racial bloc voting and political mobilization in south carolina

R A C I A L B L O C V O T I N G A N D P O L I T I C A L

M O B I L I Z A T I O N IN S O U T H C A R O L I N A

James W. Loewen

Over the last quarter century, major changes in Southern social structure have been accompanied by more positive white attitudes on racial issues. Has voting behavior reflected these changes? The question has important consequences. The degree of racial bloc voting and political mobilization often determines outcomes not only of elections but also of voting rights lawsuits. Data from 130 black/white elections in South Carolina were used to determine rates of racial polarization and mobilization. Bloc voting remained high. Other variables had little explanatory power. Some secondary factors helped explain variations in the generally high levels of polarization by race.

In the first decade following the Voting Rights Act (1965-1975), blacks registered in large numbers. Black political aspirations were frustrated, however, because whites replied by bloc voting for white candidates. Black bloc voting quickly rose to levels nearly as high. Except in areas of very heavy black population concentration, whites usually won elections, but blacks usually won lawsuits under the Voting Rights Act. What is the situation since 1975? Has the polarization died down, as the violent resistance to school desegregation dwindled after a decade?

Election outcomes present a confusing pattern. On one hand, victories by black candidates for mayor in Chapel Hill, New Orleans, and other cities, and for governor in Virginia, herald a new era of black political power, sometimes accompanied by increased white willingness to vote for black candidates. On the other hand, the national proportion of public officials who are black is still only about 5 percent, while blacks make up 12 percent of the population. Thernstrom states that polarization has

24 The Review of Black Political Economy/Summer 1990

waned in the districts covered by the Voting Rights Act: "The majority- white county, city, or district in which whites vote as a solid bloc against any minority candidate is now unusual."l She offers no data to buttress this conclusion, however. Nor have other scholars published systematic studies on minority and white voting behavior over time.

It is particularly important to see if racial bloc voting (RBV) persists in jurisdictions covered by the 1982 extension of the Voting Rights Act, because RBV is key to the application of Section 2 of that act. 2 Indeed, Thernstrom suggests the Voting Rights Act and decisions relying on it represent judicial overkill, unless "one a s s u m e s . . , consistent and persistent racial bloc voting."3 Questions that need answers include:

--what is the degree of RBV? --is RBV increasing or decreasing over time? --is RBV uniform across different types of elections and different

social structures? --what variables correlate with nonracial or crossover voting?

The present study seeks to answer these questions be examining 130 South Carolina elections held between 1972 and 1985. South Carolina has its own unique history and social structure; results can be generalized to other states only with caution. South Carolina does contain urban and rural areas, areas of intense black political mobilization and places where blacks are still under effective white political control, black-majority districts and districts where blacks make up only a small fraction of the population. Thus its political landscape is varied enough to test various hypotheses about the persistence of RBV.

METHODS AND DATA

South Carolina has an additional virtue as a site for this kind of analysis: the state keeps marvelous records. Because race is coded when citizens register, and because voter sign-ins at each election are also computer-entered, accurate turnout figures are available, by race and precinct, for every election. 4 For elections between 1972 and 1983, U. S. Department of Justice attorneys supplied election results by precinct from the official reports or files of the State Election Commission, the state committee of the appropriate political party, or if unavailable from those sources, from newspaper reports. From state sources, representatives of the Department of Justice supplied turnout and registration data by county

Loewen 25

and by precinct by race (except Beaufort County, 6/13/78, for which turnout data were unavailable; I substituted registration data as of May 31, 1979.) The South Carolina NAACP supplied 1984-1985 data from the same sources. 5

Contests pitting black candidate(s) against white candidate(s) for a single office offer the clearest sites for examining racial polarization. Because data from so many black/white contests were available, white/ white and black/black contests were omitted from the analysis. For the same reason, I omitted multimember contests and contests that involved only county subdistricts. In an election with white-black contests for several county positions, I usually limited my analysis to that contest in which the black candidate(s) did besto 6 In all, I analyzed 130 elections, including:

(a) the statewide Democratic primary, 6/13/78, for Secretary of State, and runoff, 6/27/78;

(b) 4 contests for U. S. House of Representatives; (c) 21 contests for State Senator; (d) 19 contests for State House of Representatives; 7 and (e) 84 contests for local (county) offices.

