SOCIAL SCIENTIFIC INQUIRY
Characteristics of Social Science
Introduction
One of the livelier academic debates of recent years has concerned the “scientific” status of those disciplines gathered under the rubric of the social sciences-typically including sociology, political science, social psychology, economics, anthropology, and sometimes fields such as geography, history, communications, and other composite and specialty fields, basically at issue like whether human behavior can be subjected to scientific study.
It is a firm assumption of social scientists now-a-days that social behaviour can be subjected to scientific study as legitimately as can atoms, cells and so forth. Like physical scientists, social scientists seek to discover regularity and order. The social scientist looks for regularity in social behavior. He does this through careful observation and measurement, discovery of relationship, and framing of models and theories.
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Aggregate social behaviour can be measured systematically as well. The political scientist can determine, the election-day voting behavior of the entire electorate or of individual precincts. The amount of traffic over a given section of highway can be measured at different points of time. Consumer’s behaviour could be measured. Preference patterns for a product can also be measured.
Attitudes may be measured, although this is a point of broad disagreement. For example, anti-Semitic prejudice can be measured by determining individual acceptance or rejection of beliefs and perspectives representing such prejudice. Religiosity, political liberalism, conservatism, authoritarianism, taste and preferences such as brand preferences, buyer’s attitude and similar variables can be measured.
However, scientific measurements must be judged on the basis of their utility for inquiry, rather than on the basis of absolute truth. For example, while measuring religiosity of people a social scientist can never hope to describe a person as religious and some one else, irreligious in absolute sense. This is more so when a social scientist tries to measure qualitative variables. When we measure socio-economic variables like intelligence, brand preference, brand loyalty, industrialization, risk evasiveness etc we use proxy variables. In this context, we ask ourselves questions such as: Is this measure the true representation of the variables under consideration? Or are we going nearer the variable with this measure? It may be mentioned that in the absence of a true measure, a proxy variable works as a representative. We use these on the basis of their utility rather than absolute truth. For example, we use IQ Test scores to represent intelligence. Similarly we may use a composite index to represent level of development.
Discovering Social Regularities
There is a tendency to regard the subjects of the physical sciences as more regular than those of the social sciences. A heavy object falls to earth every time it is released, while a man may vote for a candidate in one election and against him in the next. Similarly, ice always melts when heated, while seemingly religious people do not always attend place of worship. While these particular examples are generally true, there is a danger in going on to discount the existence of social regularities altogether- The existence of observable social norms denies this conclusion.
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Some social norms are prescribed by the formal institutions of a society. For example, only person as of a certain age or older are permitted to vote in elections. In American society, men were drafted into the armed forces, but women were not. In traditional Muslim society women were not allowed to pray inside the Mosque along with men. Such formal prescriptions, then, regulate, or regularize, social behavior.
Besides formal prescriptions, other social norms can be observed. Registered Republicans are more likely to vote for Republican candidates than are registered Democrats. University professors tend to earn more money than unskilled laborers. Women tend to be more religious than men. There could be a variety of such social norms, which we observe in our day-to-day life.
Reports by social scientists of such regularities are often subject to three types of criticism. First, it may be charged that the report is trivial, that everyone was aware of the regularity. Second, contradictory cases may be cited, indicating that the observation is not wholly true. And third, it may be argued that the people involved could upset the observed regularity if they wished.
Regularities in social science is not a question of triviality. Even if such regularities are known by everyone, social scientists test these empirically and test hypotheses to formulate theories.
The criticism that given generalization from social science are subject to dis-confirmation in specific cases is not a sufficient challenge to the scientific character of the inquiry. Thus it is not sufficient to note that a given man is more religious than a given woman. It may so happen a given man is more religious than an given woman. Social regularities represent probabilistic patterns, and a general relationship between two variables need not be true in 100 percent of the observable cases. All voters in an election could suddenly switch to the underdog so as to frustrate the pollster.
