OBJECTIVITY English meaning

What is objectivity

Widespread disagreement does not, however, indicate that there is no objective fact to be known. There are many examples of widespread disagreement regarding facts that are clearly objective. For example, there was once widespread disagreement about whether the universe is expanding or in a “steady state.” That disagreement did not indicate that there is no objective fact concerning the state of the universe. Thus, widespread disagreement regarding moral judgments would not, by itself, indicate that there are no objective moral facts. Further, one can perceive oneself as an object, in addition to knowing one’s subjective states fairly directly.

What is objectivity

They mainly differ with respect to the role of an explicitly subjective interpretation of probability. It presupposes, however, a clear-cut distinction between cognitive values on the one hand and contextual values on the other. The main issue for us in this debate is whether there are any reasons to believe that experimental results provide an aperspectival view on the world.

c. Objectivist Theories

Many philosophers would use the term “objective reality” to refer to anything that exists as it is independent of any conscious awareness of it (via perception, thought, etc.). Common mid-sized physical objects presumably apply, as do persons having subjective states. Subjective reality would then include anything depending upon some (broadly construed) conscious awareness of it to exist. Particular instances of colors and sounds (as they are perceived) are prime examples of things that exist only when there are appropriate conscious states. Particular instances of emotions (e.g., my present happiness) also seem to be a subjective reality, existing when one feels them, and ceasing to exist when one’s mood changes.

What is objectivity

Kuhn’s analysis is built on the assumption that scientists always view research problems through the lens of a paradigm, defined by set of relevant problems, axioms, methodological presuppositions, techniques, and so forth. Scientific progress—and the practice of normal, everyday science—happens within a paradigm that guides the individual scientists’ puzzle-solving work and that sets the community standards. The contents of an individual’s experiences vary greatly with his perspective, which is affected by his personal situation, and the details of his perceptual apparatus, language and culture. The appearance of a tree will change as one approaches it but—according to common sense and most philosophers—the tree itself doesn’t. A room may feel hot or cold for different persons, but its temperature is independent of their experiences. In epistemology, Plato accordingly distinguishes the highest knowledge as knowledge of the highest reality, the Forms.

Nevertheless, there is something appealing in the idea that factual disagreements can be settled by the very facts themselves, that explanations and predictions grounded in what’s really there rather than in a distorted image of it. The ideal of objectivity has been criticized repeatedly in philosophy of science, questioning both its desirability and its attainability. This article focuses on the question of how scientific objectivity should be defined, whether the ideal of objectivity is desirable, and to what extent scientists can achieve it.

Objectivity as Absence of Normative Commitments and the Value-Free Ideal

Assuming that reality is consistent, it follows that your and my logically incompatible judgments about a thing cannot both be true; intersubjective disagreement indicates error for at least one of us. One can also argue that agreement indicates probable truth, because it is unlikely that you and I would both be wrong in our judgment regarding an object and both be wrong in exactly the same way. Conversely, if we were both wrong about some object, it is likely that we would have differing incorrect judgments about it, since there are innumerable ways for us to make a wrong judgment about an object. Finally, we discuss Feyerabend’s radical criticism of a rational scientific method that can be mechanically applied, and his defense of the epistemic and social benefits of personal “bias” and idiosyncrasy. Summing up our findings, neither of the two major frameworks of statistical inference manages to eliminate all sources of personal bias and idiosyncrasy. The Bayesian considers subjective assumptions to be an irreducible part of scientific reasoning and sees no harm in making them explicit.

  1. In his book Trust in Numbers, Theodore Porter pursues this line of thought in great detail.
  2. In this view, science is objective to the degree that it succeeds at discovering and generalizing facts, abstracting from the perspective of the individual scientist.
  3. Both cognitive and contextual value judgments guide these choices and are themselves influenced by their results.
  4. Agreement in different subjects’ judgments (20°C) is often taken to be indicative of objectivity.

