a result, the proponents of different paradigms 'fail to make complete contact with each other's viewpoints', Kuhn claimed.
The doctrine of incommensurability stems largely from Kuhn's belief that scientific concepts derive their meaning from the theory in which they play a role. So to understand Newton's concept of mass, for example, we need to understand the whole of Newtonian theory - concepts cannot be explained independently of the theories in which they are embedded. This idea, which is sometimes called 'holism', was taken very seriously by Kuhn. Kuhn used the incommensurability thesis both to rebut the view that paradigm shifts are fully 'objective', and to bolster his non-cumulative picture of the history of science.
Kuhn's second philosophical argument was based on an idea known as the 'theory-ladenness' of data. Kuhn argued that the ideal of theory-neutrality is an illusion - data are invariably contaminated by theoretical assumptions. It is impossible to isolate a set of pure' data which all scientists would accept irrespective of their theoretical persuasion. [truth itself is relative to a paradigm.]
- Perfectly objective choice between two paradigms is therefore impossible: there is no neutral vantage-point from which to assess the claims of each.
- the very idea of objective truth is called into question.
Perception is heavily conditioned by background beliefs - what we see depends in part on what we believe. Scientists' experimental and observational reports are often couched in highly theoretical language.
In rebutting the charge that he had portrayed paradigm shifts as non-rational, Kuhn made the famous claim that there is 'no algorithm' for theory choice in science. What does this mean? An algorithm is of a set of rules that allows us to compute the answer to a particular question. So an algorithm for theory choice is a set of rules that when applied to two competing theories would tell us which we should choose. Much positivist philosophy of science was in effect committed to the existence of such an algorithm. The positivists often wrote as if, given a set of data and two competing theories, the 'principles of scientific method' could be used to determine which theory was superior. This idea was implicit in their belief that although discovery was a matter of psychology, justification was a matter of logic.
Lots of philosophers and scientists have made plausible suggestions about what to look for in theories - simplicity, broadness of scope, close fit with the data, and so on. But they aren't a true Algorithm, because a common sense is always required to make the final choice.
The moral of Kuhn's story is not that paradigm shifts are irrational, but rather that a more relaxed, non-algorithmic concept of rationality is required to make sense of them.
Kuhn's Legacy = After Kuhn, the following came into focus:-
- i) the idea that philosophers could not afford to ignore the history of science
- ii) sharp dichotomy between the contexts of discovery and justification.
- iii) focus attention on the social context in which science takes place, something that traditional philosophy of science ignored.
- iv) Kuhn's ideas have been very influential among sociologists of science. In particular, a movement known as the 'strong programme' in the sociology of science, which emerged in Britain in the 1970s, owed much to Kuhn.
Strong Programme :- The strong programme was based around the idea that science should be viewed as a product of the society in which it is practised. Strong programme sociologists took this idea very literally: they held that scientists' beliefs were in large part socially determined. So to explain why a scientist believes a given theory, for example, they would cite aspects of the scientist's social and cultural background.
But strong programme sociologists were more radical than Kuhn, and less cautious. They openly rejected the notions of objective truth and rationality, which they regarded as ideologically suspect, and viewed traditional philosophy of science with great suspicion. This led to a certain amount of tension between philosophers and sociologists of science, which continues to this day
[Refer @1]
- v) Kuhn's work has played a role in the rise of cultural relativism in the humanities and social sciences.
Ironically, Kuhn, the science philosopher, influenced Cultural relativists who are normally very anti-science. They object to the exalted status that science is accorded in our society, arguing that it discriminates
06 - Philosophical questions in Physics, biology and psychology
'General Philosophy of Science' deals with issues like - Induction, Explanation, Realism, and Scientific Change - scientific investigation in general, not any specific field. Then there are the "Philosophies of Special Sciences".
1. Leibniz versus Newton on space 'Absolutionist' vs 'Relationist' : Leibniz strongly disagreed with the absolutist view of space, and with much else in Newton's philosophy. He said space consists simply of the totality of spatial relations between material objects. Leibniz's argument was that absolute space conflicts with what he called the Principle of the Identity of Indiscernibles (PlI), which says that if two objects are indiscernible, then they are identical, they are really one and the same object.. Since Leibniz regarded this principle as indubitably true, he rejected the concept of absolute space.