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The charge that observed social regularities could be upset through the conscious will of the actor is not a sufficient challenge to social science, even though there does not seem to be a parallel situation in the physical sciences. (Presumably an object cannot resist falling to earth “because it wants to.”) There is no denying the religious, right-wing bigot could go to the polls and vote for an agnostic, left-wing radical black if he wanted to upset political scientist studying the election. All voters in a election could suddenly switch to the underdog so as to frustrate the pollster. By the same token, workers could go to work early or stay home from work and thereby prevent the expected rush-hour commuter traffic. But these things do not happen sufficiently often to seriously threaten the observation of social regularities.
In spites of the criticisms, the fact remains that social norms do exist, and the social scientist can observe those norms. When norms change over time, the social scientist can observe and explain those changes. Ultimately, social regularities persist because they tend to make sense for the people involved in them. Whereas the social scientist may suggest that it is logical to expect a given type of person to behave in a certain manner, those people may very well agree with logical basis for the expectation. Thus, while the religious right-wing bigot could vote for the agnostics, left-wing radical black candidate, he would consider it stupid to do so.
In order to give scientific status to social sciences the social scientist argue that the social behaviour can be subjected to scientific inquiry since social behaviour could be measured and regularities & order in social behaviour could be established. In addition to the above they count several characteristic of the social science and compare those with the physical sciences. While comparing the social sciences and physical sciences with respect to the characteristics they argue that the social science and physical science differ with respect to degree only.
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The Characteristics of Social Science:
Logical Reasoning (Deduction & Induction): Science is fundamentally a rational activity, and scientific explanation must make sense. Religions may rest on revelations, custom or traditions, gambling on faith; but science must rest on logical reasoning.
Logic is a difficult and complex branch of philosophy, and a full delineation of systems of logic is well beyond the scope of this note. Perhaps a few examples will illustrate what is meant by science being logical. For example, a given event cannot, logically, cause another event that occurred earlier in time. The movement of a bullet cannot cause the explosion of the gunpowder propelling it. Thus science takes a different approach from the teleological views assumed by some religions. For example, some Christians believe that Jesus was destined to be crucified, and that this destiny thereby caused him to be betrayed and tried. Such a view could not be accepted within the logic of science.
In the logic of science, it is impossible for an object to have two mutually exclusive qualities. The flip of a coin cannot result in both a head or a tail. By contrast we might note that many deeply prejudiced people argue that Jews are both “clannish” (refusing to mix with non-Jews) and “pushy” (forcing themselves in with non-Jews).
Faced with such an assertion, the scientist would suggest that either one or both of the characterizations of Jews are untrue or that the two characteristics are being defined in such a way that they are not mutually exclusive,.
Similarly, a given event cannot have mutually exclusive results. Thus, getting a college education cannot make a man both wealthier and poorer at the same time. It is possible for a college education to result in wealth for one man and poverty for another just as some Jews might be described as clannish and others pushy, but contradictory results or descriptions fly in the face of logic and are intolerable to science.
This is not to say that science in practice is-wholly devoid of illogical assertions. Many readers will realize that physicists currently regard light as both particles and waves even though these are contradictory descriptions of the nature of light. This particular contradiction exists in science since light behaves as particles under some conditions and waves under others. As a result of this situation, physicists continue to use the two contradictory conceptualizations as they may be appropriate in given conditions. Nevertheless, such a situation represents a strain for the logic of science.
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Beyond this common-sense notion of logic, there are two distinct logical systems important to the scientific quest, referred to as deductive logic and inductive logic which could briefly be described as follows ;
Logicians distinguish between inductive reasoning (from particular instances to general principles, from facts to theories) and deductive reasoning (from the general to the particular, applying a theory to a particular case.
In induction one starts from observed data and develops a generalization which explains the relationships between the objects observed. On the other hand, in deductive reasoning one starts from some general law and applies it to a particular instance.
The classical illustration of deductive logic is the familiar syllogism: “All men are mortal; Socrates is a man; therefore Socrates is mortal.” A researcher might then follow up this deductive exercise with an empirical test of Socrates mortality. This is essentially the approach discussed as the “traditional perspective of science”.
