In science and history, consilience (also convergence of evidence or concordance of evidence) is the principle that evidence from independent, unrelated sources can "converge" on strong conclusions. That is, when multiple sources of evidence are in agreement, the conclusion can be very strong even when none of the individual sources of evidence is significantly so on its own. Most established scientific knowledge is supported by a convergence of evidence: if not, the evidence is comparatively weak, and there will probably not be a strong scientific consensus.
The principle is based on unity of knowledge; measuring the same result by several different methods should lead to the same answer. For example, it should not matter whether one measures distances within the Giza pyramid complex by laser rangefinding, by satellite imaging, or with a meter stick – in all three cases, the answer should be approximately the same. For the same reason, different dating methods in geochronology should concur, a result in chemistry should not contradict a result in geology, etc.
The word consilience was originally coined as the phrase "consilience of inductions" by William Whewell (consilience refers to a "jumping together" of knowledge).[1][2] The word comes from Latincom- "together" and -siliens "jumping" (as in resilience).[3]
Description
Consilience requires the use of independent methods of measurement, meaning that the methods have few shared characteristics. That is, the mechanism by which the measurement is made is different; each method is dependent on an unrelated natural phenomenon. For example, the accuracy of laser range-finding measurements is based on the scientific understanding of lasers, while satellite pictures and meter (yard-)sticks rely on different phenomena. Because the methods are independent, when one of several methods is in error, it is very unlikely to be in error in the same way as any of the other methods, and a difference between the measurements will be observed.[note 1] If the scientific understanding of the properties of lasers were inaccurate, then the laser measurement would be inaccurate but the others would not.
As a result, when several different methods agree, this is strong evidence that none of the methods are in error and the conclusion is correct. This is because of a greatly reduced likelihood of errors: for a consensus estimate from multiple measurements to be wrong, the errors would have to be similar for all samples and all methods of measurement, which is extremely unlikely. Random errors will tend to cancel out as more measurements are made, due to regression to the mean; systematic errors will be detected by differences between the measurements (and will also tend to cancel out since the direction of the error will still be random). This is how scientific theories reach high confidence – over time, they build up a large degree of evidence which converges on the same conclusion.[note 2]
When results from different strong methods do appear to conflict, this is treated as a serious problem to be reconciled. For example, in the 19th century, the Sun appeared to be no more than 20 million years old, but the Earth appeared to be no less than 300million years (resolved by the discovery of nuclear fusion and radioactivity, and the theory of quantum mechanics);[4] or current attempts to resolve theoretical differences between quantum mechanics and general relativity.[5]
Significance
Because of consilience, the strength of evidence for any particular conclusion is related to how many independent methods are supporting the conclusion, as well as how different these methods are. Those techniques with the fewest (or no) shared characteristics provide the strongest consilience and result in the strongest conclusions. This also means that confidence is usually strongest when considering evidence from different fields because the techniques are usually very different.
For example, the theory of evolution is supported by a convergence of evidence from genetics, molecular biology, paleontology, geology, biogeography, comparative anatomy, comparative physiology, and many other fields.[6] In fact, the evidence within each of these fields is itself a convergence providing evidence for the theory. (As a result, to disprove evolution, most or all of these independent lines of evidence would have to be found to be in error.[2]) The strength of the evidence, considered together as a whole, results in the strong scientific consensus that the theory is correct.[6] In a similar way, evidence about the history of the universe is drawn from astronomy, astrophysics, planetary geology, and physics.[2]
Finding similar conclusions from multiple independent methods is also evidence for the reliability of the methods themselves, because consilience eliminates the possibility of all potential errors that do not affect all the methods equally. This is also used for the validation of new techniques through comparison with the consilient ones. If only partial consilience is observed, this allows for the detection of errors in methodology; any weaknesses in one technique can be compensated for by the strengths of the others. Alternatively, if using more than one or two techniques for every experiment is infeasible, some of the benefits of consilience may still be obtained if it is well-established that these techniques usually give the same result.