While unbalanced allocations can certainly happen by chance, randomization still provides some warrant that the allocation was not done on purpose with a view to promoting somebody’s interests. A priori, the experimental procedure is thus more impartial with respect to the interests at stake. It has thus been argued that RCTs in medicine, while no guarantor of the best outcomes, were adopted by the U.S. Food and Drugs Administration (FDA) to different degrees during the 1960s and 1970s in order to regain public trust in its decisions about treatments, which it had lost due to the thalidomide and other scandals (Teira and Reiss 2013; Teira 2010).

It could also refer to a judgment based on evidence that is of necessity available only to some subjects. Debates about positivism, relativism, and postmodernism are relevant to evaluating these concepts’ importance and the distinction between them. On the other hand, it is not clear that economists and other social scientists qua social scientists shouldn’t participate in a debate about social goals. For one thing, trying to do welfare analysis in the standard Weberian way tends to obscure rather than to eliminate normative commitments (Putnam and Walsh 2007). Obscuring value judgments can be detrimental to the social scientist as policy adviser because it will hamper rather than promote trust in social science. For another, economists are in a prime position to contribute to ethical debates, for a variety of reasons, and should therefore take this responsibility seriously (Atkinson 2001).

A subjectivist could regard the statement “Torture is immoral,” for example, as merely expressing the feeling of abhorrence among members of a certain culture, or among people in general. History as a discipline has wrestled with notions of objectivity from its very beginning. While its object of study is commonly thought to be the past, the only thing historians have to work with are different versions of stories based on individual perceptions of reality and memory.

Issues in the Special Sciences

For example, the prior degree of belief in hypothesis \(H\), written \(p(H)\), can in principle take any value in the interval \([0,1]\). Simultaneously held degrees of belief in different hypotheses are, however, constrained by the laws of probability. After learning evidence E, the degree of belief in \(H\) is changed from its prior probability \(p(H)\) to the conditional degree of belief \(p(H \mid E)\), commonly called the posterior probability of \(H\). Feminist philosophers (e.g., Harding 1991; Okruhlik 1994; Lloyd 2005) have argued that science often carries a heavy androcentric values, for instance in biological theories about sex, gender and rape. The charge against these values is not so much that they are contextual rather than cognitive, but that they are unjustified.


For instance, when the results of an experiment are incorrect because of malfunctioning equipment, we do not worry about objectivity—we just say that the results should not be taken into account. […] So it is only when the epistemic risk is related to our own failings, and is hard to avert, that we start talking about objectivity. Illusions, subjectivity, idiosyncrasies, and collective biases are important epistemic risks arising from our imperfections as epistemic agents. On the other hand, RCTs can be regarded as “debiasing procedure” because they prevent researchers from allocating treatments to patients according to their personal interests, so that the healthiest (or smartest or…) subjects get the researcher’s favorite therapy.

In epistemology and theory of knowledge

“Minimal” doesn’t mean zero, however, and indeed this procedure makes an important presupposition (in this case a metaphysical assumption about the one-valuedness of a physical quantity). Moreover, the procedure yielded at best a reliable instrument, not necessarily one that was best at tracking the uniquely real temperature (if there is such a thing). That said, Douglas’ proposal is not very concrete when it comes to implementation, e.g., regarding the way diverse values should be balanced. First, no standpoint is, just in virtue of being in the middle, evidentially supported vis-à-vis more extreme positions. Second, these middle positions are also, from a practical point of view, the least functional when it comes to advising policy-makers.

3 Feyerabend: The Tyranny of the Rational Method

Causal relations in the social and biomedical sciences hold on account of highly complex arrangements of factors and conditions. Whether for instance a substance is toxic depends on details of the metabolic system of the population ingesting it, and whether an educational policy is effective on the constellation of factors that affect the students’ learning progress. If an RCT was conducted successfully, the conclusion about the effectiveness of the treatment (or toxicity of a substance) under test is certain for the particular arrangement of factors and conditions of the trial (Cartwright 2007). Thus, Bayesian inference, which analyzes statistical evidence from the vantage point of rational belief, provides only a partial answer to securing scientific objectivity from personal idiosyncrasy. Bayesian inference quantifies scientific evidence by means of probabilities that are interpreted as a scientist’s subjective degrees of belief. The Bayesian thus leaves behind Carnap’s (1950) idea that probability is determined by a logical relation between sentences.