These data were analyzed by ecological regression, using the standard two-equation method, which yielded the voting behavior of each racial group, with little error. 8 RBV totals by county for the 1978 statewide runoff for Secretary of State were also combined into a new statewide data set, along with county-level Census data for income, education, and percent urban. I then applied multiple correlation and regression to investigate effects on voting patterns from factors other than race and to see if the effect due to race held up when these factors were controlled for.

RACIAL BLOC VOTING PERSISTED AMONG WHITES AND INCREASED AMONG BLACKS

Table 1 shows RBV among blacks and whites for the 130 elections, arranged by year. A reasonable summary would be that voting was polarized throughout the period. Eighty percent of the variance in these election returns is associated with the racial composition of the precinct or county. Overall, whites cast about 90 percent of their votes for white candidates, while blacks cast 85 percent for black candidates. Thus the primary determinant of election results in these interracial contests was the racial composition of the turnout. 9


T A B L E 1 M e a n Percentages of Racial Bloc Voting and M e a n Corre la t ion Coefficients,

by Year , 1972-1984, South Caro l ina

Year N of Z of Whites Z of Blacks r r 2 Eleetions Votin~ White Votlng Black (in Z)

1972-3 8 88.6Z 73.2Z .758 57.5Z

1974-5 9 95.0Z 83.8Z .880 77.2Z

1976-7 15 94.9Z 87.3Z .899 80.7Z

1978-9 9 87.5Z 91.8Z .931 86.7Z

1980-1 43 S8.3Z 86.6Z .904 81.9Z

1982-3 39 88.7Z 83.9g .902 8 t . 4 g

1984-5 7 98.4~ 83 . t~ .923 85.1Z

Tota l 130 90.2Z 85.0g b .895 80.1

bp<,O1 (% white--% black) Most elections fell on even-numbered years; a few special elections in odd-numbered years have been grouped with preceding even-numbered years.

Over time, whites showed a consistently high level of RBV. Black voting behavior began somewhat less polarized than white but immedi- ately increased to nearly the white level. Although based on only eight 1972-73 contests, this trend is consistent with evidence of decreasing fear of white retaliation on the part of black voters, 1970-76, found by Garrow. 1~ In the 1970s, in some counties, fear as a factor inhibiting black political mobilization was decreasing, and black political organization was increasing. 11 Nonetheless, whites usually bloc voted even more than blacks, making it difficult for black candidates to win. Later we shall examine differences by race in registration, turnout, and unspoiled votes recorded for each office (roUon), in addition to RBV. Based solely on the different levels of RBV shown in Table 1, white and black candidates had a 50/50 chance when black voters cast 51.3 percent of the rollon.

Loewen 27

CAN FACTORS OTHER THAN RACE ACCOUNT FOR THIS RBV?

In voting rights litigation, most judges and social scientists have held that consistent RBV is itself the point, not the motivations for it, because they are interested in its implications for electoral success (Brennan opin- ion, Gingles v. Edmisten, 106 S.Ct. at 2772-2779; James W. Loewen, 1985, "Racial Bloc Voting Measures are Dependable," Voting Rights Review 1, 4 (1985): 1-2). Other judges and social scientists, including some witnesses for defendants in voting rights cases, have claimed that race may not be the primary motivating factor, even given enormous correlations like these. They have suggested using multiple regression to examine other variables that might underlie RBV (Higginbotham concur- rence, Jones v. Lubbock, 730 F.2d at 234; Jacobs and O'Rourke, 1986). Such reasoning admits that racial groups voted differently and tries to determine why.

In these South Carolina contests, searching for variables other than race has its pitfalls. Correlation coefficients between race and voting are so high, as shown in Table 1, that race "explains" almost all of the variance in voting, leaving just 20 percent to factors unrelated to race.

Searching for factors other than race presents additional problems. Consider the claim that income, not race, really determines how people vote. Then the relative affluence of white South Carolinians would "explain" their vote. But for income to "explain" correlation between race and voting, the correlations between race and income and between income and voting behavior must be at least as high as between race and voting. As we will see, no variable correlates nearly as highly as race with voting behavior.