Consilience is important across all of science, including the social sciences,[7] and is often used as an argument for scientific realism by philosophers of science. Each branch of science studies a subset of reality that depends on factors studied in other branches. Atomic physics underlies the workings of chemistry, which studies emergent properties that in turn are the basis of biology. Psychology is not separate from the study of properties emergent from the interaction of neurons and synapses. Sociology, economics, and anthropology are each, in turn, studies of properties emergent from the interaction of countless individual humans. The concept that all the different areas of research are studying one real, existing universe is an apparent explanation of why scientific knowledge determined in one field of inquiry has often helped in understanding other fields.
Deviations
Consilience does not forbid deviations: in fact, since not all experiments are perfect, some deviations from established knowledge are expected. However, when the convergence is strong enough, then new evidence inconsistent with the previous conclusion is not usually enough to outweigh that convergence. Without an equally strong convergence on the new result, the weight of evidence will still favor the established result. This means that the new evidence is most likely to be wrong.
Science denialism (for example, AIDS denialism) is often based on a misunderstanding of this property of consilience. A denier may promote small gaps not yet accounted for by the consilient evidence, or small amounts of evidence contradicting a conclusion without accounting for the pre-existing strength resulting from consilience. More generally, to insist that all evidence converge precisely with no deviations would be naïve falsificationism,[8] equivalent to considering a single contrary result to falsify a theory when another explanation, such as equipment malfunction or misinterpretation of results, is much more likely.[8][note 3]
In history
Historical evidence also converges in an analogous way. For example: if five ancient historians, none of whom knew each other, all claim that Julius Caesar seized power in Rome in 49 BCE, this is strong evidence in favor of that event occurring even if each individual historian is only partially reliable. By contrast, if the same historian had made the same claim five times in five different places (and no other types of evidence were available), the claim is much weaker because it originates from a single source. The evidence from the ancient historians could also converge with evidence from other fields, such as archaeology: for example, evidence that many senators fled Rome at the time, that the battles of Caesar’s civil war occurred, and so forth.
Consilience has also been discussed in reference to Holocaust denial.
"We [have now discussed] eighteen proofs all converging on one conclusion...the deniers shift the burden of proof to historians by demanding that each piece of evidence, independently and without corroboration between them, prove the Holocaust. Yet no historian has ever claimed that one piece of evidence proves the Holocaust. We must examine the collective whole."[2]
That is, individually the evidence may underdetermine the conclusion, but together they overdetermine it. A similar way to state this is that to ask for one particular piece of evidence in favor of a conclusion is a flawed question.[6][9]
Outside the sciences
In addition to the sciences, consilience can be important to the arts, ethics and religion. Both artists and scientists have identified the importance of biology in the process of artistic innovation.[1]
History of the concept
Consilience has its roots in the ancient Greek concept of an intrinsic orderliness that governs our cosmos, inherently comprehensible by logical process, a vision at odds with mystical views in many cultures that surrounded the Hellenes. The rational view was recovered during the high Middle Ages, separated from theology during the Renaissance and found its apogee in the Age of Enlightenment.[1]
The Consilience of Inductions takes place when an Induction, obtained from one class of facts, coincides with an Induction obtained from another different class. Thus Consilience is a test of the truth of the Theory in which it occurs.
More recent descriptions include:
"Where there is a convergence of evidence, where the same explanation is implied, there is increased confidence in the explanation. Where there is divergence, then either the explanation is at fault or one or more of the sources of information is in error or requires reinterpretation."[11]
"Proof is derived through a convergence of evidence from numerous lines of inquiry--multiple, independent inductions, all of which point to an unmistakable conclusion."[6]
Edward O. Wilson
Although the concept of consilience in Whewell's sense was widely discussed by philosophers of science, the term was unfamiliar to the broader public until the end of the 20th century, when it was revived in Consilience: The Unity of Knowledge, a 1998 book by the author and biologist E. O. Wilson, as an attempt to bridge the cultural gap between the sciences and the humanities that was the subject of C. P. Snow's The Two Cultures and the Scientific Revolution (1959).[1] Wilson believed that "the humanities, ranging from philosophy and history to moral reasoning, comparative religion, and interpretation of the arts, will draw closer to the sciences and partly fuse with them" with the result that science and the scientific method, from within this fusion, would not only explain the physical phenomenon but also provide moral guidance and be the ultimate source of all truths.[12]
Wilson held that with the rise of the modern sciences, the sense of unity gradually was lost in the increasing fragmentation and specialization of knowledge in the last two centuries. He asserted that the sciences, humanities, and arts have a common goal: to give a purpose to understand the details, to lend to all inquirers "a conviction, far deeper than a mere working proposition, that the world is orderly and can be explained by a small number of natural laws." An important point made by Wilson is that hereditary human nature and evolution itself profoundly effect the evolution of culture, in essence, a sociobiological concept. Wilson's concept is a much broader notion of consilience than that of Whewell, who was merely pointing out that generalizations invented to account for one set of phenomena often account for others as well.[1]
A parallel view lies in the term universology, which literally means "the science of the universe." Universology was first promoted for the study of the interconnecting principles and truths of all domains of knowledge by Stephen Pearl Andrews, a 19th-century utopian futurist and anarchist.[1]
See also
Appeal to authority– An argument that justifies the conclusion via an appeal to authority
Appeal to tradition– Logical fallacy in which a thesis is deemed correct on the basis of tradition
↑ Note that this is not the same as performing the same measurement several times. While repetition does provide evidence because it shows that the measurement is being performed consistently, it would not be consilience and would be more vulnerable to error.
