Ideological Boundaries of Status Advantages: Legislative Effectiveness in the United States House of Representatives

Abstract

Prior research assumes that high-status actors have greater organizational influence than lower-status ones, that is, it is easier for the former to get their ideas and initiatives adopted by the organization than it is for the latter. Drawing from the literature on ideology, we posit that the status–influence link is contingent on actors’ ideological position. Specifically, status confers organizational influence to the degree that the focal actor is ideologically mainstream. The more an actor’s ideology deviates from the mainstream the less will her status translate into increased organizational influence. We find support for this hypothesis using data on the work of legislators in the House of Representatives in the United States Congress. By illuminating how and under what conditions status leads to increased influence, this study qualifies and extends current understandings of the role of status in organizations.

Keywords

Congress ideology influence social capital status

Introduction

A widely established tenet among organizational scholars is that high-status actors are more influential than lower-status ones. A stream of experimental and observational research finds that, in task-oriented groups, the ideas of high-status members carry greater weight in determining the solutions a group adopts and the directions it takes (Berger, Rosenholtz, & Zelditch, 1980; De Kwaadsteniet & Van Dijk, 2010; Eckel & Wilson, 2007). Similarly, at a more macroscopic level, research shows that high-status actors have more influence in shaping the ideas and practices that gain support and become adopted, both within and across organizations (Coleman, Katz, & Menzel, 1966; Nerkar & Paruchuri, 2005; Podolny & Stuart, 1995; Rogers, 2010; Simmel, [1904] 1957; Van den Bulte & Joshi, 2007). The status–influence link is taken to be so straightforward that it is often considered to be a defining feature of status (Anderson, John, Keltner, & Kring, 2001; Berger, Fisek, Norman, & Zelditch, 1977; Ridgeway & Walker, 1995; Ridgeway & Correll, 2006).

Some researchers, however, criticize this approach and suggest that status should be distinguished from its consequences (Bunderson, Van der Vegt, Cantimur, & Rink, 2016; Fiske & Berdahl, 2007; Magee & Frasier, 2014; Magee & Galinsky, 2008; see Blader & Chen, 2014 for a review). These authors point out several examples illustrating how status might not always be associated with organizational influence, defined as the ability to get one’s ideas and initiatives adopted by the organization. Magee and Frasier (2014), for instance, highlight that although ambassadors to foreign countries and members of advisory boards often hold high status, such status confers limited actual influence. Fiske and Berdahl (2007, p. 682) argue that lame-duck administrators often enjoy high status but have little influence over organizational outcomes.¹ Furthermore, several small group studies suggest that the link between status and influence might be more tenuous than is generally assumed. For example, evidence suggests that status confers limited influence when there are different viewpoints about a task (Hong, Zhang, Gang, & Choi, 2019). The overall implication from these studies is that to improve our understanding of the role of status in organizations, it is important to decouple status from its consequences and examine the conditions under which status confers organizational influence.

In this study, we propose ideology as a key moderating factor determining whether status translates into influence. Ideology is defined as a set of relatively coherent and stable beliefs associated with ostensible preferences about a social domain (Allport, Clark, & Pettigrew, 1954; Converse, [1964] 2006; Gerring, 1997, p. 980; Knight, 2006). The construct of ideology is often associated with politics, which is the setting in which we test our theory. However, a number of studies show that ideology is also relevant to organizations more generally (Barley & Kunda, 1992; Bunderson, 2001; Fiss & Zajac, 2004; Guillén, 1994; Kunda & Ailon, 2006; Mees-Buss & Welch, 2019; Meyer, 1986; Simons & Ingram, 1997; Weiss & Miller, 1987). This is especially the case for matters related to wider social issues such as sustainability or welfare (Guillén, 1994; Hafenbrädl & Waeger, 2017; Mees-Buss & Welch, 2019), since managers tend to adhere to ideologies which they believe will bring benefits to their organizations and society at large. In his study of managerial ideologies, for example, Guillén cites the CEO of IBM, a public proponent of the managerial ideology of human relations, claiming that ‘without our attitude towards human relations we would have fallen short of our business goals’ (Guillén, 1994, pp. 77–78).

Prior studies concur that ideologies within organizations are not monolithic and that organizations’ members often adhere to different, sometimes opposing, ideologies. For example, Mees-Buss and Welch (2019) analyse the dynamics of an ideological conflict at Unilever, where managers were divided between normative and rational ideologies in the redefinition of Dove as a socially responsible brand. While largely ignored in previous research on the status–influence link, such differences in ideology shape how actors evaluate each other’s ideas and actions and how they relate to one another (Denzau & North, 1994; Weiss & Miller, 1987). Accordingly, we propose that considering actors’ position in an ideological space might enable us to evaluate the conditions under which status confers organizational influence. Our main contention is that status confers organizational influence to the degree that the focal actor is recognized to be ideologically mainstream. By contrast, the more an actor’s ideology deviates from the mainstream the less her status will translate into increased influence.

We test our argument using data on the work of legislators in the House of Representatives in the US Congress, an organization in which the subject matter of ideology is government. While our proposition is relevant for organizations in general, focusing on the US House of Representatives offers an ideal vantagepoint to test this proposition. Decision-making processes in this organization, as in many other contemporary organizations, comprise multiple decision-making points that involve deliberations, and where securing others’ attention, approval, and endorsement are important to have influence (Chown & Liu, 2015). An advantage of our setting is that it provides a high level of detail about which initiatives progress through these decision-making points, and enables us to measure the status and ideological positioning of each legislator. We examine 873 legislators’ status, ideology, and influence in the legislative process over eight consecutive congresses. We find that the effect of status is entirely contingent on ideology: it enhances an actor’s influence if her ideological position fits squarely within current mainstream ideology, but not if it deviates from it.

Theory

Prior research shows that status confers several advantages (Piazza & Castellucci, 2014). In particular, a widely held argument is that status confers organizational influence, that is, the ability to get particular ideas or initiatives adopted by the organization (Coleman et al., 1966; Nerkar & Paruchuri, 2005; Rogers, 2010). The literature advances three main mechanisms to support this claim. First, status elicits greater attention, a prerequisite to have influence (Simcoe & Waguespack, 2011). Second, status is associated with higher quality evaluations (Azoulay, Stuart, & Wang, 2013; Clark, Clark, & Polborn, 2006; Merton, [1948] 1968; Ridgeway, 1981; Simcoe & Waguespack, 2011). Third, status helps actors build stronger coalitions around their ideas and initiatives (Simpson, Willer, & Ridgeway, 2012, p. 150; Watkins & Rosegrant, 1996, p. 60). For these reasons, the likelihood that an idea or initiative will be adopted by the organization is higher if its proponent has high status (Coleman et al., 1966; Nerkar & Paruchuri, 2005; Rogers, 2010).