2. Problem of Biological Classification : Biologists traditionally classify plants and organisms using the Linnean system, named after the 18th-century Swedish naturalist Carl Linnaeus (1707-1778).
Linnean system - First of all, individual organisms are assigned to a species - the basic taxanomic unit. Each species is then assigned to a higher taxa - genus, each genus to a family, each family to an order, each order to a class, each class to a phylum, and each phylum to a kingdom. there are 5 kingdoms - Animals, Plants, Fungi, Bacteria, and Protoctists (algae, seaweed, etc.).Various intermediate ranks, such as subspecies, subfamily, and superfamily are also recognised.
Cladists - try and reflect evolutionary relationships between species, Pheneticists consider it independent of evolutionary considerations. Evolutionary Taxanomists combine elements of both.
07 - Science and it's critics
Scientism : 'Scientism' is a pejorative label used by some philosophers to describe what they see as science-worship - the over-reverential attitude towards science found in many intellectual circles.
Willard van Orman Quine :- Questions that cannot be resolved by scientific means are not genuine questions at all, they hold.
Also critics are from Religion and Is Science value free?
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REF : Ziauddin Sardar
@1 - Karl Mannheim (1893–1947) had earlier founded the Sociology of Scientific Knowledge (SSK).
SSK is an interdisciplinary field within the sociology of science that emerged in the 1970s. It focuses on understanding scientific knowledge as a social phenomenon, examining how social factors influence the development, validation, and acceptance of scientific theories and facts. Unlike earlier approaches that treated scientific knowledge as objective and immune to social influences, SSK treats science as a human activity subject to social, cultural, and historical contexts.
Mannheim believed that social factors influenced knowledge, but he made a clear distinction between ideological (biased) knowledge and scientific (objective) knowledge. He argued that while everyday and ideological knowledge is socially determined, scientific knowledge could still be objective and less influenced by social factors.
SSK believed that scientific knowledge was universal – its objectivity transcended specific cultural origins – and hence science was beyond sociological inquiry. Several types of sociology of science were developed within these limits after the Second World War. The most influential was the one proposed by the American sociologist R.K. Merton (b.1910) who systematized the normative pronouncements of famous scientists. In the late 1960s, Mannheim’s strictures were unceremoniously ejected by the “Strong Programme”.
The Strong Programme, developed primarily by David Bloor and Barry Barnes at the University of Edinburgh, is a specific approach within SSK. It is called "strong" because it applies the same social explanations to both successful and unsuccessful scientific theories, in contrast to earlier approaches that only applied social explanations to erroneous or pseudo-scientific beliefs.
Key Tenets of Strong Programme:
- Causality: Scientific beliefs are caused by social factors as well as empirical evidence.
- Impartiality: The same types of causes should be used to explain true and false beliefs.
- Symmetry: True and false scientific beliefs should be explained in the same way, without privileging "true" beliefs.
- Reflexivity: The sociological explanations applied to scientific knowledge should also be applicable to the sociology of science itself.
The proponents of the Strong Programme, argue that SSK has four basic elements.
1. SSK discovers the conditions – economic, political, social, as well as psychological – that bring about states of knowledge.
2. SSK is impartial in its selection of what is studied. It gives equal emphasis to true and false knowledge, successes and failures of science.
3. SSK is consistent (or uses “symmetry”) in its explanation of selected instances of scientific knowledge. It would not, for example, explain a “false” belief with sociological cause or use a rationalist cause to explain a “true” belief.
4. The models of explanation of SSK are applicable to sociology itself.
The “Strong Programme”, which began at Edinburgh University, was an initiative in the general attempt to bridge what C.P. Snow (1905–1980) called the “two cultures”. In post-war Britain, scientists and adepts of arts and humanities had ceased communicating with each other.
SCIENCE AS SOCIAL CONSTRUCTION
“Constructionists” - Certain sociologists of science argue that science is socially constructed and not determined by the world or some “physical reality” out there.
Constructionists study specific historic or contemporary episodes in science. They also carry out “field research” in laboratories.