Moreover, claiming that income "explains" the correlation between race and voting behavior amounts to asserting that race is associated with income. Since income cannot cause race, the implication is that race "causes" income. Therefore most observers would lay the association with voting behavior at the doorstep of race, not income (Lichtman and Hebert, 1986).

Bearing in mind the problems inherent in multivariate analysis, data from a statewide contest allow us to assess claims that income or other factors can account for much of the observed relationship between race and voting. The major black/white statewide contests during the period were the Democratic primary and runoff in 1978 for Secretary of State. These contests showed considerable RBV. Results for the first primary were almost identical to those of the runoff: r was .86 between % white


TABLE 2 Race, Income, Education, and Percent Urban as Predictors of %

of Votes for the White Candidate for Secretary of State, Democratic Runoff 6/27/78: Zero-Order Regression

F a c t o r b S . E . C o n s t a n t b e t a r A d J . r 2

r a c e . 5 8 . 0 5 15 . 8 5 . 8 6 . 7 3 (% white)

income .39 . I 28 .46 .46 .19 (median family)

education -.71 1.37 62 -.08 -.08 .00 (median)

% urban -.01 .08 56 -.02 -.02 .00

in turnout and votes for the white candidate(s) in each. For the sake of economy, I report only the runoff. Ecological regression showed that among white voters, 77 percent voted for the white candidate; among black voters, 93 percent voted for the black candidate.

Besides race, the socioeconomic factors most commonly suggested to be important in predicting elections are probably income, education, and percent urban. I examined county-level Census data for these variables. Table 2 shows the zero-order correlation and regression coefficients for income, education, and percent urban as predictors of vote outcome. Race was by far the strongest factor, with r =. 86. Education and % urban were not statistically significant.

Multiple regression was used to investigate further whether these other factors could account for part or all of the variance associated with race. To avoid multicollinearity among the independent variables, I examined each in turn, paired with % white in turnout, as predictors of % of the votes won by the white candidate. 12 Table 3 shows the results. Race remained by far the most important factor in determining how counties voted. Each of the three SES factors had a negative and modest impact on RBV when race was also included in the equation. Multiple regression resulted in only a small improvement in adjusted r 2. Thus the data do not support those who would use multiple regression in analyzing RBV. Racial composition of the precinct was the basic predictor of outcome.

Loewen 29

TABLE 3 Income, Education, and Percent as Predictors of % of Votes for White Candidate

when Paired with Race: Multiple Regression

F a c t o r b $.E. Cons tan t b e t a M u l t . r Ad~.r 2

Race .81 .07 1.18 Income - , 3 6 .1 25 - . 4 3 ,90 .80

Race .63 .05 .92 Educa t ion - . 2 7 .62 37 - . 2 9 .90 .80

Race .63 .05 .92 Urban - . 1 4 .04 16 .25 .89 .78

To simplify decimals, constant terms are in percentages and income is in hundreds of dollars.

CAN FACTORS OTHER THAN RACE BE SECONDARY FACTORS?

Once we recognize race as the primary factor, however, we can investigate various secondary factors, for although RBV was high, it was not uniform. Using precinct-level data for the Secretary of State race, I calculated three indicators of political mobilization in each county: the percent of white voting age population (VAP) that turned out at the polls, the percent of black VAP that turned out at the polls, and the percent of overall RBV. (Overall RBV is the proportion of white voters who voted white plus the proportion of black voters who voted black. Thus 200 percent = total RBV and 100 percent = no RBV.)

Table 4 shows the matrix of correlations between these variables and the following political and SES factors: the proportion of the total population that was black (%BPop), the proportion of the black VAP that turned out at the polls (%BTrnVAP), the percent of the overall population that was urban (%Urban), the white (WMed$) and black (BMed$) median family incomes, and the median years of schooling in the white (WEduc) and black (BEduc) adult (over 25) population. 13

Two factors had the greatest influence on white turnout: percent black in the population (%BPop) and whether blacks turned out (%BTrnVAP). Similarly, blacks turned out more in counties that were high in the percentage of blacks in the population and where whites turned out more. The percentage of blacks in the population appears to have been the prior and more basic cause of political mobilization in both groups, spurring