Using inductive logic, the researcher might begin by noting that Socrates is mortal and observing a number of other mortals as well. He might then note that all the observed mortals were men, thereby arriving at the tentative conclusion that “all men are mortal.”
Deductive logic is very old as a system, dating at least to Aristotle. Moreover, this system was predominant in philosophy until the sixteenth or seventeenth century. The birth of modern science was marked by the rise of inductive logic in a variety of scientific contexts. Increasingly, the general conclusions derived from careful observations contradicted the general postulates that represented the anchoring points of many deductive systems.
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Using the deductive method, a researcher might derive a theoretical hypothesis regarding the nature of the relationship between two variables say for example a person’s education (X) and his income ( Y ).
The greater a person’s education (X) the greater his income ( Y ).
If we know the education of a person this hypothesis would permit us to estimate the person’s income.
Using the inductive method, the researcher begins with the observed reality. Next he attempts to find a general, regular pattern that closely corresponds to that reality. The pattern that he decides upon, then becomes his tentative conclusion regarding the relationship between variables X and Y. The example of levels of education & income could be extended to this.
Once again, the tentative conclusion reached by the inductive method correspond more closely to the observed reality than does the hypothesis used in the deductive method. (This need not be the case, but it frequently is.) Scientific conclusions should have both theoretical and empirical support. Generally speaking, the deductive method is stronger in the former, while the inductive method is stronger in the later.
Quite clearly, the best scientific research would involve both the inductive and deductive methods, used in a cyclical fashion. The researcher might begin with a derived hypothesis, modify it inductively, rethink his theoretical system, reformulate his hypothesis, and seek new observations. Replication is the key to this process and resolves the problems of both the deductive and inductive methods. Only repeated observation, yielding the same result or conclusion (replication), can assure the scientist that he has discovered-deductively, inductively, or both a general principle.
Determinism
Science is based on the assumption that all events have antecedent causes that can be identified and logically understood. For the scientist, nothing “just happens”; it happens for a reason. If a man catches a cold, if it rains today, if a ball seems to roll uphill, the scientist assumes that each of these events is susceptible to rational explanation.
Several caveats should be entered in this regard. First, scientists do not know, nor do they pretend to know, the specific causes of all events. They simply assume that such causes exist and can be discovered. Second, Science accepts multiple causation. A given event may have several causes. A few examples may be considered to explain this point.
(i) The voting decision in an election may have resulted from a number of different factors. And one event may have one cause, while a similar event may have a different cause. Two men may vote for the same candidate for different reasons, but it is assumed that reasons exist in each case.
(ii) Increment in prices of cars over the last few years have not been associated with significant decline in demand. This has been observed by a researcher and he might find several causes for this. A person’s preferences for a particular product may have several reasons such as his income, social status, his brand loyalty etc. Similar examples could be many when we consider behaviour of several variables in the economy.
Thus, an observed phenomenon may have several causes or determinants. However, science is based on a probabilistic form of determinism. For example, event A may result in Event B 90 percent of the time, or 70 percent of all Republicans may vote for a given political candidate, while only 23 percent of the Democrats do so. In this sense, then, political party affiliation would be said to determine voting behavior, even though the determination was not complete. Other factors might be introduced to explain the discrepancies. (Our other examples could also be extended here).
The deterministic posture of the social sciences represents its most significant departure from more traditional, humanistic examinations of social behavior. A social scientist tries to identify the observable and measurable explanations of social behaviour. He, by doing this, provides the logical basis for the examination of cause and effect in social scientific analysis.
Generalization
Science aims at general understanding rather than at the explanation of individual events. The scientist is typically less interested in understanding why a given ball falls to the earth when released from a height than in understanding why all such balls tend to do so. Similarly, the scientist is less interested in explaining why a given man voted as he did than in understanding why large groups of people voted as they did. A researcher is less interested in finding why a person would respond to changes in prices of commodity rather he is interested in the general behaviour of consumers when there are changes in prices. A manager is interested in finding in what happens to sale volume when advertising expenditure increases in general rather in a specific case.