Constructionists interrogate the "facts" of science and the "truths" they are supposed to express. And also examine how the process of knowledge production actually works at the cutting edge of research.
The Effect of Reality : The most famous constructionist study is Laboratory Life: Social Construction of Scientific Facts (1979; 1986) in which Bruno Latour and Steve Woolgar examined the detailed history of a single fact: the existence of Thyrotropin Releasing Factor (Hormone), or TRF(H) for short. Latour and Woolgar show that TRF(H) has meaning and significance according to the context in which it is used. It has a different significance for each group of specialists – medical doctors, endocrinologists, researchers and graduate students who use it as a tool in setting up bioassays.
Latour and Woolgar also suggest that the transformation of statement into fact is reversible: that is, reality can also be deconstructed. Reality cannot be used to explain why a statement becomes a fact, since it is only after a fact has been constructed that the effect of reality is obtained.
Latour and Woolgar emphasize that the process of constructing facts is what produces the "reality" that we then use to explain or justify these facts. This reversal of the usual cause-effect relationship (where facts reflect reality) is a key insight of their work. In essence, the transformation of a statement into a fact—and thus into "reality"—is a socially mediated process. The fact's apparent direct connection to reality is an effect created by this process, rather than its cause.
The Construction of Objectivity by Ian Mitroff’s The Subjective Side of Science (1974) : examined the perceptions, cherished theories and published results of scientists who analysed lunar rocks brought back by Apollo 11. In almost all cases, scientists found what they expected. his conclusion - Scientific Objectivity is nothing but a socially constructed charade. Important to note that Mitroff investigates how personal biases, emotions, values, and psychological factors influence the behavior and decision-making of scientists. Mitroff doesn’t argue that ALL scientific knowledge is socially constructed but rather that the subjective experiences of scientists play a significant role in shaping how science is done. Mitroff does NOT necessarily challenge the overall objectivity of science but instead shows how subjective factors can influence scientific practice.
The Science Tribe : Karin Knorr-Cetina, in her seminal work, The Manufacture of Knowledge (1981), studied scientists in a laboratory like a tribe in the jungle. Concluding - "Can there ever be such things as value-neutral "Objective facts" ? Knorr-Cetina focuses on the micro-social processes within scientific laboratories.
Constructionism Vs Strong Programme :What is the difference between social constructionists and proponents of the Strong Programme?
- Unlike the constructionists, the Strong Programme accepts the existence of an "unproblematic reality" - The term "unproblematic reality" in this context suggests that the Strong Programme recognizes that there is a reality independent of human thought and perception—a reality that science can investigate and learn about. But it emphasizes that the processes through which scientific knowledge is produced are socially influenced.
- Radical constructionists, deny the existence of an objective reality or the fact that science can gain knowledge about it
- Constructionists argue that all aspects of scientific knowledge, including reality itself, are socially constructed and thus problematic
Kuhn's Theory laden observations strongly influenced the thought that theories are burdened with cultural baggage.
The context of Tradition :
Thomas Kuhn argued that observations in science are "theory-laden," meaning that what scientists observe is influenced by the theoretical framework or paradigm they are operating within. This suggests that different scientific communities, working within different paradigms, might interpret the same empirical data differently because their observations are filtered through their theoretical commitments.
Strong Programme argue that it is not the raw observations themselves that are necessarily theory-laden, but rather the reports and interpretations of those observations. The interpretation of an observation involves using the resources of a particular scientific tradition. This means that how observations are reported, understood, and integrated into scientific knowledge depends on the social and intellectual context, rather than being purely determined by the theory alone
The Strong Programme is not directly against Kuhn’s concept of theory-laden observations. Instead, it builds on the idea by adding a layer of social analysis. While Kuhn focuses on the role of paradigms and theoretical frameworks in shaping observations, the Strong Programme highlights how social traditions and contexts shape the reporting and interpretation of those observations. Strong Programme can be seen as complementary to Kuhn’s ideas. It extends the analysis from the cognitive or intellectual realm (how theories shape observation) to the social realm (how traditions and social contexts shape the interpretation and reporting of observations).