T A B L E 4 Facto~ R e ~ t ~ toPof i f ica lMobi l izaf ion

Dep.Var. ZBPop ZBTrnVAP %Urban WMed$ BMed$

I'I~TrnVAP .662 .666 -.561 -.423 - .187 (% of White VAP that turned out)

%BTrnVAP .614 . . . . .435 -.135 -.411 (% of Black VAP that turned out)

RBV -.155 -.I14 .225 .057 .280 -.091 (1 of White voters voting White + I of Black voters voting Black)

k'Educ BEduc

- .308 -631

- .183 - .398

.17l

blacks to turn out because they might win (owing to their percentage in the population), and spurring whites to turn out so they would retain control (mobilized by the threat of the percentage of blacks in the population). 14

Other relationships were weaker and partly artifactual. For example, blacks in heavily black counties had less education, which helps explain why black education correlated negatively with turnout. Partial correlation was used to examine effects of other SES variables while holding percent black in the population constant. All partial correlation coefficients were smaller; that for black median education became a minuscule - . 057 , for example. Similarly, an inverse relationship held between percent black and black median income. Black families were poorer in heavily black counties. This is a remnant of plantation social structure. Thus the positive correlation between percent black and black political mobilization underlies and explains the otherwise inexplicable negative correlation between income and mobilization in the black community.

None of these SES factors fully explained the variations in mobilization. They also played very little role in explaining different levels of RBV, as shown by the small correlations in the bottom line of Table 4. To uncover more satisfying answers as to why political mobilization and RBV varied, we must look to geography as a secondary factor. Different subregions and different counties have endured distinctive histories. In the process, they have developed distinctive political cultures that are only partly explained by SES variables.

Fine-grained examination of the 1978 major statewide primary runoff for Secretary of State supplied two examples of the power of "geography." Beaufort County lies surrounded by the "Low Country" counties

Loewen 31

of Allendale, Colleton, Hampton, and Jasper, and shares with them com- mon SES characteristics. Yet Beaufort blacks showed high political mobilization. They outdid whites, per capita, in registration, turnout, rollon, and RBV. Nothing of the sort occurred in neighboring counties. "Geog- raphy" here is a surrogate for distinctions in social structure, history, and culture. In November 1861, the United States Navy invaded the county, held it for the rest of the war (with the help of freed slaves), and began a process of transferring land ownership from disloyal white planters (who had fled to the interior) to freed slaves. After the war, the process was not fully reversed. As a result, Beaufort blacks have had a history of land ownership and independent farming (also oystering) for more than a hundred years. As early as 1968, they were registering in greater proportion than Beaufort whites. Conversely, white retirees at Hilton Head and Marine recruits at Parris Island produced fewer votes in Democratic primaries than whites in neighboring counties. 15

Newberry County provided an instructive example of the converse: low black political mobilization in the black community. Bass and DeVries singled out Newberry as a county with a "historic record of an unusually high level of intimidation of blacks," owing partly to a major demagogic leader early in this century. 16 This legacy has persisted to the present to some degree, in contrast to neighboring Fairfield County, and helps explain a 7 percent difference in black political mobilization between the two. 17

To some social scientists, geography cannot be a socially causal variable itself, but indicates mis-specified variables. In South Carolina, geography in part correlated with SES factors that helped to explain why some subregions showed greater political mobilization and RBV than others. In part, geography did not act as a surrogate for SES variables, but reflected historical uniqueness.

OTHER POSSIBLE CORRELATES OF RACIAL BLOC VOTING: LEVEL OF OFFICE, TYPE OF ELECTION, AND INCUMBENCY

Some social scientists have suggested that a different kind of secondary factor can influence the levels of RBV and political mobilization: qual- ifications of candidates, types of offices sought, campaigning styles, and the like. As explanations for RBV, these factors run into the same problem that we have seen afflict SES explanations. If whites are said to vote against blacks owing to newspaper endorsements, for instance, we must ask whether race "explains" endorsements.


