Churches as organizational resources

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1 This is a case study of a single city using pooled, cross-sectional data to describe the period from 1952-58. We do not claim Detroit is representative of all American cities, nor that we can ascertain the national or regional distribution of connections between religious institutions and political outcomes studying a single city. Instead, we attempt to discover the importance of churches and denominational populations for neighborhood-level political outcomes. Examining how the religion-politics connection worked in Detroit in the 1950s involves choosing a case with maximum variance. Detroit supported the Democratic Party and left-wing political candidates when the majority of the state of Michigan and country as a whole voted for the conservative politics of the McCarthy era. Were we to test our hypotheses in a city with less variance in political contention, we would not have the possibility of examining conservative and progressive Catholics and we would lack the intersection of progressive black Protestantism and conservative mainline protestant churches. This study offers the possibility of learning about the range of possibilities in the relationship between church and electoral campaign, a set of relationships that then merit examination in longer time periods and different locations.

2 Lenski (1963:28,33) notes that because the French were the first settlers in Detroit, it was a Catholic community during its early history. But as immigrants arrived in Detroit, it made the city more cosmopolitan and much like Cleveland, Pittsburgh, Buffalo, and Chicago in its economics, politics, ethnicity, and religion.

3 For ease of exposition, we use for term “church” from here on out to refer to both churches and synagogues.

4 For more information on these political party platforms and Michigan Proposal 3, see (XXXX).

5 Putnam (2000) emphasizes the 10% drop in church membership since 1950, and the 5% drop in church attendance over this same time period. The discrepancy between his analysis and that of Wald and Greeley is in the timeframe considered. Although Putnam shows data for earlier years (from 1940), he only mentions in passing that the 1940 rates of church membership were lower than they were in 1999 (when using church records; when using the Gallup Poll, they were about 7 percentage points lower in 1999). Putnam’s data show that church attendance was equivalent in 1940 and 1999.

6 Zald and McCarthy credit Collins (1982) for this idea.

7 We use Lenski’s findings here to help characterize the Detroit religious groups. We do not attempt to measure bonds for our analysis.

8 Recent scholarship on denominations has suggested that differences between denominations have decreased over the last 50 years (Wuthnow 1993). Our time frame, which is at the very beginning of this trend, represents a time when they were more pronounced.

9 This helps to explain the neighborhood battles over black entry into previously ethnic neighborhoods in Northern cities. Catholics stayed and fought off black entry, while Protestants and Jews moved to the suburbs and avoided direct conflict.

10 Relatively conservative in this context meant solidly Democratic Party, as opposed to Democratic with communist sympathies or some third party (left-wing) voting.

11 The ACTU was organized to fight communism in unions. It had a liberal political stance, but was staunchly anti-communist. Dorosh criticized it from the left.

12 This is contrary to what might be expected in light of Greeley’s argument regarding the importance of community among Catholics.

13 We saw earlier that favors bestowed by her husband, Henry Ford, came with strict restrictions.

14 The Catholic priesthood was dominated by Irish priests, who tended more towards the Republicans even more so than the component of the Catholic laity that was middle-class (Lenski 1963:306).

15 This study has two units of analysis: individuals and neighborhoods. While logically churches form a third level, we assess churches as an attribute of census tracts and groups of tracts (something more like neighborhoods).

16 Ordinary least square regression breaks down under conditions on non-constant error variance (heteroskedasticity), is not resistant to outliers and is inefficient, especially in small samples (Dietz et al. 1991). There problems are more severe in aggregate analysis, tract-level data in the current project. Robust regression disregards gross outliers with Cook’s Distance > 1. After an initial OLS model, it employs iteratively reweighted least squares until convergence.

17 This was a difficult and tedious process, involving the utilization of several maps at one time, to locate the census tract of the precinct/church. Although we double checked all data, there are bound to be some mistakes due to boundary issues and unclear map information. These mistakes become less important for the adjacency variable, since it calculates the presence of churches in all surrounding areas. Our process was as follows: we used a 1952 precinct map of Detroit as our base. We placed a plastic cover over the map and drew in the census tracts over them. We then recorded the precincts that fell within each cencus tract. For those that straddled the census boarders, we assigned a corresponding proportion to each tract.

18 We located each church on our map and recorded the census tract that it fell within.

19 This assumes that religious populations were basically stable in the time period under study. Deskins (1972) shows that the main migrations of blacks within Detroit occur during the 1960s.

20 Adjacent pairs of tracts 22 and 23 are merged as are 56 and 58. Tracts 23 and 58 have small populations, 119 and 3 people, respectively, and are missing census data on predictors. These are non-residential areas and merged with adjacent residential areas.

21 The Detroit Area Study was not designed as a spatially representative sample of Detroit neighborhoods. Even when data are pooled from 1953-58, 69 tracts have no data. To treat this missing data problem conservatively and bias against a finding in regression models, we substitute the median value for the missing percentage of denominational population.