We expect these advantages to also be relevant for the work of legislators within the US House of Representatives – the empirical focus of the present study. To explain why, we begin by providing a description of the legislative process and then articulate how status may provide organizational influence in that context.

Legislative process in the House of Representatives

The legislative process in the House of Representatives is highly formalized. Each bill is introduced by a single legislator, who acts as the bill’s sponsor. Other legislators can endorse the legislative initiative of the sponsor by co-sponsoring it, i.e. by affixing their signature to the bill. Once a bill is introduced, the speaker of the House directs it to a committee, which in turn works with subcommittees. Committees are not compelled to consider a bill and may reject them (Smith, Roberts, & Vander Wielen, 2013). If the committee approves the bill, it is then scheduled for discussion and put to a vote (Smith et al., 2013).²

In order to increase the likelihood of success of their legislative initiatives, sponsors seek co-sponsors, because co-sponsorships signal the potential benefits of a bill to key agenda setters (e.g. committee members, speaker of the House, majority party leader). Agenda setters pay attention to co-sponsors (Kessler & Krehbiel, 1996; Koger, 2003, p. 227; Krutz, 2005; Schiller, 1995) when evaluating whether a bill should be moved forward. Consequently, legislators who sponsor bills search for co-sponsors to signal to agenda setters that their bill is likely to be a success: ‘a lot of times congressmen cosponsor because they have been asked by a member who wants to get support to get committee action’ (Koger, 2003, p. 231). Such acts of support are not necessarily reciprocated and reflect a status hierarchy among legislators (Gould, 2002; Jourdan, Durand, & Thornton, 2017; Rushing, 1962, p. 146). For example, Harward and Moffett (2010, p. 127) explain that legislators who have the most prestige and influence ‘might be unwilling to compromise that influence by overextending the utility of their endorsement’ and are therefore more selective in granting their support.

Status advantage in the legislative process

Building on the three mechanisms elaborated above (i.e. greater attention, superior quality evaluations and more-effective coalition building), we expect that a legislator’s high status within the House of Representatives will help her secure favourable outcomes for her bills throughout the legislative process. First, a large number of bills are under consideration at a given point in time. Most legislators, including committee members to whom the bill has been directed, are likely to allocate their attention (e.g. study the bill, gather background information, consult constituencies) to no more than a tiny minority of these bills. Extant theory suggests that bills sponsored by high-status legislators are more likely to attract the attention of colleagues (see Simcoe & Waguespack, 2011, for evidence in another setting). Conversely, bills that carry the name of low-status legislators are more likely to pass unnoticed. Second, the evaluation of a bill is likely to be positively affected by the status of its sponsor (Azoulay et al., 2013; Merton, [1948] 1968; Simcoe & Waguespack, 2011). As a consequence, holding everything else constant, legislators are more likely to cosponsor, support in committees and then vote in favour of bills sponsored by high-status legislators than by low-status ones. Third, lower-status legislators have an incentive to support the bills of high-status peers, in the expectation that they will be repaid for their help at some point in the future (Blau, 1964; Goode, 1978; Homans, 1961). Hence, high-status legislators are in a privileged position to negotiate support (e.g. Castellucci & Ertug, 2010) and forge coalitions around their bills.

These arguments suggest that status should enhance influence over the advancement of new legislation in the House of Representatives. Accordingly, we offer the following baseline expectation:

Baseline expectation: Status enhances legislators’ influence as indicated by their ability to advance legislative proposals.

The ideological boundaries of status advantage

Bothner, Kim and Smith (2012) point out that the advantages accruing to high-status actors are vulnerable because they are not owned by the status holder. Rather, they accrue to the status holder because, and insofar as, others bestow them on the status holder. This observation is important for our key hypothesis, suggesting that status translates into increased organizational influence to the degree that the ideology espoused by the status holder is in line with the current mainstream ideology of the organization.

As we summarized in our overview, status enhances an actor’s organizational influence via three mechanisms: it increases attention, it elicits higher evaluations and it helps build coalitions around one’s initiatives. We propose that these mechanisms operate in full force when the status holder’s ideology falls squarely within the mainstream ideology of her organization, but they become weaker as the status holder’s ideology deviates from the mainstream. First, we argue that legislators are more likely to pay attention to bills sponsored by high-status actors. However, the strength of this effect is likely to be weaker for actors who are not ideologically mainstream, because people tend to have negative preconceptions about those who are ideologically distant from them. Hence, even though high-status legislators holding non-mainstream ideologies are likely to elicit a great deal of attention among the restricted circle of legislators who are ideologically close to them, this will not be the case among the majority of legislators.

Second, the literature suggests that status enhances organizational influence by eliciting higher evaluations of quality. Here, too, we suggest that the strength of this mechanism will decline as the status holder’s ideology deviates from mainstream. The reason is that evaluations of quality are rarely purely objective; rather, they are embedded in a set of underlying beliefs and values (Sauder, Lynn, & Podolny, 2012, pp. 275–276). By informing the values and beliefs an actor holds, an actor’s ideology may shape the evaluative process in two ways. First, it may influence the objectives an actor aims to achieve when preparing, elaborating and communicating her initiatives. Second, it may affect the value criteria she uses in evaluating the initiatives of others. The result is that status provides an unambiguous signal of quality among actors who espouse a mainstream ideology. However, the further away an actor’s ideology is from mainstream, the more likely her definition of quality will differ from that of other legislators and, therefore, the weaker will be the signalling mechanism associated with high status.