TABLE 5 Racial Bloc Voting, 1980-1984 Democratic Primaries and Runoffs,

by Level of Office

Type of Election

County level

Legislature

Congress

N of % of Whites % of Blacks r r 2 Elections Voting White Votin~ Black (in %)

46 91.8% 85.1% a .924 85.4%

24 89.7% 80.5% .848 72.0%

3 78.8% 74.8% .737 54.3%

~p<.05 (% white--%black)

Now that racial composition of precinct has been established as the primary cause of election results, however, three "candidate" factors can be examined as possible secondary factors. I combined all elections to see if level of office (county, state, or national), type of election (primary or general), or incumbency affected RBV.

Type of Office Sought

Commentators have offered various hypotheses as to those offices to which whites will elect blacks. In the Fusion days (c. 1877-1890), white Democrats elected blacks to minor local offices like coroner while re- serving statewide and major local offices for whites. On the other hand, white voters have sometimes felt that fairness demands black represen- tation on multimember boards, such as county commissions. Moreover, electing one black to such a board does not threaten whites with black takeover of the office. This principle might lead whites to support black candidates for Congress or the state legislature, although a given voter has only one congressman or state senator.

Table 5 contrasts RBV for county-level offices, state legislature, and U.S. Congress. 18 Voters of both races showed higher levels of bloc voting in county elections, and lower levels in congressional elections. Although these trends were interesting, perhaps suggesting somewhat greater willingness on both sides to crossover vote for higher offices, they were not statistically significant. Results on all levels showed RBV.

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TABLE 6 Racial Bloc Voting, 1980-1984, Comparing General Elections

to Democratic Primaries

Type of N of Z of Whites Z of Blacks ~ r 2 Election Elections Votin~ White Voting Black (in Z)

Primary 73 90.6g c 82.9Z bd .891 79.4Z

General 16 83.3Z 94.3Z a .965 93.1Z

~p<.05 (%white--% black) bp<.01 (%white--% black) r (% in primaries--% in general elections) dp<.01 (% in primaries--% in general elections)

Type of Election

Since the Voting Rights Act, blacks have been overwhelmingly Dem- ocratic. Thus they may be even less likely to vote for a white (Republi- can) in general elections than for a white candidate in Democratic primaries. White southerners have traditionally been Democratic. Hence they may be more likely to vote for a black Democratic nominee in the general election than for the same candidate competing with whites in the Democratic: primary. Table 6 compares RBV in primaries (including runoffs) and general elections. 19 A black candidate who won the Dem- ocratic primary and then opposed a white Republican could expect about 11 percent more black RBV and about 7 percent additional white crossover voting in the general election. The differences were significant, although results in both types of elections showed extreme RBV.

Incumbency

Table 7 tests whether incumbency affected voting patterns by race. It divides primaries into three groups: elections with a white incumbent, with no incumbent, and with a black incumbent. 2~ The table shows that incumbency made a significant impact on levels of RBV in the black community. Black voters gave great support--97 percent--to black in-


TABLE 7 Racial Bloc Voting, 1980-82 Democratic Primaries, by Race of Incumbent

Race of N of Z of Nhites Z of Blacks ~ncumbene Elections Vots Nhite Voting Black

Black I0 84.6Z a 97.0Z b

None 38

White 22

90.1Z 85.4Z

93.3X 72.1Z

~p<.05 (% voting for white incumbent--% voting for black incumbent) bp<.01 (% voting for black incumbent--% voting for white incumbent)

cumbents. Conversely, 28 percent of black voters crossed over to vote for white incumbents. The white electorate was less affected by incumbency: more than five white voters in six voted against black incumbents. This may be grounds to infer that black voters give more weight to qualifica- tions than do white voters. Results achieved statistical significance within both groups. But neither group gave incumbency nearly as much weight as race itself, the primary factor.

SUMMARY

"As long as white southerners refused to vote for blacks, the concept of a color-blind society remained a legal fiction," noted Stephen Lawson, and minority influence remained restricted. 21 It would be encouraging to report that white RBV has decreased. In South Carolina, white RBV was a bit lower when white challengers faced black incumbents, when the office was part of a multimember board (including legislatures), and in a handful of isolated contests. However, these differences were too small to encourage much belief that white RBV was waning.