22 To check the accuracy of our estimate, we compare the tract-level means for the proportion of blacks estimated from the DAS data and the 1950 census. A two sample t-test for unpaired data with unequal variances indicates that the means (17.47% black population from the 1950 census and 21.34% black from our pooled DAS estimate) are not significantly different. Our estimate falls within a 95% confidence interval around the true value of the count of blacks from the census. Of course, the ethnic composition of Detroit changed between 1950 and 1958 but these tests indicate that our spatial sample is close to the population despite being based on samples that are not spatially representative.

23 Steensland et al. (2000:297), for example, classify nondenominational/no-denomination Protestants that are frequent church goers as evangelical.

24 Since there were only 2 reform congregations and 3 conservative congregations in Detroit during this period, we include only orthodox congregations. This practice most likely works against our hypotheses.

25 Steensland et al.’s catch-all “other affiliation” category has no relevance to our analysis. This is because, in individual models, we compare a given religious group to all others (religious and not) in the population. In an aggregate level model we only enter the religious populations of interest.

26 Three tracts of 367 had more than two dominant groups by this criteria. In those, mainline Protestant was the largest, so the tract were recoded as “mainline dominant.”

27 Unlike other Detroit Area Studies, the 1953 survey drew a sample of women with children (18-years-old or younger) (Monk and Newcomb 1956). Data were collected on the husband’s occupation, ethnicity, work status. Self-reports of voting in the 1952 election were collected for both husband and wife; 12 percent of women reported that their husband’s political preference differed from their own. Because most households have the husband as employed breadwinner, his occupational information is used to control for social class and the models use husband’s vote. However, it makes no substantive difference to the analysis which spouse is used to code the dependent variable. (For discussion of class effects in these data see XXXX 2003.)

28 Studies of religion confirm that how often someone goes to church and how fervently beliefs are held matter to socio-religious outcomes. While there is crude data on church attendance in the Detroit Area Studies, we focus on a more basic test: does the presence of a church matter controlling for the denominational population of a neighborhood. Neither the spatial nature of religious institutions nor the geographic distribution of “religiosity” have been empirically examined in the literature. We are much more certain about the existence of churches and synagogues than of the spatial distribution of some latent and abstract “religiosity” measure.

29 It might be asserted that the causal direction of the church-politics relationship is the opposite. This would mean that people of a specific political and religious persuasion moved to be near such a church and, thus, the shift in population not the institution are responsible for the effect we observe. The recent literature on migration and on church-communities ties discounts this argument. Both scholars of religion and church leaders themselves have noted the tendency for people to live increasingly far away from their churches. The Polis Center Project on Religion and Urban Culture even terms these congregants “religious commuters” a trend it has found ongoing since the 1930s (Diamond 1999). Moreover, studies find that religious institutions interact with other neighborhood features to reduce residential mobility rates (Irwin, Tolbert and Lyson MS; Meyers 2000). Rather than attracting people to neighborhoods, churches create reasons for them to stay or, failing that, follow their congregation to a new community. A possible exception is with Latin American immigrants in the late 20^th century when churches played an important role acclimating people to their new communities (Hagan and Rose 2003). But our study is of a time period when the major waves of immigration were from the southern United States and Europe.

30 None of our measures of religious concentrations were significantly related to neighborhood voting patterns, so they are not presented here. This finding differs from those of previous studies, but as will become apparent later, religious concentrations are significant in our aggregate models.

31 All models control for the voting age population. Vote models commonly analyze the proportion of votes for a particular candidate. While intuitive and straightforward to interpret, this practice induces two problems. First, it makes a bounded dependent variable, for which standard models typically predict out-of-range-values. Second, and more seriously, this induces heteroskedasticity because the variance of the mean is inversely proportional to the sample size within the geographic unit. Rather than build that error into the dependent variable, it is better to control for the number of eligible voters in the tract. Results are thus read as the number of votes that a particular variable contributes to the outcome, net of the number of voters.

32 Of course, the population of black Protestants and the black population are highly correlated in space (r=0.76). In our aggregate data the concepts of race and black Protestant religion cannot be further disentangled. The effect of the church, however, remains significant no matter which variable is entered.

33 As with black Protestants, Jewish, Catholic and white Protestant groups overlap with specific immigrant populations. Members of new immigrant groups, those from Poland, Czechoslovakia, the USSR, Lithuania, Romania and Italy, are highly correlated with the Jewish population, while members of old immigrant groups, those from Germany and the British Isles, are highly correlated with mainline Protestants. Catholics are positively correlated with both groups. As the effect of churches holds regardless of controls, we see religion as a salient community composed of ethnic, racial, and linguistic factors spatially clustered in neighborhoods and around churches.

34 Progressive Party candidate Vincent Hallinen had been imprisoned for most of his campaign for contempt of court in his defense of popular Longshoremen’s union leader Harry Bridges at his deportation hearings.

35 The hierarchical logistic models of self-reported voting failed to find a role for concentrations of religious members.

36 We say “general” theology here because Protestants are divided into 3 basic camps: black, mainline, and evangelical. The black Protestant church has a religious meaning system and social organization that is similar to that of evangelical Protestants. But it emphasizes components of the theology that are particularly relevant to the black experience (Steensland et al. 2000).