This characteristic of science is related to its probabilistic determinism. It is conceivable that we could completely explain the reasons lying behind a given event-why a given man voted for candidate X. The scientist might conceivably discover every single factor that went into the voting decision. If he were successful in this, then presumably he could predict the voting behavior of identical persons with perfect accuracy. In the long run, however, such a capability would not provide much useful information about voting behavior in general. Similarly in case of changes in demand one could attempt to find the reason (s) such as changes in the prices, changes of prices of the substitutes, changes in income etc and try to generalize the consumers behaviour with much accuracy in a particular period of time.
Generalizability is an important characteristic of scientific discoveries. The discovery that red balls fall to earth at a given acceleration is less useful than the discovery that balls of all colors do so. Similarly, it is less useful to know that balls fall with a given acceleration at sea level, than to know that the acceleration of all falling balls can be determined from their altitude.
To the social scientist, a theory of voting behavior that applies only to whites is less useful than one that applies to voters of all races. A theory of religiosity that applies only to a particular religious group is less useful than one that applies to people of all religions or people with no religion at all. Similarly, an economic theory which applies to a group of people is less useful than one that has universal application.
While the social scientist often begins with an attempt to explain a rather more limited range of social behavior or the behavior of a limited subset of the population, his goal is normally to expand his findings to explain other forms of behavior and other subsets of the population.
Parsimony
As the previous sections indicate the scientist spends much of his effort in the attempt to discover the factors that determine types of events. At the same time, he attempts to discover those factors that do not determine the events. Thus, in determining the acceleration of a falling object, we discount its color as being irrelevant.
Like the physical scientist, the social scientist attempts to gain the most explanatory power out of the smallest number of variables. In many cases, the additional consideration of new variables adds explanatory and predictive power, but it also results in a more complicated model. And, in practice, the addition of more variables often reduces the generalizability of the explanation, since certain variables may have one effect among members of one subset of the population and a different effect among those of other subsets.
It should be noted that the parsimonious character of social science, like its deterministic posture, opens it to criticism than those holding a more individualistic view of human behavior. Whereas they would tend to explore the depths of idiosyncratic (a person’s particular way of thinking or behaving) factors resulting in a decision or action on the part of a given person, the social scientist consciously attempts to limit such inquiry.
The social scientist, (to continue with one of the earlier examples) then night attempt to explain overall voting behavior through the observation of, say, three or four variables. The critic might object that each of the voters had “many other individual reasons” for voting as he did, that the “limited number of variables” did not adequately explain the “depth” of decision making for any of the subjects under study. The problem here is that the social scientist has a special goal in all this. He is consciously attempting to gain the greatest amount of understanding from the smallest number of variables. Neither the scientist nor his critic in such a case is more correct than the other; they simply have different goals. We must fully understand the scientist’s goal, however, in order to recognize that this criticism is not a valid one. (The scientist’s goal is to find “general” voting behaviour!)
Ultimately, the scientist attempts to understand the reasons of the events, using as few explanatory factors as possible, In practice, of course, the number of explanatory factors taken into account typically increases the degree of determination achieved. For example a political scientist may achieve a certain degree of explanation of voting behavior through the use of only two factor, say party affiliation and social class. Another might achieve a more complete understanding by also taking into account such other factors as race, region of upbringing, sex, education, and so forth. (The former is more simple while the later is more complex).
Frequently, the scientist is forced to choose between simplicity, on the one hand, and degree of explanation on the other. However, he has to be judicious in opting for one with respect to reality and/or theoretical consistency (the other examples given in this note could be extended in this line.
Specificity
The social scientist, like the physical scientist, must specify his methods of measurement. Perhaps this is especially important in the Social sciences, since they deal with concepts more vaguely defined in common discourse. While the physicist defines “acceleration” more rigorously than the layman, the scientific definition is not greatly at variance with the common understanding of the term. Concepts such as “religiosity” and “prejudice” “Preferences” “choices” however have such varied meaning in common language that their rigorous definitions are not readily apparent.