Hilary Rose, in " Love, Knowledge, Power (1994)", Responsible Rationality = restores care and concern within scientific objectivity.
Post Colonial Science Criticism = Like feminist scholars, post-colonial critics argue that real change can come about only through a fundamental transformation of concepts, methods and interpretations in science – a complete re-orientation in the logic of scientific discovery. This branch has three quite distinct strands ...
- Critique of Colonial Science and Knowledge Production - non western positions on
- Reclaiming and Recognizing Indigenous Knowledge Systems
- Impact of Postcolonial Science on Contemporary Issues
Social Epistemology
Social epistemology emerged in the 1980s as a critical movement concerned with the fundamental questions about the nature of knowledge.
“Social epistemology tries to reconcile the two approaches. It aims to develop a more holistic sense of inquiry, rather than the mutually alienated forms of knowledge that make up the degree courses in the average university.” - Steve Fuller
- Steve Fuller, the founder of the school of social epistemology, and his students, were concerned with attempts to reconcile normative and empirical approaches to the study of science.
- What social epistemology asks :-
- What sort of knowledge do we want?
- For what ends?
- Who should be producing it?
- On behalf of whom?
- How should we be using it?
Science Communication : Another way of pursuing social epistemology is by promoting the importance of rhetoric in the curriculum, specifically by encouraging specialists in Science Studies to join “science communication” programmes in which people who already hold science degrees seek to become part of the “public relations” arm of science.
Joan Leach in "Science and Society: The role of social epistemology in addressing social needs" published in 2006 : Social epistemology is the study of the social dimensions of knowledge, including how social processes, institutions, and interactions shape the production, validation, and dissemination of knowledge. In her work, Joan Leach argues that social epistemology can provide valuable insights into how scientific knowledge is created and how it can be made more responsive to social needs. She emphasizes that understanding the social contexts in which science operates is crucial for making science more accountable to the public.
Traditional epistemological approaches often focus on the benefits of science, and hide the costs. argue in a way that public can ask - "what's in it for them". In today's skeptical climate, these programmes have become vehicles for renegotiating science's social contract with the public.
Social epistemology has been instrumental in promoting multiculturalism as a vehicle for envisioning alternative ends and means of organizing the production of knowledge. However, the aim here is less on preserving distinct “local knowledges”, such as in museum exhibits, than in enabling one culture to learn from the successes and failures of other cultures’ knowledge-producing practices. Knowledge pursued "for it's own sake" is a western concept of epistemology.
Science Wars:
For much of the second half of the 20th century, scientists took the criticism of sociologists of science, social constructionists, social epistemologists, feminists and post-colonial scholars with – shall we say – some grace. They continued to do what they always did, with an occasional senior statesman of science usually Steven Weinberg – standing up to defend the good ol’ values of science.
But in 1990s, public disenchanment with science reached an all time high. Animal rights activists started picketing laboratories. Funding for "Big Science" such as super-conducting super-collider projects began to be squeezed. A full onslaught against the "science-critics" [charlatans] was launched.
A broad coalition of scientists, social scientists and other scholars was mobilized for the defence of science through a series of lavish, well-funded and highly publicized conferences. The most effective of these was the Flight from Science and Reason conference, sponsored by the New York Academy of Science, held in New York during the summer of 1995. The issues, the conference declared, are those of Reason and its application in science – and the status of these in our time. Defenders of the purity of science were convinced that there was a conspiracy from the “academic left” against science.
The much-cited work by Paul Gross and Norman Levitt, Higher Superstition: The Academic Left and Its Quarrels with Science (1994), became an unofficial manifesto of the defenders of science. There is open hostility from the “left” towards the actual content of scientific knowledge and towards the assumption – which one might have supposed universal among educated people – that scientific knowledge is reasonably reliable and rests on a sound methodology.
The Duke University journal Social Text is perhaps one of the most sacred precincts of the Cultural Studies brigade. On the cover of the Spring/Summer 1996 issue, "Science Wars" was mentioned.
The journal editor, Andrew Ross, describes science as a new religion and dismisses Higher Superstition as a shallow “shrill” work belonging to the well-established right-wing scholarly tradition of “crying wolf”.