↑ Statistically, if three different tests are each 90% reliable when they give a positive result, a positive result from all three tests would be 99.9% reliable; five such tests would be 99.999% reliable, and so forth. This requires the tests to be statistically independent, analogous to the requirement for independence in the methods of measurement.
↑ More generally, anything which results in a false positive or false negative.
Related Research Articles
Empirical research is research using empirical evidence. It is also a way of gaining knowledge by means of direct and indirect observation or experience. Empiricism values some research more than other kinds. Empirical evidence can be analyzed quantitatively or qualitatively. Quantifying the evidence or making sense of it in qualitative form, a researcher can answer empirical questions, which should be clearly defined and answerable with the evidence collected. Research design varies by field and by the question being investigated. Many researchers combine qualitative and quantitative forms of analysis to better answer questions that cannot be studied in laboratory settings, particularly in the social sciences and in education.
Falsifiability is a deductive standard of evaluation of scientific theories and hypotheses, introduced by the philosopher of science Karl Popper in his book The Logic of Scientific Discovery (1934). A theory or hypothesis is falsifiable if it can be logically contradicted by an empirical test.
Observation in the natural sciences is an act or instance of noticing or perceiving and the acquisition of information from a primary source. In living beings, observation employs the senses. In science, observation can also involve the perception and recording of data via the use of scientific instruments. The term may also refer to any data collected during the scientific activity. Observations can be qualitative, that is, only the absence or presence of a property is noted, or quantitative if a numerical value is attached to the observed phenomenon by counting or measuring.
Statistics is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments.
The scientific method is an empirical method for acquiring knowledge that has characterized the development of science since at least the 17th century It involves careful observation, applying rigorous skepticism about what is observed, given that cognitive assumptions can distort how one interprets the observation. It involves formulating hypotheses, via induction, based on such observations; the testability of hypotheses, experimental and the measurement-based statistical testing of deductions drawn from the hypotheses; and refinement of the hypotheses based on the experimental findings. These are principles of the scientific method, as distinguished from a definitive series of steps applicable to all scientific enterprises.
A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. More generally, hypothesis testing allows us to make probabilistic statements about population parameters. More informally, hypothesis testing is the processes of making decisions under uncertainty. Typically, hypothesis testing procedures involve a user selected tradeoff between false positives and false negatives.
First formulated by David Hume, the problem of induction questions our reasons for believing that the future will resemble the past, or more broadly it questions predictions about unobserved things based on previous observations. This inference from the observed to the unobserved is known as "inductive inferences". Hume, while acknowledging that everyone does and must make such inferences, argued that there is no non-circular way to justify them, thereby undermining one of the Enlightenment pillars of rationality.
A scientific theory is an explanation of an aspect of the natural world and universe that can be repeatedly tested and corroborated in accordance with the scientific method, using accepted protocols of observation, measurement, and evaluation of results. Where possible, some theories are tested under controlled conditions in an experiment. In circumstances not amenable to experimental testing, theories are evaluated through principles of abductive reasoning. Established scientific theories have withstood rigorous scrutiny and embody scientific knowledge.