Third, whereas the literature posits that status confers influence by enhancing an actor’s ability to forge coalitions around their initiatives, ideologically non-mainstream legislators may not be able to enjoy such benefits to the same degree. Legislators who are ideologically far from the mainstream hold beliefs and values that diverge from those of most other legislators, sometimes on principles, which makes it more difficult to identify acceptable compromises during negotiations (Converse, [1964] 2006, pp. 5–6). Furthermore, ideologically non-mainstream legislators are likely to confront greater difficulties in forging coalitions around their bills because legislators are keenly aware of the symbolic and practical costs they might incur by associating with legislators espousing non-mainstream ideologies. Thus, when determining whether to support a proposal, legislators may think twice before providing support to a bill submitted by a sponsor who is non-mainstream. The above arguments lead to our central hypothesis:

Hypothesis: The positive relationship between a legislator’s status and influence (as indicated by her ability to advance legislative proposals) holds for mainstream legislators but erodes as the ideology of the legislator departs from the mainstream.

Data and Methods

Our analysis is based on a dataset of legislative work in the US House of Representatives (hereafter the House). There are 435 representatives in the House, who are elected every two years. Each two-year period is called a Congress (e.g. 1997–1999 for the 105th Congress and 1999–2001 for the 106th Congress and so on). Our data ranges from the 105th Congress to the 112th Congress; 873 representatives worked in the House during this period. The data we use in our analyses result from a combination of the Volden and Wiseman (2014) data on representatives and their legislative effectiveness in congress between 1973 and 2014 and information on individual bills from the @theunitedstates project, which is a dataset compiled by the Sunlight Foundation, Govtrack, New York Times and the Electronic Frontier Foundation.

Dependent variables

Legislative effectiveness

To measure legislators’ ability to advance legislative proposals, we adopt an index that has been developed in political science, which is the legislative effectiveness score (LES) (Volden & Wiseman, 2014, 2016; Volden, Wiseman, & Wittmer, 2013). The LES is a composite index that measures legislators’ influence – their ability to get their legislative initiatives adopted by the House – in a granular fashion across the whole legislative process. Specifically, for each legislator, the composite index includes how many bills (i) she introduces, (ii) receive action in committee (AIC), (iii) pass committee and receive action on the floor of the House (ABC), (iv) pass the House (PASS), and ultimately (v) become law (LAW) and gives greater weight to the advanced stages of the legislative process. The LES is robust to different weighting schemes (Volden & Wiseman, 2014, pp. 56–68) and provides a more accurate measure of legislators’ ability to advance legislative proposals than alternative measures, such as those that take into account enacted laws only (Volden & Wiseman, 2014, pp. 54–56). As consistent with the work of Volden and Wiseman the scores are calculated for each congress.

Independent variable

Status

As explained above, co-sponsorship is a public (it is visible to others) and asymmetric (actor A co-sponsoring B does not necessarily imply that actor B will in turn co-sponsor actor A’s initiative) act of support that serves to build and maintain relationships between legislators. As such, co-sponsorsing is an act of deference that can signal the status hierarchy between legislators (Gould, 2002; Harward & Moffett, 2010; Jourdan et al., 2017). In such a network defined by acts of co-sponsorship, status can be operationalized recursively, such that actors have high status to the extent that they receive deference from other actors, who also receive deference from other high-status actors (Bonacich, 1972, 1987; Podolny, 2005). For each congress, we construct a non symmetric square matrix X in which each cell $x_{i j}$ records the number of times legislator i has had her bills co-sponsored by j during this congress. The possible asymmetry (legislators supporting one another’s bills to different degrees) is an important part of capturing differences (asymmetry) in patterns of deference. We then use this matrix to compute a measure of the status of each legislator using Bonacich’s network centrality measure (Bonacich, 1987). The Bonacich’s network centrality measure of centrality can be defined as follows:

S_{i t} (α, β) = \sum_{j} (α + β S_{j t}) x_{i j t}

(1)

where $S_{i t}$ is the status of actor i for congress t, j is the index of i’s contacts, α is a scaling constant and β is a parameter that determines the extent to which the status of an individual is affected by the status of her peers. The value of β ranges between 0 and the inverse of the norm of the maximum eigenvalue of X. We set β to 75 percent of the reciprocal of the largest eigenvalue.³

The status of a legislator may change from congress to congress. Accordingly, we recalculate it for each congress using all the data on co-sponsorship for that congress. It is an advantage of this setting that there are longitudinal data to enable the recalculation of a legislator’s status for each congress. An attribute of status that has been noted is that it is relatively stable and slow to change. Some studies have assumed status to be absolutely ‘stable’ (time-invariant) by using indicators that are either measured only at one point in time or that, by definition, cannot change. If we compare our measure to those used in studies that have measured status over time, our measure displays similar levels of stability. The autocorrelation of status (i.e. the correlation between the status of a legislator in a given congress and her status in the previous congress) in our setting is 0.67, which compares well with those reported in prior studies (e.g. 0.52 in Podolny and Phillips (1996), 0.41 in Washington and Zajac (2005) and 0.52 in Castellucci and Ertug (2010)).

The status score we calculate for each congress is lagged, so that when we predict legislative effectiveness of a legislator in a given congress, we use her status score from the previous congress.

It is important to note that an actor’s ideological position and status do not necessarily covary. Prior research shows that rising high-status actors can be outside the mainstream (Bourdieu & Desault, 1975; Cattani, Ferriani, & Allison, 2014). In our setting, there are a number of high-status legislators who are positioned far from the ideological mainstream. Well-known examples during the time period covered by our study are Ron Paul (Republican) and George Miller (Democrat), who, despite holding far from mainstream positions in the ideological space, had high status.⁴ Beyond such examples, in terms of the overall relationship, the correlation in our estimation sample between status and ideological distance from the median ideology is rather low (r = 0.06).