Black RBV varied more than white RBV, was more affected by incumbency and other factors, but has been growing and becoming more consistent. 22 To a slight degree, higher black RBV resulted from the existence of more black incumbents. Mostly it is one aspect of the con- tinuing political mobilization of the black population. In metropolitan areas blacks are often now more mobilized than whites. In rural plantation areas, blacks are still less mobilized than whites.

Loewen 35

Thus, over time, RBV has remained high in South Carolina. Because polarization was so consistent, nonracial characteristics (of voters or candidates) proved only modestly useful in explaining when and where RBV was particularly intense, not at all useful in supplanting or "explaining" race as a factor. For this state, at least, the "consistent and persistent racial bloc voting" Thernstrom (1979) says is required to justify persistent application of the Voting Rights Act has been demonstrated. There- fore we must conclude that the Voting Rights Act and decisions relying on it are still essential to ensuring blacks some chance to make their votes count.

NOTES

1. Abigail M. TherrJstrom, Whose Votes Count? Affirmative Action and Minority Vot- ing Rights (Cambridge: Harvard Univ. Press, 1987), p. 243.

2. Paul W. Jacobs and Timothy G. O'Rourke ("Racial Polarization in Vote Dilution Cases under Section 2 of the Voting Rights Act: The Impact of Thornburg v. Gingles," Journal of Law and Politics, 3 (1986): 295-353), claim that RBV was not a critical factor prior to the 1982 amending of the Voting Rights Act. However Jim Pieper ("Results of the Results Test: The Impact of the 1982 Amendments to Section 2 of the Voting Rights Act on Dilution Suits," Journal of Law and Politics, 2 (1985): 341-367), notes that a determination of RBV was "implicit in the earlier dilution cases and . . . explicit in some." Indeed, courts have taken notice of statistical measures of RBV since at least 1971 (James W. Loewen, 1971, "Testimony" in National Democratic Party v. Riddell, Fedl. Dist. Ct. (S. Dist., MS.)). Demonstrating RBV is a crucial step in challenging multimember districts (Frank R. Parker, "The 'Results' Test of Section 2 of the Voting Rights Act: Abandoning the Intent Standard," Virginia Law Review, 69 (1983): 715- 764); majority-vote requirements (Katherine Inglis Butler, "The Majority Vote Require- ment: The Case Against Its Wholesale Elimination," Urban Lawyer, 17 (1985): 441- 455); potentia]Ily gerrymandered single-member districts (James U. Blacksher, "Drawing Single-Member Districts to Comply with the Voting Rights Amendments of 1982," Urban Lawyer, 17 (1985): 347-367; and other election practices.

3. Abigail M. Thernstrom "The Odd Evolution of the Voting Rights Act," The Public Interest, 55 (1979): p. 57.

4. A minor problem affects Democratic primaries and runoffs: turnout in either of these elections is coded only once, so the analyst cannot tell if the person voted in both elections or just one. In practice, this difficulty disappears owing to very high correlations between the racial proportion at the polls in each of the paired elections. There have been no Republican runoffs.

5. Thanks to Election Data Services for data analysis, under my direction, for elections between 1980 and 1983; and to Thomas Keeling and Ellen Weber, Department of Justice, and Dennis Hayes and Adell Adams, NAACP, for assistance in supplying data.

6. This decision rule modestly (<5%) decreased white and increased black RBV. It provides a conservative measure of white RBV.

7. Districts for United States Congress and some for the South Carolina legislature comprised several counties or portions thereof. Each district contest was considered one election.


8. See James W. Loewen, Social Science in the Courtroom (Lexington, MA: D. C. Heath, 1982), pp. 189-190. Some commentators have criticized the use of ecological regression to determine RBV. Thernstrom (1987: 207) says "expert witnesses cannot definitively answer the question of who has voted for whom, much less why." Jacobs and O'Rourke claim "the only way to know with a high degree of certainty how individuals have voted is by asking them"; they go on to recommend exit polling (1986: 320). However, exit polling reveals only how individuals say they have voted. If these critics mean to invoke the ecological fallacy, we note that ecological regression does not commit this fallacy so long as its central assumption holds. Ecological regression assumes min- imal correlated error--here, that the rate of RBV shows little correlation with the independent variable, percent white in the precinct. Several pieces of evidence support this assumption: correlation coefficients were extremely high; curvilinearity was slight; ho- mogeneous precincts analysis confirmed ecological regression results; and analysis at two different levels, county and precinct, yielded similar results.