Enter Sokal
After the orthodox pronouncements from the Curia – the college of cardinals of Science Studies – comes the curious contribution by Alan Sokal, a Professor of Physics at New York University, entitled “Transgressing the Boundaries: Towards a Transformative Hermeneutics of Quantum Gravity”. The paper is a trifle unusual – even by the constructionist tradition of extreme relativism. The bibliography clearly reads like a deliberately constructed “Who’s Who” of science critics and bears little relationship to the contents of the paper. And it contains embarrassingly flattering citations from the works of Andrew Ross and Stanley Aronowitz, editors of the journal. Yet, the editors of Social Text themselves failed to grasp its significance - "IT WAS A HOAX" !! When Sokal revealed his hoax, “Science Wars” went public in a media blaze. Sokal consolidated his hoax with Intellectual Impostures (1997) in which he took on the entire French left-wing postmodern establishment. It was open season on Jacqes Lacan, Julia Kristeva, Bruno Latour, Gills Deleuze, and Jean Baudrillard.
Jacques Lacan: Psychoanalysis and poststructuralism; 1950s–1970s. Julia Kristeva: Psychoanalysis, feminist theory, and semiotics; 1960s–present. Bruno Latour: Science and Technology Studies, Actor-Network Theory; late 20th century–early 21st century. Gilles Deleuze: Poststructuralism, continental philosophy; 1960s–1990s. Jean Baudrillard: Postmodern philosophy and social theory; 1970s–1990s
Sokal's Hoax, for some, confirmed that - the overbearing influence of Cultural Studies on Science Studies has produced a situation where anyone can get away with anything in the name of "Postmodern Criticism". Feyerabend's motto "anything goes" can now be applied to Science Studies itself.
Postmodern Criticism challenges traditional notions of fixed meaning and objective truth, advocating for a more fluid and context-dependent understanding of knowledge. It is marked by the work of influential theorists like Jean-François Lyotard, Jacques Derrida, Michel Foucault, Fredric Jameson, and Donna Haraway. While it has been praised for its innovative approach to culture and knowledge, it faces criticism for its relativism, obscurantism, and potential implications for political and ethical discourse.
But we should not allow Science Wars, or the deep subjectivity of certain constructionists’ positions, to distract us from the real issue: the power and authority, as well as the value-laden nature, of science.
Hence, the deep concern in scientific circles about the “public understanding of science”.
The Public Understanding of Science (PUS) movement emerged in the 1990s. It was championed by the scientific establishment itself and received major funding from research institutions and government agencies. It is largely based on the assumption that if the public has a better understanding of the technical side of science, it will have a greater respect for both science and scientists. Science sponsored "Science Communication" was given a high priority,
Publicity vs Accountability : The rubric “PUS” has been used to describe a continuum of activity. On one end, you have people, including some scientists, who see PUS as a public relations exercise and even a way of persuading audiences that controversial areas of science are unproblematic. On the other end of that continuum you have people, including scientists interested in public accountability, who want real dialogue about the future of research. Under various PUS schemes, scientists are encouraged to learn communication skills so they can talk intelligently to the public. Journalists are encouraged to report science more accurately and widely.
Corporate Funding of Research
After 1978, commercial funding for R&D began to exceed that of the govt
By early 1990s, corporations funded more than 1/2 of all research in US.
Industry expenditure on R&D is now 2-3X the amount of Federal spending.
Most of the research done at the universities is now funded by industry.
Market and private sector imperatives now drive scientific and technological advances and determine what Does and Does NOT get funded ! This makes Science subservient to business interests! Profit often determines the direction of science. Ex : More funding is happening in Biology than Physics (Big Pharma, Genome than particle accelerators).
The old military-industrial complex is being replaced by the corporation–university–private laboratory complex. Science becomes just another commodity, produced for sale.
Commercially driven science also defines “the problem” in a very specific way. For example, “the problem of cancer” is seen purely in terms of “finding a cure”. Not “eliminating cancer”.
This means that the benefits of scientific research accrue to certain groups, particularly the pharmaceutical companies. More effort is spent on researching contraception than investigating ways and means of eliminating poverty, developing low-cost housing, basic and cheap health delivery systems and encouraging employment-generating (rather than profit-producing) technologies.