Moderating variable

Ideological distance from the median

Following the political science literature, we measure legislators’ ideology using a spatial model of parliamentary voting. This model assumes that legislators have preference functions centred around ideal points that identify their preferred outcomes regarding the issues being voted on, and that these ideal points can be derived from legislators’ positioning on basic ideological dimensions (Poole, 2005; Poole & Rosenthal, 2009). Poole and Rosenthal have shown that a two-dimensional ideological space is adequate to explain the voting behaviour of legislators during the entire existence of the US congress with a sufficient level of accuracy. Furthermore, and more pertinent to the time period we study (i.e. contemporary US politics), Poole and Rosenthal note that voting behaviour can be explained using a single dimension, this dimension being the liberal–conservative axis (Poole & Rosenthal, 2009). The ‘liberal’ and ‘conservatives’ labels map onto a series of positions on different subjects, such as for example taxation and regulation, which are tied to each other.⁵ If there are p legislators, one liberal–conservative dimension in the ideological space and n issues on which legislators take position, the spatial model can be explained by the relationship (Poole, 2005, 2007):

xw = Y

where x is a column vector with p components corresponding to each legislator. Each component of x indicates the positioning of the legislator on the liberal–conservative continuum. w is a row vector with n components that maps the position of the legislator on the liberal–conservative continuum onto their ideal points for each position. In other words, w maps legislators on the liberal–conservative continuum (i.e. vector x) onto a matrix Y in which each cell indicates the extent to which a specific legislator is likely to support a specific bill. For example, a cell in Y might indicate whether a legislator is likely to support the inspection mandate of the Occupational Health Safety Administration as a function of her positioning on the liberal–conservative continuum (Poole & Rosenthal, 2007). Legislators who are at the conservative end of the liberal–conservative continuum are predicted to favour no inspection mandate. Legislators who are at the centre of the spectrum will favour inspection for firms above a certain size and liberal legislators will support inspection for almost all firms.

We use the first dimension of the DW-NOMINATE (dynamic weighted nominal three-step estimation) scores of each politician in each congress (i.e. their position on the liberal–conservative continuum in each congress). A legislator’s first dimension in the DW-NOMINATE score in a given congress is derived from their entire rollcall voting history, which makes it feasible to compare ideological scores across congresses. The score ranges within the [-1, 1] interval. A score close to 1 indicates that the legislator is very conservative and a score close to -1 that the legislator is very liberal. This score can be mapped on the set of ideology positions corresponding to the liberal and conservative dimensions. For example, Henry Waxman is a Democrat who represented the 29th district in California in the 107th Congress. Waxman’s DW-NOMINATE score on the first dimension in this congress was -0.521, which locates him in the 11th percentile of the most liberal members of congress. Waxman is known for his positions on universal health insurance, Medicaid, favouring air and quality standards (source: politico.com). By contrast, Waxman voted against a bill that proposed to eliminate the estate tax (see Govtrack, HR-8 Death Tax Elimination of 2001 vote #84) and against House Resolution 1836 (107th Congress): Economic Growth and Tax Relief Reconciliation Act of 2001, also known as the ‘Bush Tax cuts’, in 2001. On the conservative side, Jack Kingston is a Republican representative of the first district of Georgia in the 107th Congress. He had a DW-NOMINATE score of 0.586, which puts him in the 86th most conservative percentile in the House. In contrast with Waxman, Kingston voted for the elimination of the estate tax and for the Bush tax cuts. Further, in the 111th Congress Kingston opposed the affordable care act (i.e. ‘Obamacare’).

The ideological position of legislators is stable over time (Poole, 2005, pp. 137–139). Whereas particular policy preferences of legislators may change, legislators’ ideological position relative to their peers rarely changes. For example, even though the September 11 attacks modified the policy preferences of legislators in general with regard to privacy and national security, the (relative) positioning of these legislators onto the basic liberal–conservative dimension remained virtually unchanged (Poole, 2007, p. 448). The observed changes in the average ideological positioning of the chamber occur in large part due to the turnover of legislators, because of election outcomes, retirement and other types of exits. Likewise, when the majority party changes, the ideological positioning of the House naturally moves towards the ideology of the majority party. However, the positions of legislators (relative to others who are in the House in that congress) on the ideological scale remains stable (Poole, 2007). Consequently, it is reasonable to assume that legislators’ ideology does not vary endogenously with their status or influence. This assumption is borne out by analyses in previous studies.⁶ In our own estimation sample, the correlation between a politician’s score in a given congress and in the previous one is 0.99.

We measure the degree to which the ideology of a legislator is far from the mainstream by calculating the ideological distance of this legislator from the median ideological score in the House of Representatives. We use ideological distance from the median in the entire House to test our hypothesis. As we detail later, we also ran the same estimations using ideological distance from the median ideology of majority party as a robustness check. The two measures are highly correlated (r = 0.91) and the results remain substantively unchanged.

Control variables

Building on the work of Volden and Wiseman, we include a set of control variables that have been found to influence a legislator’s ability to advance legislation (Volden & Wiseman, 2014; Volden et al., 2013). Seniority is the number of terms a legislator has served in the House. A dummy variable indicates whether the legislator is in the majority party. Other dummy variables are included as indicators of whether a legislator occupies a formal position from which she could influence the progress of a bill or positions whose holder traditionally does not introduce legislation: (a) majority party leader (majority leader), (b) minority party leader (minority leader), (c) speaker of the House (speaker), (d) committee chair and (e) power committee member (member of Appropriations, Rules or Ways and Means Committees) (Deering & Smith, 1997; Volden & Wiseman, 2014). The size of the congressional delegation from the state of the legislator is included to take into account potential coalitions among representatives from the same state (size of congressional delegation). A vote share (vote share) variable is included to take into account that members in safe seats may not be under pressure to promote legislations and that members who are in risky positions may be focusing on activities other than legislation such as raising campaign funds (Volden & Wiseman, 2014).

We also control for the size and density of the co-sponsorship network of each legislator. We consider two legislators to be connected, i.e. a tie to exist between them, if either of these legislators co-sponsored at least one bill of the other legislator within a given congress (Fowler, 2006). Using this definition for each focal legislator (ego), we identify others who have ties with her (alter), which end up constituting this focal legislator’s network. We control for the network size (logged) of each legislator, which is the total number of distinct legislators who either co-sponsor bills sponsored by ego, or whose sponsored bills are co-sponsored by ego. We use this same definition of a tie in assessing whether a given pair of ego’s direct contacts, i.e. those legislators who are in ego’s network, are also connected to each other. We control for network density, which captures the degree to which the contacts of a focal individual are connected to each other. Specifically, a focal legislator’s network density is the proportion of the ties that exist between each pair of direct contacts of this legislator to the total possible number of ties between those pairs. As with legislative effectiveness and status, these network measures are recalculated based on the sponsoring and co-sponsoring activity in each congress. Likewise, these two measures are also lagged. Network size and network density show moderate to strong correlations with status, as might be expected. Removing either one or both of these variables from our models leaves the statistical support for our hypothesis unchanged (when checked in models 4 and 5 in Table 2, the main effect of status has a positive coefficient and our hypothesized interaction has a negative coefficient, p < 0.05 for both, after removing either or both of the network measures).

