Encyclopedia of Sociology

CAUSAL INFERENCE MODELS

Kothari, Rajni 1970 Caste in Indian Politics. New Delhi:
Orient Longman.

Leach, E. R. (ed.) 1960 Aspects of Caste in South India,
Ceylon, and North-West Pakistan. Cambridge, Eng.:
Cambridge University Press.

Mahar, J. M. (ed.) 1972 The Untouchables in Contemporary
India. Tucson: University of Arizona Press.

Rudolph, L. I., and S. H. Rudolph 1960 ‘‘The Political
Role of India’s Caste Associations.’’ Pacific Affairs
33(1):5–22.

——— 1987 In Pursuit of Laxmi. Chicago: University of
Chicago Press.

Scott, James C. 1990 Domination And The Arts Of Resist-
ance: Hidden Transcripts. New Haven, Conn.: Yale
University Press.

Sheth, D. L. 1987 ‘‘Reservation Policy Revisited.’’ Eco-
nomic and Political Weekly, vol. 22, Nov.14.

Southall, Aidan W. 1970 ‘‘Stratification In Africa.’’ In
Leonard Plotnicov and Arthur Tuden, eds., Essays in
Comparative Social Stratification. Pittsburg, Pa.: Uni-
versity of Pittsburg Press.

Srinivas, M.N. 1962 Caste in Modern India. London: Asia
Publishing House.

——— 1969 Social Change in Modern India. Berkeley:
University of California Press.

Weiner, Myron 1983 ‘‘The Political Consequences of
Preferential Policies: A Comparative Perspective.’’
Comparative Politics 16(1):35–52.

Zelliot, Eleanor 1970 ‘‘Learning the Uses of Political
Means: The Mahars of Maharashtra.’’ In Rajni Kothari,
ed., Caste in Indian Politics. Delhi: Orient Longman.

RITA JALALI

CAUSAL INFERENCE MODELS

NOTE: Although the following article has not been revised for
this edition of the Encyclopedia, the substantive coverage is
currently appropriate. The editors have provided a list of
recent works at the end of the article to facilitate research and
exploration of the topic.

The notion of causality has been controversial
for a very long time, and yet neither scientists,
social scientists, nor laypeople have been able to
think constructively without using a set of explana-
tory concepts that, either explicitly or not, have

implied causes and effects. Sometimes other words

have been substituted, for example, consequences,

results, or influences. Even worse, there are vague

terms such as leads to, reflects, stems from, derives from,

articulates with, or follows from, which are often used

in sentences that are almost deliberately ambigu-

ous in avoiding causal terminology. Whenever

such vague phrases are used throughout a theo-

retical work, or whenever one merely states that

two variables are correlated with one another, it

may not be recognized that what purports to be an

‘‘explanation’’ is really not a genuine theoretical

explanation at all.

It is, of course, possible to provide a very

narrow definition of causation and then to argue

that such a notion is totally inadequate in terms of

scientific explanations. If, for example, one de-

fines causation in such a way that there can be only

a single cause of a given phenomenon, or that a

necessary condition, a sufficient condition, or both

must be satisfied, or that absolute certainty is

required to establish causation, then indeed very

few persons would ever be willing to use the term.

Indeed, in sociology, causal terminology was al-

most deliberately avoided before the 1960s, ex-

cept in reports of experimental research. Since

that time, however, the notion of multivariate cau-

sation, combined with the explicit allowance for

impacts of neglected factors, has gradually re-

placed these more restrictive usages.

There is general agreement that causation can

never be proven, and of course in a strict sense no

statements about the real world can ever be ‘‘prov-

en’’ correct, if only because of indeterminacies

produced by measurement errors and the necessi-

ty of relying on evidence that has been filtered

through imperfect sense organs or fallible measur-

ing instruments. One may accept the fact that,

strictly speaking, one is always dealing with causal

models of real-world processes and that one’s infer-

ences concerning the adequacy of such models

must inevitably be based on a combination of

empirical evidence and untested assumptions, some

of which are about underlying causal processes

that can never be subject to empirical verification.

This is basically true for all scientific evidence,

though the assumptions one may require in mak-

ing interpretations or explanations of the underly-

ing reality may be more or less plausible in view of