MODE 2 KOWLEDGE
The total commodification of science, its increasing domination by commercial and consumer interests is also transforming science from within. The conventional production of scientific knowledge, generated within the boundaries of a single discipline in cognitive context, is now being replaced by a new system. This new system has been called “Mode 2 knowledge production”. Also called “post-academic science’ or “consumer-driven science”.
In their seminal work, The New Production of Knowledge (1994), Michael Gibbons et al. describe several attributes of knowledge production under Mode 2, they describe the attributes of Mode 2 as follows:
• Scientific work will no longer be limited to conventional institutions like universities, government research centres and corporate laboratories. There will be an increase in sites where knowledge will be created. Scientific work will also be done by independent research centres, industrial laboratories, think tanks and consultancies.
• These sites will be linked in various ways – electronically, organizationally, socially, informally – through functioning networks of communication.
• There will be simultaneous differentiation at these sites of fields and areas of study into finer and finer specialities.
• The recombination and reconfiguration of these subfields form the bases for new forms of useful knowledge.
“As a result, most scientists will become contract workers; they will work as temporary gangs of ‘fungible’ researchers,… specially brought together to work on a particular problem and, at the conclusion of each project, redeployed or discarded. Researchers will become totally proletarianized as they lose their property, both in the skills of stable paradigm-based research, and in the rights to their results."-J. Ravetz, Philosopher of Science
Consequences of Mode 2 Knowledge :-
“Mode 2” is a radical departure from the types of social structures that science has had over the past centuries. Several emerging problems in these new social relations can be identified.
For instance … What will ensure...
• What will ensure...the preservation of the “academic” sector, still necessary for training and creativity, when it is inevitably assimilated into the new mode of knowledge production?
• What will ensure...the maintenance of quality-control, when the traditional informal “community” skills, etiquette and sanctions are rendered meaningless in a totally “commodity” enterprise?
• What will ensure...the survival of independence and criticism, when the management of troublesome elements does not need the crude threat of dismissal but only the subtler control of the blacklist?
• What will ensure...the recruitment of gifted young people, when the career image of independent searchers for knowledge is replaced by that of contract “geeks” in Mode 2?
Uncertainty in Mode 2:-
Scientists have long known about uncertainty. Every time they start to investigate a problem, the possible answer is uncertain to some degree. But in normal science, the uncertainties are small; the puzzle is almost sure to be solved, and the possible answers are in a narrow range.… And although all the results in science have some uncertainty, but they are mainly what we call Technical…Statistical methods can tame them, and they can be adequately expressed with “error bars”...Uncertainty occupies centre stage when policy is involved, and when consumer-driven science moves towards Mode 2 production of knowledge. Why does uncertainty become central?
Policy Debates in Balance
In policy debates, uncertainties must always be balanced against “error costs”. In the case of global warming, for example, some would suggest that the American economy must not be damaged by energy restrictions, unless we are quite sure about global warming. Others may argue that despite uncertainties, dangers to humanity are clear.
Science in policy arena is like science in law courts, than normal research science.
The value-commitments that actually shape all research are here quite open, explicit and contested. How uncertainty can affect policy was illustrated by the frightening case of “mad cow” disease.
Ex : “Mad cow” disease – struck UK in the 1980s as a strange epidemic of unknown causes, yet almost certainly related to intensive rearing and unnatural feeding practices (herbivorous cattle were fed on animal protein). As the epidemic spread, scientific advisers had to juggle the uncertainties of its ultimate economic cost, the price of control by mass slaughtering and the unlikely but still conceivable possibility of the disease spreading to humans. Even as cats caught the disease in 1990s, there was an official denial of danger to humans… Measures of containment were all too little, too late and too partial. By 1996, when a human form of the disease was confirmed, there was brief general panic. The nation settled down to wait and see whether there would be isolated tragedies or mass horror.
Ex: MMR SCARE
We can see uncertainty in situations involving decisions about the control of ordinary infectious diseases. The UK Department of Health has a rigorous policy of simultaneous vaccination for three common childhood diseases: “MMR”, or measles, mumps and rubella (chicken pox). Each of these can have severe effects on a minority of victims.