Research in political science suggests that bill valence (i.e. quality of the bill, in terms of chances of making it through the process) facilitates legislative effectiveness (Hirsch & Shotts, 2012; Hitt, Volden, & Wiseman, 2017). Therefore, legislators might aim to increase the valence (i.e. quality) of their bills, making them more attractive to other legislators and more likely to pass the House, independent of their ideology. Therefore, we construct a proxy, bill valence, to account for the quality of the bills. Each bill has a list of keywords (e.g. higher education, manufacturing, oil and gas), which can be collected from Govtrack. These keywords provide one way to characterize the content of the bill. The success of a legislator in getting bills passed might be because others defer to the sponsor and endorse her initiatives, or it might be that the content of the bill is such that it is more likely to pass the House. We control for the success probability of a given bill by adopting an approach similar to that of Kovács and Sharkey (2014, p. 14), who calculate a book reader’s predicted rating for a book based on the focal book’s genres and the reviewer’s previous evaluations of other books in those genres. This approach is known as collaborative filtering, which is used in computer science and marketing (e.g. Fleder & Hosanagar, 2009). We calculate this variable starting from Congress 106, using the first congress in our sample (105) as our ‘burning’ period. We proxy the probability of success for bills in a given congress on the basis of the success of their keywords in the previous congress(es). To provide an example,⁷ assume that Congress 105 has three bills, all with three keywords: bill 1 (keywords: drug, FDA, addiction), bill 2 (keywords: weapon, army, Iraq) and bill 3 (keywords: weapon, army, Iran). Bill 1 passed the House (success = 1), bill 2 did not pass the House (success = 0) and bill 3 passed the House (success = 1). Now, if bill 1 in Congress 106 has four keywords (drug, army, weapon, war), we first calculate the success probability of each keyword as follows: success probability of drug = 1; success probability of army = (1+0)/2 = 0.5; success probability of weapon = (1+0)/2 = 0.5; success probability of war = (.) [missing value, not used in the calculation], because it did not appear before. Then we take the average success probability of all keywords (drug, army, weapon) as the success probability of the focal bill, which is (1+0.5+0.5)/3 = 0.667. Second, we take the average success probability of all bills sponsored by the focal legislator in the focal congress to arrive at our measure of bill valence for this legislator.

Finally, we also include indicator variables for each congress, congress dummies, to take into account characteristics of a given congress that might intervene in the relationship between status, ideological distance from the median and legislative effectiveness.

Estimation

We use ordinary least squares (OLS) regressions with legislator fixed-effects to estimate our models. We used legislator fixed-effects estimations based on the results of a Hausman test (p < 0.001). Because of this fixed-effects estimation, variables such as gender or ethnic origin are not included in the model, since their effects do not vary within individuals in our observation period. The support we report for our prediction remains statistically significant (p < 0.001) if we choose to not use fixed effects and perform a random effects estimation, in this case also adding indicators for the gender and ethnic origin of the legislator in our models. We use robust standard errors, clustered on each legislator, to take into account the possible non-independence of observations across congresses for the same legislator.

Results

Table 1 presents the descriptive statistics and correlations. The correlation between ideological distance from the median and status is very weak (r = 0.06). The correlation between status and legislative effectiveness is positive (r = 0.24), which is consistent with the baseline expectation. The correlation between network size and network density is negative (r = -0.69), as consistent with prior research. Status and network size are strongly positively correlated (r = 0.67), which might give some readers concern. As we noted in our discussion of the variables, the removal of network size does not reduce the statistical support for our prediction.

Table 1.

Descriptive statistics and correlations.

		Mean	S.D.	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
1	Legislative effectiveness	1.05	1.60
2	Number of bills that passed House	0.67	0.67	0.76
3	Status	0.70	0.75	0.24	0.20
4	Ideological distance from the median	0.47	0.29	–0.30	–0.36	0.06
5	Bill valence	0.19	0.06	0.12	0.20	–0.08	–0.07
6	Seniority	6.40	4.03	0.29	0.16	0.29	0.05	–0.01
7	Majority party	0.52	0.50	0.37	0.42	0.02	–0.80	–0.02	–0.03
8	Majority leader	0.03	0.16	0.06	0.10	0.04	–0.10	–0.02	0.02	0.16
9	Minority leader	0.03	0.16	–0.08	–0.07	0.01	0.17	0.01	0.03	–0.17	–0.03
10	Speaker	0	0.05	0.00	0.01	–0.02	–0.03	0.06	0.04	0.05	0.24	–0.01
11	Committee chair	0.06	0.23	0.57	0.40	0.09	–0.19	0.06	0.29	0.23	–0.01	–0.04	–0.01
12	Subcommittee chair	0.23	0.42	0.20	0.28	0.05	–0.44	0.04	0.11	0.52	0.00	–0.09	–0.03	–0.07
13	Power committee member	0.30	0.46	–0.05	–0.08	0.05	–0.09	–0.04	0.14	0.09	0.06	0.04	–0.03	–0.04	–0.06
14	Size of congressional delegation	19.65	15.48	0.02	0.05	0.14	0.11	0.03	0.09	–0.05	0.02	0.01	0.03	0.06	0.01	0.01
15	Vote share	69.91	13.02	0.05	0.03	0.03	–0.03	0.05	0.09	0.10	0.08	0.00	0.01	0.06	0.07	0.08	0.07
16	Network size	5.27	0.41	0.13	0.13	0.67	0.05	–0.15	0.13	–0.03	0.00	0.02	–0.08	0.03	0.01	–0.05	0.08	–0.01
17	Network density	0.65	0.08	–0.23	–0.23	–0.53	0.14	0.00	–0.10	–0.16	–0.02	0.02	0.02	–0.11	–0.10	0.00	–0.03	0.09	–0.64

N = 2,620. Correlations stronger than |0.04| are significant at p < 0.05.

The results of our regressions are presented in Table 2. Model 1 includes all the control variables. As expected, bill valence is positive and significant. Majority party member, majority leader and committee chair all have a positive and significant effect on legislative effectiveness, which is consistent with the fact that legislators in a powerful party or powerful positions have more influence and are therefore more effective in advancing legislative proposals. Consistent with prior research we also find that power committee has a negative effect on legislative effectiveness. Members of ‘power’ committees devote most of their time to the work of the committee rather than to their own legislative initiative, and high priority legislation is typically introduced by the chair in these committees (Volden et al, 2013, p. 11).