9. If we define low white RBV as <60 percent of white voters voting for white candidate(s), then 4 of these 130 contests qualify: SC Senate District 7 Seat 1, 1972 Democratic primary (55.9%); Charleston County Council District #2, 1978 general (58.0%); SC House District 111, 1980 Primary (34.7%), and SC House District 102, 1982 General (52.8%). I am working with local experts in South Carolina to understand these four elections.

10. David J. Garrow, "Black Voting in South Carolina," Review of Black Political Economy, 9 (1978): 60--78.

11. Garrow tested in South Carolina Salamon and Van Evera's conclusion from Mis- sissippi that fear of white retaliation deterred black turnout (Lester Salamon and S. Van Evera, "Fear, Apathy, and Discrimination," American Political Science Review, 67 (1973): 1290-1299). His data strongly supported their hypothesis for 1970 but offered much less support in each subsequent year through 1976. This volatility convinced him that their fear model was probably wrong, so he believed that rapid changes in socioeconomic characteristics of the black population could explain his new patterns. However, demographic variables changed more slowly than fear in this period. Owing in part to massive school desegregation in about 1970, fear did decrease markedly in the early 1970s in some counties in Mississippi and South Carolina, facilitating black political organization (Steven F. Lawson, In Pursuit of Power: Southern Blacks and Electoral Politics, 1965-1982 (New York: Columbia University Press, 1985); James W. Loewen, "Afterward: Between Black and White Twenty Years Later," in The Mississippi Chi- nese: Between Black and White (Prospect Heights, IL: Waveland, 1987). Some counties where blacks had been most oppressed but were most numerous now became sites for black political mobilization. Decreased fear and increased black political organization can explain Garrow's data.

12. Some multicollinearity existed between race and income, moderately inflating the correlations between income and votes for white candidate.

13. For some analyses, five counties had to be discarded owing to incomplete data. 14. The modest relationship between political mobilization and percent in population

neither violates the basic assumption of ecological regression nor biases its results, for several reasons. First, the two-equation method avoids making assumptions about turnout. Second, our ecological regression analyses are on the precinct level, while the point here relates to percent black in the county. Estimates of the chance of victory for candidates of each race are likely to be influenced by the racial composition of the county, not precinct. Finally, extremely high correlations underlie our regression analyses, indicating little curvilinearity for any reason, including this one.

Loewen 37

15. George C. Rogers, "South Carolina," in D. Roller and R. Twyman, eds., The Encyclopedia' of Southern History (Baton Rouge: Louisiana State University Press, 1979); Chester W. Bain, "South Carolina: Partisan Prelude," in W. Havard, ed., The Changing Politics of the South (Baton Rouge: Louisiana State University Press, 1972), pp. 588- 636.

16. Jack Bass and Walter DeVries, "South Carolina: The Changing Politics of Color," in The Transformation of Southern Politics (NY: Basic Books, 1976), p. 273.

17. Such subregional variations should finally put to rest the so-called "65% rule," which was an appropriate finding only for the case in which it was first developed, Kirksey et al. v. Hinds County Board of Supervisors, 402 F.Supp. 658 (S.D. Miss. 1975). The proportion minority a district must be in order for the minority to have an equal chance has always been an empirical question. In Beaufort Count3", blacks did not even have to be in a population majority in order to have an even chance.

18. To avoid the possibility that effects from type of election or year might confound the results, analysis was confined to Democratic primaries and runoffs, 1980-84.

19. No important black-white contests occurred in Republican primaries. 20. To avoid possible third variable effects, general elections were excluded. 21. Steven F. Lawson, In Pursuit of Power: Southern Blacks and Electoral Politics,

1965-1982 (NY: Columbia University Press, 1985), p. xi. 22. Paul J. Stekler, "Electing Blacks to Office in the South--Black Candidates, Bloc

Voting, and Racial Unity Twenty Years after the Voting Rights Act," Urban Lawyer, 17 (1985): 473--487 found a similar increase in the Mississippi Delta.

racial bloc voting and political mobilization in south carolina

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