In conducting a research project on the topic of prejudice/preferences, then, the scientist must generate a specific operationalization of the concept viz., prejudice/preferences. For example, he must find agreement/disagreement with several questionnaire statements that seem to indicate prejudice/preferences. In reporting his research, he will be careful to describe his operationalizations in detail so that the reader will know precisely how the concept has been measured. While a given reader may disagree with the operationalization, he will at least know what it is. A social scientist specifies a methodology of his research inorder to help the fellow researcher in replicating the findings and/or verifying the theory. This specifies precise description and mode of measurement in quantifying qualitative variables.
Empirical Verification
Science at its best results in the formulation of general laws or equations describing the world around us. Such formulations, however, are not useful unless they can be verified through the collection and manipulation of empirical data. A general theory relating to some human bahaviour would be useless unless it suggested ways in which data might be collected and unless it predicted the results that would be obtained from the analysis of those data. For example, consider when a physicist tells us that all objects fall to the ground when thrown. This is due to the gravitational force. And a chemist says that H20 is water. All these are empirically verifiable. In all such cases the scientist is unable to disconfirm the theory.
There is another way of viewing this characteristic. In a sense,’ no scientific theory can ever be proved. Let’s consider the case of gravity. Physicists tell us that a body falls to earth because of the general attraction that exists between physical bodies and that this relationship is affected by the mass of the bodies involved. Since Earth has a vast mass, a ball thrown out a window will move toward Earth. Such an explanation of gravity is empirically verifiable. A researcher can throw a ball out a window and observe that it falls to the earth, This does not prove the ‘truth of the theory of gravity, however. Rather, the researcher specified that if the ball does not fall to the earth, then the theory of gravity is incorrect. Since the ball is, in fact, observed to behave as expected, the theory of gravity has not been disconfirmed.
Thus, when we say that a scientific explanation must be subject to empirical testing, we mean, more precisely, that the researcher must be able to specify conditions under which the theory would be disproved. As he consistently fails to disprove the theory, then he may become confident that the theory is correct. But it is important to realize that he will never have proved it.
In the example of falling bodies, another theorist might note that the experimental ball was of the same color as the ground to which it fell. He might suggest, therefore, that bodies of the same color are attracted to each other- for whatever reason he might devise. The initial experiment, then would lend confirmation to both of the competing theories. The second theory, however, suggests a method of dis-confirmation. If a ball differing in color from the earth were thrown out the window, it should not fall to the earth. To do so would disconfirm the second theory. An appropriate second experiment would hopefully, result in an empirical dis-confirnation of the color-attraction theory.
To be useful, social scientific propositions and theories must also be testable in the real world. Thus it is useless to assert that religiosity is positively associated with prejudice without suggesting ways in which the two variables might be measured and the proposition tested. As in the physical sciences, the social scientist must be able to describe empirical conditions under which a given proposition would be judged incorrect, ways in which it night be disproved.
Religious belief, such as the existence of God, for example are not susceptible to empirical verification. Similarly, the assertion that members of a religious or racial groups are disloyal “in their hearts” even when they appear to act in a loyal manner is not subjected to empirical verification. However, many hypotheses regarding human social behaviour can be tested empirically. For example, it has been commonly believed ‘in America that women were incapable of reasoning as logically as men. Instead, women have been characterized as “flighty” and “emotional” in their thinking .processes. This notion – so comfortable for American men- could be tested empirically. Moreover, the recent success of women in the “thinking professions” suggests that a controlled empirical test would wipe out the common, comfortable belief.
Much social research is addressed to testing, with empirical data, those items of “common-sense” that “everybody knows are true”. Where “common-sense” notions are imprecise the social scientist doggedly specified them in a testable form and tests them. Then, he respecifies them in another testable form and retests them. Frequently, he discovers that “common-sense” doesn’t make much sense in terms of the empirical reality.
To summarise our above discussion, it may be pointed out that formulation of general laws or equations or models are not useful unless they can be verified through collection and manipulation of empirical data.