Table 2.

Legislator fixed-effects OLS models predicting legislative effectiveness.

	(1)	(2)	(3)	(4)	(5)
Bill valence	2.279^***	2.274^***	2.267^***	2.260^***	2.311^***
Bill valence	(0.472)	(0.472)	(0.465)	(0.465)	(0.467)
Seniority	0.069	0.064	0.062	0.056	0.054
Seniority	(0.062)	(0.061)	(0.065)	(0.064)	(0.083)
Majority party	0.659^***	0.426^*	0.651^***	0.376^*	0.409^*
Majority party	(0.079)	(0.172)	(0.079)	(0.164)	(0.169)
Majority leader	0.572^***	0.557^***	0.560^***	0.541^***	0.444^**
Majority leader	(0.160)	(0.162)	(0.159)	(0.160)	(0.164)
Minority leader	–0.028	–0.019	–0.029	–0.019	–0.030
Minority leader	(0.119)	(0.118)	(0.119)	(0.119)	(0.117)
Speaker	–0.512	–0.509	–0.437	–0.428	–0.288
Speaker	(0.368)	(0.355)	(0.322)	(0.304)	(0.231)
Committee chair	3.507^***	3.487^***	3.502^***	3.479^***	3.376^***
Committee chair	(0.401)	(0.401)	(0.400)	(0.399)	(0.375)
Subcommittee chair	0.266^**	0.254^*	0.266^**	0.253^*	0.240^*
Subcommittee chair	(0.097)	(0.099)	(0.097)	(0.100)	(0.099)
Power committee member	–0.476^***	–0.481^***	–0.481^***	–0.487^***	–0.449^***
Power committee member	(0.120)	(0.120)	(0.120)	(0.120)	(0.120)
Size of congressional delegation	0.035	0.034	0.035	0.034	0.037
Size of congressional delegation	(0.039)	(0.038)	(0.038)	(0.038)	(0.037)
Vote share	–0.002	–0.003	–0.002	–0.003	–0.002
Vote share	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)
Network size	0.084	0.120	–0.034	0.001	–0.050
Network size	(0.133)	(0.132)	(0.122)	(0.124)	(0.129)
Network density	–0.956	–0.763	–0.503	–0.248	–0.264
Network density	(0.665)	(0.691)	(0.752)	(0.767)	(0.775)
Ideological distance from the median		–0.496		–0.582	0.010
Ideological distance from the median		(0.368)		(0.354)	(0.409)
Status			0.176⁺	0.187^*	0.607^***
			(0.094)	(0.092)	(0.157)
Status * Ideological distance from the median					–0.823^*** (0.209)
Constant	–0.585	–0.499	–0.354	–0.239	–0.365
	(1.434)	(1.427)	(1.396)	(1.383)	(1.371)
N	2,620	2,620	2,620	2,620	2,620
R ²	0.420	0.421	0.422	0.423	0.438

Robust standard errors in parentheses. All tests are two-tailed. ⁺p < 0.10, ^*p < 0.05, ^**p < 0.01, ^***p < 0.001.

We add ideological distance from the median in model 2. The coefficient of ideological distance from the median is not significant, indicating that a legislator’s ideological distance from the median on its own, once other factors are taken into account, does not influence her legislative effectiveness.

We add status in model 3 (and remove ideological distance from the median in this model to show the effect of status across the models). The effect of status on legislative effectiveness is positive and significant (p = 0.062), which provides support for the baseline expectation. We add status and ideological distance from the median together in model 4. The results are consistent with those presented in model 2 and model 3. The coefficient of ideological distance from the median is not significant, and the coefficient of status is positive and significant (p < 0.05). In model 5, we add the interaction between ideological distance from the median and status. The coefficient is negative and significant (p < 0.001), indicating that the positive relationship between status and legislative effectiveness is weaker (negatively moderated) as the legislator’s ideological distance from the median increases. This finding provides support for our hypothesis.

The coefficients in model 5 indicate that for legislators whose ideological distance from the median is one standard deviation below the mean (what one might consider as ideologically orthodox or mainstream legislators), one standard deviation increase in status increases legislative effectiveness by 0.21 standard deviations. However, for legislators whose ideological distance from the median is one standard deviation above mean (i.e. ideologically non-mainstream legislators), one standard deviation increase in status yields no increase whatsoever in legislative effectiveness (it in fact decreases by -0.01 standard deviations, but practically this is not different from no change). Another way of indicating the strength of the interaction effect is that for legislators whose ideological distance from the median is greater than 0.57 (which places them on the 61st percentile in terms of their ideological distance from the median), even a two standard deviation increase in status does not yield a statistically significant increase in their legislative effectiveness.

We illustrate the interaction effect between status and ideological distance from the median in Figure 1. The solid line plots the effect of status on legislative effectiveness when ideological distance from the median is one standard deviation below the mean (legislators close to mainstream). The dashed line plots the same relationship when ideological distance from the median is one standard deviation above mean (legislators far from the mainstream).

Figure 1.

Plot of the interaction between status and ideological distance from the median on legislative effectiveness (using model 5 in Table 2).

Robustness Analysis

First, we use an alternative dependent variable, the (log) number of bills that passed the House, as in Liu and Srivastava (2019). We present the results in Table 3, with the interaction effects plotted in Figure 2. Our hypothesis continues to receive support (p < 0.01), with the positive main effect of status also continuing be statistically significant (p < 0.01).

Table 3.

Legislator fixed effects OLS models predicting number of bills that passed House.