Epidemiological studies are rejected by critics as flawed. There is no consensus at all on the facts, and the values – the common good versus a risk of severe injury to my child – are in dispute. A large refusal of the “triple shots” would lead to a real danger of an epidemic of measles among the unvaccinated.
Assessing the Bigger Picture:-
In all such cases, the uncertainties go far beyond the merely “scientific”. When planners are considering the threats of future floods (a likely consequence of global climate change), their decisions face the prospect of conflicts. in all of these uncertainties are severe, and the various interests can all too easily be set against each other.
Statistical Errors
The same level of uncertainty can be found deep within science. In any experiment involving statistical techniques, a choice is made between the errors of Type I (rejecting a true hypothesis) and of Type II (accepting a false hypothesis). Normally, the Type I errors are deemed to be more serious, and researchers automatically tune their tests accordingly.
Problems of managing uncertainty lead us to the question of ignorance.
Sir Peter Medawar (1915–87) British immunologist and Nobel Prize laureate: "Science is the art of soluble".
This restricted view of science enhanced its power in the past. Now it presents perils for the future. To begin with, we are discovering that science seldom solves problems in neat packages – there are always extra bits that are not and cannot be solved. As in the case of the radioactive waste produced by nuclear power, these messy unsolved parts of the problem are typically neglected until they suddenly present crises in all dimensions.
The restriction of science to the “soluble” also has other, even deeper, effects on our vision of knowledge and the world. For it entails a total exclusion of ignorance from our view. Ignorance is not soluble by means of ordinary research. We therefore have no notion of its existence.
A choice of Ignorance : Recognition of ignorance becomes very important for one very practical problem in scientific activity: priorities and choices. For whenever a proposed research project is given a low priority, it is not undertaken. As a result, the chance of gaining new knowledge is lost; and in that respect we remain in ignorance.
if our society is relatively less interested in say - occupational health and alternative energy supplies than in hi-tech medicine and nuclear power, we remain in ignorance about these alternatives. What we "know" is selected by these priorities and choices. ..
In this way, we can speak of ignorance as politically and socially constructed.
“By focusing on ignorance rather than on knowledge, we can escape some of the relativistic, sceptical implications of constructionist theories of science. It is easier for us to imagine ignorance as being conditioned by values and power.” - J. Ravetz
Ignorance Squared
Ignorance of ignorance – or “ignorance-squared” – is a very recent phenomenon in European intellectual history. Continuously, from the time of Plato to that of Descartes, the ignorance of ignorance was a recognized category among philosophers. Socrates’ quest was for awareness of his own ignorance. Ignorance was also an important concept in Islamic, Indian and Chinese science and philosophy. Renaissance humanist writers gave prominence to ignorance-squared as the worst intellectual failing.
Ignorance is deadly serious when encountered in the selection of research and in gauging the dangers of proposed scientific innovations. Modern science, with its myths of "objectivity", lacks the conceptual equipment to deal with ignorance-squared. Uncertainty and ignorance of ignorance become pressing practical problems when safety becomes a major issue for science.
Ex Genetic Modified crops effect on ecology is not known, fish modified to grow faster died prematurely, GM potatoes instead of increasing starch and reducing sugar actually decreased the starch. Gm modified maize star link turned out to be an allergen and impacted other crops .
Increasing the Uncertainty Stakes
These isolated examples indicate the sorts of things that could happen, on an ever-increasing scale, as gene technology becomes established and routine. There is no way of knowing what sorts of harmful effects may occur; and some of them will certainly fail to be detected in standard safety checks. These cases, as well as the BSE (“mad cow” disease) crisis first in Britain then in Europe, show that our vast ignorance of possible harm is more important for policy than our limited knowledge of the possible pathways to that harm.
BOTH THE "SYSTEM UNCERTAINTIES" ANDTHE "DECISION STAKES" ARE ENORMOUS
BEYOND THE NORMAL
The combination of ignorance and uncertainty, as well as the practical changes to science – involving funding, commercialization, the complex issues of safety and new modes of knowledge production – all mean that science no longer functions in the “normal” way. We find ourselves in a situation that is far from normal. Whenever there is a policy issue involving science, we discover that ...