Explanation of social behaviour (equations or statistical models) must make sense and they must correspond to what is being actually observed. For example brand preference could be a function of awareness and economic status. However, such relationship will be meaningless unless the variables are specified in a certain way and data could be collected. The quantification of qualitative variable should represent the “construct” , and these variables should be capable of being measured.
Intersubjectivity:
It is frequently asserted that science is “objective” but such an assertion typically results in a good deal of confusion as to what “objectivity” is. Moreover, it has been noted increasingly in recent years that no scientist is completely objective in his work. All scientists are “subjective” to some extent-influenced by their personal motivations.
Science is “inter-subjective” means that two scientists with different subjective orientations would arrive at the same conclusion if each conducted the same experiment. The following example from political science should clarify this.
The tendency for intellectuals in America to align themselves more with the Democratic party than with the Republican Party has led many people to assume that Democrats as a group are better educated than Republicans. It is reasonable to assume that a Democratic Scientist would be happy with this view while a Republican Scientist would not. Yet, it would be possible for the scientist to agree on the design of a research project that would collect data from the American electorate relating to party affiliation and educational levels. The two scientists could then conduct independent studies of the subject, and both would discover that Republicans as a whole have a higher educational level than do Democrats. (This is due to the fact that the Democratic Party also attracts a larger proportion of working class voters than does the Republican party in America, while businessmen are more attracted to the Republican Party).
Both scientists with opposite subjective orientations-would arrive at the same empirical conclusion.
Clearly, scientists often disagree among themselves. They may offer grossly different explanations for a given event. Such disagreements, however, typically involve questions of conceptualization and definition. Thus, one social scientist may report that religiosity is positively related to prejudice, while another disagrees. The disagreeing scientist will, in all likelihood suggest that either or both of the variables have been incorrectly measured. He may conduct his own study, measuring the two variables differently, and report a negative relationship between them. If the first researcher had reported the design and execution of his study in precise and specific details, however, and the second were to replicate that study exactly, he should arrive at the same finding. This is what is meant by the inter-subjectivity of science.
Taking another example in the economy: A researcher reports that GNP of country and the level of industiralisation are positively related. Another researcher disagrees with this. He suggests that either or both the variables have been incorrectly measured. He conducts his own study measuring the two variables differently and reports a negative relationship or a stastistically insignificant relationship between the said variables. However, had the first researcher reported the design and execution of his study in precise and specific details and the second were only to replicate the study he would have arrived at the same empirical conclusions. Such observations could be related to inter-subjectivity of the researchers.
Openness to Modification:
It should be clear from the previous section that “science” does not provide a set of easy steps to the attainment of Truth. Two scientists, both adhering to the previously discussed characteristics of science, may arrive at quite different explanations of a given phenomenon. At a given time, there may be no way of evaluating their relative merits. If the two explanations contradict one another presumably both cannot be correct. Either one or both will later be proven incorrect, or else it will be discovered that the two explanations are not mutually exclusive after all.
Countless “scientific” theories of the past have subsequently been disproved and replaced by better ones. Current theories will eventually be replaced. More basically, we shall probably never discover absolute truth in any area of inquiry, (particularly in social sciences).
In an important sense science does not even seek Truth but rather utility. Scientific theories should not be judged on their relative truth value, but on the extent to which they are useful in understanding the world around us.
The characteristics of science/ Social Science that have been discussed above provide a set of guidelines that enhance the utility of discoveries and theories. Inquiries that seek to adhere to these characteristics will, in the long run, produce more useful discoveries than inquiries of another sort. Thus, one man may be able to predict the weather more accurately on the basis of his observation of associated phenomenon than all the scientific meteorologists in the world, but in the long run the scientists will contribute more to our general understanding of the nature of the weather.
No social theory is likely to survive indefinitely. Either a growing weight of disconfirming evidence will bring it down, or a newer, more parsimonious replacement will be found. In any event, no social science finding can be expected to withstand the long-term test of time.
Adapted from : The Practice of Social Research by E. R. Babbie.
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