	(1)	(2)	(3)	(4)	(5)
Bill valence	3.005^***	3.008^***	3.000^***	3.002^***	3.014^***
	(0.263)	(0.264)	(0.260)	(0.261)	(0.260)
Seniority	0.047⁺	0.049^*	0.044	0.045⁺	0.045
	(0.025)	(0.024)	(0.027)	(0.026)	(0.030)
Majority party	0.375^***	0.475^***	0.371^***	0.455^***	0.462^***
	(0.036)	(0.083)	(0.036)	(0.083)	(0.083)
Majority leader	0.360^***	0.367^***	0.355^***	0.361^***	0.338^***
	(0.087)	(0.087)	(0.087)	(0.087)	(0.086)
Minority leader	0.081	0.077	0.080	0.077	0.074
	(0.080)	(0.080)	(0.080)	(0.080)	(0.080)
Speaker	–0.492^***	–0.494^***	–0.459^***	–0.461^***	–0.428^***
	(0.144)	(0.149)	(0.126)	(0.131)	(0.116)
Committee chair	0.874^***	0.883^***	0.872^***	0.879^***	0.855^***
	(0.075)	(0.075)	(0.075)	(0.075)	(0.074)
Subcommittee chair	0.134^**	0.138^**	0.134^**	0.138^**	0.135^**
	(0.042)	(0.042)	(0.042)	(0.042)	(0.042)
Power committee member	–0.201^***	–0.199^***	–0.203^***	–0.201^***	–0.192^***
	(0.054)	(0.054)	(0.054)	(0.054)	(0.054)
Size of congressional delegation	0.020	0.020	0.020	0.020	0.021
	(0.019)	(0.019)	(0.019)	(0.019)	(0.019)
Vote share	0.000	0.001	0.001	0.001	0.001
	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)
Network size	0.073	0.058	0.021	0.010	–0.002
	(0.067)	(0.067)	(0.069)	(0.069)	(0.069)
Network density	–0.286	–0.369	–0.084	–0.162	–0.166
	(0.319)	(0.318)	(0.332)	(0.333)	(0.332)
Ideological distance from the median		0.213		0.178	0.317^*
		(0.154)		(0.153)	(0.160)
Status			0.078^**	0.075^**	0.174^***
			(0.028)	(0.028)	(0.042)
Status * Ideological distance from the median					–0.193^** (0.063)
Constant	–1.002	–1.039	–0.899	–0.935	–0.964
	(0.664)	(0.664)	(0.662)	(0.663)	(0.662)
N	2,620	2,620	2,620	2,620	2,620
R ²	0.381	0.381	0.383	0.384	0.388

Robust standard errors in parentheses. All tests are two-tailed. ⁺p < 0.10, ^*p < 0.05, ^**p < 0.01, ^***p < 0.001.

Figure 2.

Plot of the interaction between status and ideological distance from the median on number of bills that passed House (using model 5 in Table 3).

Second, even though research indicates that the median of the majority party is close to the median of the chamber, and previous studies have used the distance from the median of the chamber (Volden et al., 2013; Wiseman & Wright, 2008), to assess the robustness of our results we also operationalize distance using ideological distance from the median ideology of majority party. The correlation between our main measure of distance and this alternative is 0.91. The results are consistent with those reported in Table 2. The effect of status on legislative effectiveness is positive and significant (p = 0.054), and the coefficient of the interaction between ideological distance from the median ideology of majority party and status is negative and significant (p < 0.001).

Third, the β used in our operationalization of status is 0.75 times the reciprocal of the largest eigenvalue. As we detail in note 4, the correlations between the status scores using different values of β, ranging from 0.6 to 0.995, are very high. If we re-run our estimations in Table 2 using an alternative operationalization in this range, the effect of status on legislative effectiveness remains positive and significant (p < 0.05), and the coefficient of the interaction between ideological distance from the median and status remains negative and significant (p < 0.001).

Fourth, we operationalized status by using eigenvector centrality instead of Bonacich’s centrality. We re-ran the estimations in Table 2 using this alternative operationalization. The effect of status on legislative effectiveness remains positive and significant (p < 0.05), and the coefficient of the interaction between ideological distance from the median and status remains negative and significant (p < 0.05).

Fifth, Kirkland (2011) suggests that weak ties between legislators are useful in increasing effectiveness. To account for this possibility, we follow Kirkland (2011) to calculate measures for legislators’ strong ties and weak ties. We created four measures, number of strong ties, number of weak ties, secondary connections from strong ties and secondary connections from weak ties.⁸ We added these four measures to our models (i.e. those in Table 2) and our results continue to hold. The effect of status on legislative effectiveness remains positive and significant (p < 0.05), and the coefficient of the interaction between ideological distance from the median and status remains negative and significant (p < 0.001). In our estimations, we do not see any of these four new measures as significantly related to legislative effectiveness (p > 0.25).

Finally, our dependent variable is a sum of five terms that correspond to the relative shares of total legislative activity for each of the five stages of a bill. We observe that the first component (i.e. number of bills introduced by a legislator) of LES is correlated with our Bonacich centrality status measure (r = 0.47), which might raise a concern. Therefore, we constructed an alternative measure of LES by excluding the number of bills introduced by a legislator from our calculation. We re-ran our estimations using this modified outcome measure. The coefficient of status remains positive (p < 0.062) and the interaction between status and ideological distance is still negative and significant (p < 0.001).

Conclusion

Extant literature often considers that organizational influence, the ability to get one’s ideas or initiatives adopted by the organization, as a deterministic outcome or even an inherent attribute of status. We challenge this view and argue that status converts into greater influence only for actors whose ideology falls within what is considered mainstream within the organization. The more an actor’s ideology deviates from mainstream ideology, the less her status translates into increased organizational influence. We tested this hypothesis using data on the work of legislators in the House of Representatives in the US Congress. We followed 873 individual legislators and traced their status, ideology and influence over eight consecutive congresses. Our analyses lend strong support to the argument that status enhances influence only for ideologically mainstream actors, but not for actors who are far from the mainstream.

Our study advances the literature in several ways. First, we illuminate an important contingency – ideology – affecting the relationship between status and influence. We discussed how previous literature notes that status yields influence via three distinct processes – it increases attention, it elicits higher evaluations and it facilitates coalition building – and proposed that these effects are contingent on the ideological position of the focal actor relative to what is considered to be mainstream within the organization. We argued that these three mechanisms are operative insofar as actors are ideologically mainstream, but their strength diminishes when the actor’s ideological position is far from the mainstream. By spelling out how the effects of these mechanisms are contingent on actors’ position in the ideology space, this study goes beyond a deterministic view of the status–influence link and sheds light on the conditions under which status confers influence. Even though status has been put forth as an important contingency factor for the implications of other social mechanisms, such as homophily (Ertug, Gargiulo, Galunic, & Zou, 2018), our arguments and findings highlight that the implications of status itself are also contingent.

