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"[A]n objective account is one which attempts to capture the nature of the object studied in a way that does not depend on any features of the particular subject who studies it. An objective account is, in this sense, impartial, one which could ideally be accepted by any subject, because it does not draw on any assumptions, prejudices, or values of particular subjects. This feature of objective accounts means that disputes can be contained to the object studied." (Gaukroger, 2001, p. 10785).

Some people regard science as objective in this sense and this objectivity in science is often attributed with the property of scientific measurement that can be tested independent from the individual scientist (the subject) who proposes them. It is thus intimately related to the aim of testability and reproducibility. To be properly considered objective, the results of measurement must be communicated from person to person, and then demonstrated for third parties, as an advance in understanding of the objective world. Such demonstrable knowledge would ordinarily confer demonstrable powers of prediction or technological construction.

However, this traditional view about objectivity ignores several things. First, the selection of the specific object to measure is typically a subjective decision and it often involves reductionism. Second, and potentially much more problematic, is the selection of instruments (tools) and the selection of the measurement methodology. Some features or qualities of the object under study will be ignored in the measurement process and the limitations of the chosen instruments will cause data to be left out of consideration. In addition to these absolute limits of objectivity surrounding the measurement process, any given community of researchers often shares certain "subjective views" and this subjectivity is therefore built in to the conceptual systems; and it can even be built in to the design of the tools used for measurement. Total objectivity is arguably not even possible in some—or maybe all—situations.

Problems arise from not understanding the limits of objectivity in scientific research, especially when results are generalized. Given that the object selection and measurement process are typically subjective, when results of that subjective process are generalized to the larger system from which the object was selected, the stated conclusions are necessarily biased.

It is the theory that decides what we can observe. -- Albert Einstein

Objectivity should not be mixed up with scientific consensus: Scientist may agree at one point in time but later discover that this consensus represented a subjective point of view.


Objectivity in measurement

To avoid the variety in subjective (equivocal) interpretation of quantifying terms such as "green", "hot", "large", "considerable", and "negligible", scientists strive, where possible, to eliminate human senses by use of standardized measuring tools (meter stick, stopwatch, thermometer, etc) and mechanical/electronic measuring instruments (spectrometer, voltmeter, timer, oscilloscope, gravimeter, etc) for performing the actual measuring process, eliminating much of the perceptive variability of individual observers. The results of measurements are expressed on a numerical scale of standard units - so that everybody else understands them the same way. Where nominal data must need be used, the ideal is to use "hard", objective criteria for assigning the classifications (see Operational definition), such that different classifiers would produce the same assignments.

Objectivity in experimental set-up and interpretation

Another methodological aspect is the avoidance of bias, which can involve cognitive bias, cultural bias, or sampling bias. Methods for avoiding or overcoming such biases include random sampling and double-blind trials.

Deliberate misrepresentation

Next to unintentional but possibly systematic error, there is always the possibility of deliberate misrepresentation of scientific results, whether for gain, for fame, or for ideological motives. When such cases of scientific fraud come to light, they usually give rise to an academic scandal, but it is (obviously) not known how much fraud goes undiscovered. However, for results that are considered important, other groups will try to repeat the experiment and fail, bringing these negative results into the scientific debate.

The role of the scientific community

Various scientific processes, such as peer reviews, the discussions at scientific conferences and other meetings where results are presented, and the efforts at replicating results, all are part of a social process whose purpose is to strengthen the objective aspect of the scientific method.

Philosophical problems with scientific objectivity

Based on a historical review of the development of certain scientific theories, in his book The Structure of Scientific Revolutions scientist and historian Thomas Kuhn raised some philosophical objections to claims of the possibility of scientific understanding being truly objective. In Kuhn's analysis, scientists in different disciplines organise themselves into de facto paradigms, within which scientific research is done, junior scientists are educated, and scientific problems are determined. The implicit social hierarchy of a scientific paradigm ensures that only scientists who are thoroughly immersed in the intellectual construction of the paradigm acquire the reputation and status to pronounce authoritatively on matters of dispute, and those scientists have a vested interest in maintaining the status quo (which confers on them this de facto position of authority).

When observational data arises which appears to contradict or "falsify" a given scientific paradigm, scientists within that paradigm have not, historically, immediately rejected the paradigm in question (as Sir Karl Popper's philosophical theory of falsificationism would have them do) but have gone to considerable lengths to resolve the apparent conflict without rejecting the paradigm, through ad hoc variations to the theory, sympathetic interpretations of the data which allow for assimilation, determination that the "conundrum" the data was obtained to explain in the first place is misconceived, or in extreme cases simply ignoring the data altogether (for example, on the basis of the lack of scientific credentials of its source).

Thus, Kuhn argues, the failure of a scientific revolution is not an objectively measurable, deterministic event, but a far more contingent shift in social order. A paradigm will go into a crisis when a significant portion of the scientists working in the field lose confidence in the paradigm, regardless of their reasons for doing so. The corollary of this observation is that the primacy of a given paradigm is similarly contingent on the social order amongst scientists at the time it gains ascendancy.

Kuhn's theory has been criticised (by Richard Dawkins and Alan Sokal, among others) as presenting a profoundly relativist view of scientific progress. In a postscript to the third edition of his book, Kuhn denied being a relativist.


  • Daston, Lorraine and Peter Galison. Objectivity. New York: Zone Books, 2007.
  • Dawkins, Richard (2003): A Devil’s Chaplain: Selected Essays, Phoenix 2004.
  • Gaukroger, S. (2001). Objectivity, History of. IN: Smelser, N. J. & Baltes, P. B. (eds.) International Encyclopedia of the Social and Behavioral Sciences. Oxford. (Pp. 10785- 10789).
  • Kuhn, Thomas (1962): The Structure of Scientific Revolutions, University of Chicago Press, 3rd Ed., 1996.
  • Porter, Theodore M. (1995): Trust in Numbers: The Pursuit of Objectivity in Science and Public Life, Princeton University Press, 1995.
  • Restivo, Sal (1994): Science, Society, and Values: Toward a Sociology of Objectivity, Lehigh University Press, 1994.
  • Sokal, Alan & Bricmont, Jean (1997): Intellectual Impostures: Postmodern Philosophers’ Abuse of Science, Profile Books, 2003.


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