Scientific evidence is evidence that serves to either support or counter a scientific theory or hypothesis, although scientists also use evidence in other ways, such as when applying theories to practical problems. Such evidence is expected to be empirical evidence and interpretable in accordance with the scientific method. Standards for scientific evidence vary according to the field of inquiry, but the strength of scientific evidence is generally based on the results of statistical analysis and the strength of scientific controls.
Consilience: The Unity of Knowledge is a 1998 book by the biologist E. O. Wilson, in which the author discusses methods that have been used to unite the sciences and might in the future unite them with the humanities.
The term Inductive reasoning is used to refer to any method of reasoning in which broad generalizations or principles are derived from a body of observations. This article is concerned with the inductive reasoning other than deductive reasoning, where the conclusion of a deductive argument is certain given the premises are correct; in contrast, the truth of the conclusion of an inductive argument is at best probable, based upon the evidence given.
In its most common sense, methodology is the study of research methods. However, the term can also refer to the methods themselves or to the philosophical discussion of associated background assumptions. A method is a structured procedure for bringing about a certain goal, like acquiring knowledge or verifying knowledge claims. This normally involves various steps, like choosing a sample, collecting data from this sample, and interpreting the data. The study of methods concerns a detailed description and analysis of these processes. It includes evaluative aspects by comparing different methods. This way, it is assessed what advantages and disadvantages they have and for what research goals they may be used. These descriptions and evaluations depend on philosophical background assumptions. Examples are how to conceptualize the studied phenomena and what constitutes evidence for or against them. When understood in the widest sense, methodology also includes the discussion of these more abstract issues.
Internal validity is the extent to which a piece of evidence supports a claim about cause and effect, within the context of a particular study. It is one of the most important properties of scientific studies and is an important concept in reasoning about evidence more generally. Internal validity is determined by how well a study can rule out alternative explanations for its findings. It contrasts with external validity, the extent to which results can justify conclusions about other contexts. Both internal and external validity can be described using qualitative or quantitative forms of causal notation.
In logic, counterinduction is the practice of elaborating a paradigm that contradicts and helps to question the current one by comparison. Paul Feyerabend argued for counterinduction as a way to test unchallenged scientific theories; unchallenged simply because there are no structures within the scientific paradigm to challenge itself. For instance, Feyerabend is quoted as saying the following:
The history of scientific method considers changes in the methodology of scientific inquiry, as distinct from the history of science itself. The development of rules for scientific reasoning has not been straightforward; scientific method has been the subject of intense and recurring debate throughout the history of science, and eminent natural philosophers and scientists have argued for the primacy of one or another approach to establishing scientific knowledge.
This timeline of the history of the scientific method shows an overview of the development of the scientific method up to the present time. For a detailed account, see History of the scientific method.
Inductivism is the traditional and still commonplace philosophy of scientific method to develop scientific theories. Inductivism aims to neutrally observe a domain, infer laws from examined cases—hence, inductive reasoning—and thus objectively discover the sole naturally true theory of the observed.
The Hedgehog, the Fox, and the Magister's Pox (2003) is Stephen Jay Gould's posthumous volume exploring the historically complex relationship between the sciences and the humanities in a scholarly discourse.
Popper and After: Four Modern Irrationalists is a book about irrationalism by the philosopher David Stove. First published by Pergamon Press in 1982, it has since been reprinted as Anything Goes: Origins of the Cult of Scientific Irrationalism and Scientific Irrationalism: Origins of a Postmodern Cult.
The philosophy of statistics involves the meaning, justification, utility, use and abuse of statistics and its methodology, and ethical and epistemological issues involved in the consideration of choice and interpretation of data and methods of statistics.
↑ consilienceOnline etymology dictionary. Retrieved 17 October 2015.
↑ Bahcall, John N. (29 June 2000). "How the sun shines". NobelPrize.org. Retrieved 23 January 2023.
↑ Weinberg, S (1993). Dreams of a Final Theory: The Scientist's Search for the Ultimate Laws of Nature. Vintage Books, New York.
1 2 3 4 Scientific American, March 2005. "The Fossil Fallacy." Link.
↑ For example, in linguistics: see Converging Evidence: Methodological and theoretical issues for linguistic research, edited by Doris Schonefeld.Link.
1 2 For example, see Imre Lakatos., in Criticism and the Growth of Knowledge (1970).
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