Second, by illuminating how ideology moderates the positive effect of status, we take a step towards providing a more culturally informed perspective of status in organizations. Researchers have noted that status is an inherently cultural product, noting that shared cultural beliefs underpin the emergence of status hierarchies, as well as the differentiation in influence that ensues from such hierarchies (Ridgeway & Correll, 2006). Prior studies have also argued that shared cultural beliefs are necessary for status distinctions to diffuse from micro-level interactions to the organizational level and even to large-scale societies (Grow, Flache, & Wittek, 2017). Despite recognition of the cultural nature of status, research on the effects of status has largely assumed culture away, rather than examining the interplay between culture and status. Our study focused on one aspect of culture – ideology – that has been shown to shape both how actors interpret and evaluate each other’s ideas and actions and how they relate to one another (Pratt, 2000, p. 488; Goll & Zeitz, 1991). By illuminating how the effect of status on organizational influence is contingent on actors’ position in an ideological space, we substantiated the view that status is an inherently cultural asset whose value depends on predominant cultural schemas and interpretations within the organization. Goldberg, Srivastava, Manian, Monroe and Potts (2016) found that being culturally mainstream helps organizational members leverage the benefits inherent in brokerage positions. Complementing this result, we showed that fitting into an organization’s ideological landscape is necessary in order to reap the benefits of status as well. By integrating insights from the organizational literatures on ideology and status, this finding enriches current understandings of status and adds new insight into the interplay of structure and culture within organizations.

Third, we examined how ideology moderates the influence of high-status actors within a political organization, but we believe that our findings would extend to the context of business organizations too. The view of status as a cultural asset that we presented posits that the mechanisms by which actors confer organizational influence lose potency the further away these actors position themselves from the organization’s ideological mainstream. Whereas political ideologies reflect belief and value assumptions about the functioning of societies at large, prior studies on the role of ideology in business companies emphasized the importance of professional (Freidson, 1994; Weitz & Shenhaav, 2000), managerial (Bowles, 1989; Raz & Fadlon, 2006) and corporate ideologies (Goll & Sambharya, 1995; Goll & Zeitz, 1991). Despite this difference in focus, at a fundamental level ideology operates similarly in political and business organizations: it provides a set of predominant values and beliefs that shape how organizational members make sense of organizational life and informs how they relate to one another and evaluate each other’s opinions, ideas and initiatives. Thus, although the particular focus of predominant ideologies is likely to differ between political and business organizations, we suggest that ideologies are likely to moderate the link between status and organizational influence similarly. We are hopeful that our findings will spur new studies to examine this hypothesis.

Finally, although we focused on the role of ideology in moderating the status–influence relationship, the explanatory framework we proposed may prove useful in elucidating other important organizational phenomena. For example, a long line of literature has examined the dynamics of coalition building within organizations. This literature recognized that status (Denis, Lamothe, & Langley, 2001; Greve & Mitsuhashi, 2007; Zhang & Greve, 2019) and ideology (Alvesson, 1992) play a crucial role in shaping both coalition-building strategies and outcomes. However, the link between status and ideology has remained understudied. The culturally informed view of status we have advanced suggests that neither status nor ideology alone may provide a satisfactory understanding of coalition-building dynamics in organizations, because actors’ status and ideological positions jointly affect their ability to forge and join coalitions. Applying our theoretical arguments to explain coalition-building processes may not only enrich the literature on coalition building, but it may also help us extend our understanding of how ideology moderates organizational influence beyond the individual level. Whereas the present study examined how an actor’s status and ideological position affect her influence, future research may consider the whole network of coalition-buliding ties as they unfold throughout the organization. Questions spring to mind when taking this broader perspective. For example, how does the joint distribution of status and ideological positions across an organization’s members affect the emergence of coalitions? Under what conditions might we expect a dominant coalition to develop around the ideological mainstream and under what conditions should we expect multiple coalitions to gain footing at the fringes of the ideological landscape? How do status and ideology affect the internal cohesion of coalitions and, relatedly, the extent of inter-coalition competition? Whereas these questions fall outside the scope of our analysis, we believe that employing a perspective that considers the interplay of status and ideology in affecting actors’ influence within organizations offers great potential in this area.

Our study has limitations, which point to opportunities for future research. We build on status mechanisms (attention, evaluation and coalition building) that are linked to influence, but we do not observe these mechanisms empirically. Directly measuring these mechanisms would deepen our understanding of the scope conditions of our arguments and findings. For example, our hypothesis may not extend to organizations where actors’ ideology is not visible to other organizational actors, or where the decision-making process is highly centralized, such that coalitions and support from colleagues are not critical. On the contrary, our findings are likely to be especially relevant in contexts in which actors’ identity is both tightly linked to their ideology and observable by others, and where exerting influence requires leveraging the support of multiple decision makers across the organization. Prior research suggests that there are many organizations in which these latter conditions apply such as, for example, professional service firms and healthcare organizations (Denis et al., 2001; Empson, 2017; Empson & Langley, 2015; March, 1962; Morris, Greenwood, & Fairclough, 2010). Examining our theory in other organizational settings would clarify the generalizability and boundary conditions of our arguments and illuminate other facets of the link between status, ideology and influence.

Footnotes

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Tengjian Zou

Notes

Author biographies

François Collet is Associate Professor (with tenure) at ESADE Business School, Ramon Llull University. He is interested in the sociological and psychological mechanisms that shape the perception of value. He also investigates how networks affect individual performance and segregation. He is director of the Master of Research at ESADE. He holds a DPhil in management from the University of Oxford. He teaches courses in organizational design and organizational theory.

Gianluca Carnabuci is associate professor of organizational behavior at ESMT Berlin. He earned a PhD in social and behavioral sciences from the University of Amsterdam. His research examines the role and dynamics of social networks across multiple levels of analysis, including individuals, ﬁrms and technology domains.

Gokhan Ertug is professor of strategic management at the Lee Kong Chian School of Business, Singapore Management University. He received his PhD from INSEAD. His research interests include social networks, status, reputation and international business.

Tengjian Zou is completing his PhD at Lee Kong Chian School of Business at Singapore Management University. He will be joining the School of Management at Zhejiang University as an Assistant Professor. His research interests include social networks, status and learning.

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