- Facts are uncertain.
- Values are in dispute.
- Stakes are high.
- Decisions are urgent.
- Complexity is the norm.
- Man-made risks may be running out of control.
- The safety of the planet and humanity is under serious threat.
POST-NORMAL SCIENCE
Post-Normal Science (PNS) begins with the realization that we need a new style of science. The old image, where empirical data led to true conclusions and scientific reasoning led to correct policies, is no longer plausible.
Post-normal science is the sort of inquiry that occurs at the contested interface of science and policy. It can include anything from scientists’ policy-related research to citizens’ dialogue on the quality of that research.
Selling the Post Normal Agenda
More specifically, post-normal science consists of a cycle of phases, constantly interacting, iterating and involving an agenda of issues.
- Policy – set in terms of general societal purposes, out of debate among the affected interests.
- Persons – who participates at any point, who selects them, by what criteria – and who selects the selectors?
- Problem – the defined task for the inquiry: recall that setting one problem excludes others and creates ignorance of the knowledge that they might have produced.
- Procedures – not just techniques, but also burden of proof: to what extent should absence of evidence of harm be taken as evidence of absence of harm?
- Product – who controls its management and diffusion, and who controls the controllers?
- Post-Normal Assessment – to what extent does the simple, tidy world of the laboratory or survey correspond to the complex, untidy world of policy and real experience?
- Scientific certainty is replaced by an extended dialogue.
- The “expert” is replaced by an “extended peer community” involving scientists, scholars, industrialists, journalists, campaigners, policy-makers and ordinary non-specialist citizens.
- “Hard facts” are replaced by “extended facts” which include not just published results but also personal experiences, local surveys and scientific information that was not intended for the public domain.
- Truth is replaced by Quality as the organizing principle.
- Scientific fundamentalism is replaced by the legitimacy of different perspectives and value-commitments from all those stakeholders around the table on a policy issue.
Both challenge traditional views of science but differ in
their focus and implications, especially regarding policy. Post-normal science
seeks to broaden the base of policy-relevant knowledge by including diverse
voices, whereas postmodern approaches encourage a critical examination of the
social processes and power relations that shape scientific knowledge, with
implications for how science is used in policy-making.
1. Post-normal science (PNS), introduced by Silvio
Funtowicz and Jerome Ravetz in their 1993 paper "Science for
the Post-Normal Age," emphasizes the complexity and uncertainty in
scientific issues that have significant societal implications. PNS argues that
in situations where "facts are uncertain, values in dispute, stakes
high, and decisions urgent," traditional scientific methods are
inadequate. It advocates for the inclusion of a broader range of
perspectives, including non-experts, in the scientific process. This
approach is particularly relevant for policy-making, where decisions must often
be made under conditions of uncertainty and high stakes. PNS suggests that
science must be democratized, involving stakeholders in the knowledge
production process to ensure that policies are socially robust and ethically
sound.
2. Postmodern approaches to science, including constructionist analysis, focus on the idea that scientific knowledge is socially constructed. Key proponents, such as Bruno Latour in "Science in Action" (1987) and Steve Woolgar in "Laboratory Life" (1979), argue that scientific facts are not simply discovered but are the result of social processes, negotiations, and power dynamics within the scientific community. This perspective critiques the notion of objective truth in science, highlighting how cultural, political, and social factors shape scientific knowledge. In terms of policy implications, constructionist analysis suggests that policies based on scientific knowledge must consider the underlying social and power structures that influence that knowledge. It questions the neutrality of science and calls for a more critical approach to how scientific knowledge is used in policy-making.
Key Differences in Policy Implications:
- Post-normal science promotes the idea of extended peer
communities, where policy decisions are informed by a wide array of
stakeholders, acknowledging the uncertainties and value-laden nature of the
issues at hand. It encourages transparency and inclusivity in policy-making.
- Postmodern approaches advocate for a critical examination of the power dynamics and social constructions that underpin scientific knowledge. In policy contexts, this means being wary of claims to objective knowledge and considering whose interests are being served by particular scientific narratives.
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