WHY THIS ISSUE MERITS EXTRA ATTENTION • A MAJOR RISK FACTOR FOR PARTNER VIOLENCE BECAUSE IT IS SO PREVALENT, EVEN THOUGH THE EFFECT SIZE IS NOT LARGE • THE EVIDENCE IS STRONG • AN IMPORTANT SOCIAL GOAL, EVEN IF IT HAD NO EFFECT ON PARTNER VIOLENCE • A SPECIAL CASE OF CONFLICT THEORY • ILLUSTRATES MACRO-LEVEL RESEARCH USING STATES • Macro = the cases are social units rather than individual persons • Almost any social unit can be the cases • Geo-political units: Nations, States, Counties, Towns • Institutional units: Churches, ]Schools, Universities, Corporations, Unions • ILLUSTRATES HOW THIS AND OTHER MACRO-SOCIOLOGICAL CONCEPTS THAT AFFECT VIOLENCE ARE MEASURED • Social disorganization • Urbanization, ETC • ILLUSTRATES THE IMPORTANCE OF TAKING MULTIPLE THEORIES INTO ACCOUNT, NOT JUST ONE FAVORED THEORY They are not necessarily competing theories Can be “additive” Can interact, i.e. one can “moderate” the effect of the other
THE GENDER EQUALITY INDEX (SCALE) USED FOR THIS RESEARCH THREE SUB INDEXES AND AN OVERALL INDEX
Correlation with Gender Equality Index • A. One sentence on what the top correlation shows without using numbers • B. One sentence on how much confidence you can have in that result • 2. Same for the bottom correlation
CORRELATION WITH NOW MEMBERSHIP ILLUSTRATES LIMITATIONS OF CROSS-SECTIONAL DATA • NOW membership could be a cause – the members lobby for equality • NOW membership could be an effect of gender equality – in a society where women have rights and power, womenorganize to protect and enhance their situation • The correlation could reflect underlying condition that lead to both NOW membership and gender equality (“spurious correlation”) • * Shoe size example of spurious correlation • * Possible sources of spuriousness illustrated by correlations in chart 3 slides back • * These can be controlled. If relationship persists, rules out spurious correlation • Longitudinal study help can establish which came first, and therefore which is the cause and which is the effect, or if there is bi-directional causation. Time lagged correlations
196 0 1990 NOW MEMBERSHIP .42 NOW MEMBERSHIP .04 . .23 . .39 GENDER EQUALITY GENDER EQUALITY What can you conclude from the red coefficients? What can you conclude from the green coefficients?
SOCIAL DISORGANIZATION AS A MODERATOR VARIABLE Disorganization high: 1. High rates of PV regardless of equality 2. Little effect of Equality until the high half of equality Disorganization low: 1. Low rates of PV 2. Equality has strong effect & reaches near zero Shows how one aspect of society influences the effect of other aspects
PARTNER VIOLENCE AND HOMICIDE ARE CORRELATED ILLUSTRATES RELATION OF DIFFERENT TYPES OF VIOLENCE TO EACH OTHER 50 states r = .29
THE SAME THING CAN BE SHOWN FOR RACIAL INEQUALITY – THE GREATER THE DEGREE OF EQUALITY BETWEEN RACES, THE LOWER THE RATE OF VIOLENCE • SUPPOSE WOMEN WERE DOMINANT – WOULD THAT ALSO RESULT IN HIGHER RATES OF VIOLENCE?
DISCUSSION • Results suggest that steps to end wife assault must go beyond treatment and/or punishment of individual men • Treatment and punishment important, but not likely to be sufficient • Basic changes in the structure of society also needed • * Increasing social integration • * Equality between men and women in the society as a whole, • not just within the confines of the family.
SOME KEY POINTS FROM THIS LECTURE • INEQUALITY INCRESES THE PRBABILITY OF VIOLENCE In society, In the family • HOW CHARACTEREISTICS OF SOCIETY CAN BE MEASURED Equality, Social Disorganization • THERE ARE LARGE DIFFEENCES BETWEEN STATES IN GENDER EQUALLITY AND SOCIAL DISORGANIZATION • AN EXAMPLE OF THE MULTIPLE CAUSES OF VIOLENCE BETWEEN PARTNERS Male dominance is an important cause, but it is only one of many causes • GENDER EQUALITY IS CORRELATED WITH SOCIAL DISORGANIZATION Illustrates the fact that even highly desirable social changes can have undesirable aspects • THE LINK BETWEEN INEQUALITY IN RELATIONSHIPS AND VIOLENCE APPLIES: When women dominate as well as when men dominate In many different national and cultural contexts
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