Minority Legislators Sponsor and Cosponsor Differently from White Legislators: Causal Evidence from U.S. Congress

Abstract

How do race, ethnicity, and gender shape a legislator’s approach to bill sponsorship and cosponsorship? This paper examines how institutional marginalization influences the legislative strategies of racial and gender minority representatives. Constrained by systemic barriers that limit their ability to sponsor legislation, minority legislators prioritize cosponsorship to achieve policy goals, build coalitions, and demonstrate responsiveness to their constituencies. Using the quasi-experimental context of the 2016 and 2018 U.S. congressional elections, I apply the synthetic difference-in-differences estimator and find that minority legislators sponsor fewer bills but cosponsor significantly more than their non-Hispanic White counterparts. Additionally, race-gendered effects reveal that women of color sponsor significantly less legislation than non-minority legislators and men of color. These patterns cannot be explained by factors like freshman status or primary election competitiveness. The findings highlight the strategic adaptations of minority legislators to navigate structural inequities and amplify their legislative influence. This study is the first to use a causal inference approach to explore the intersection of race, gender, and sponsorship and cosponsorship of congressional bills, contributing to a deeper understanding of legislative behavior among marginalized groups.

Introduction

Bill Sponsorship and cosponsorship are significant legislative activities that elected representatives engage in daily. Both practices are well documented for their substantial electoral and policy implications (e.g., Talbert and Potoski 2002). They provide lawmakers with a way to set the agenda, signal to peers and constituents what issues they represent, and advance policy in a way that is meaningful to them and their careers (e.g., Bratton and Rouse 2011). While institutional determinants of sponsorship and cosponsorship activity are well documented, findings with respect to the effects of race and ethnicity remain inconsistent. As the racial and ethnic diversity within our electoral institutions continues to increase, learning how a legislator’s identity influences their behavior is important to further understand how descriptive and substantive representation interact beyond this arena.

Research examining the impact of race and ethnicity on bill sponsorship and cosponsorship reveals mixed findings. On the one hand, scholars emphasize that racial and ethnic minority legislators continue to face institutional disadvantages that limit their legislative influence. For instance, some studies suggest that Black and Latine legislators sponsor and cosponsor significantly fewer bills than their White counterparts, pointing to systemic marginalization within legislative institutions (e.g., Garand and Burke 2006; Rocca and Sanchez 2008; Volden and Wiseman 2014). Sponsorship and cosponsorship activity, in this context, is argued to be constrained by the lack of institutional power, limited access to committee leadership roles, and low prioritization of minority-focused issues by the broader legislature or those in charge of the legislative agenda.

Conversely, other research highlights strategic adaptations by minority legislators that provide a different narrative of marginalization. While minority legislators may sponsor fewer bills overall, they appear to engage more actively in cosponsorship, when compared to their racial counterparts. For example, Wallace (2014) finds that Black and Latine congress members cosponsor significantly more bills, particularly related to issues on immigration, education, and labor—topics that directly affect their constituencies. Similarly, Bratton and Rouse (2011) demonstrate that minority legislators are more likely to cosponsor a higher volume of bills introduced by their racial or ethnic peers in contrast to White legislators, reflecting network dynamics and the importance of coalition-building.

Race-gender scholarship adds an additional layer of complexity to understanding patterns of sponsorship and cosponsorship. Research has shown that female legislators, on average, sponsor and cosponsor significantly more legislation than their male counterparts (e.g., Anzia and Berry 2013; Lazarus and Steigerwalt 2018). Within these patterns, minority women emerge as particularly active, cosponsoring more bills than minority men (e.g., Tate 2002). These findings highlight the paradoxical position of women, particularly women of color, in legislative spaces. Despite facing more severe systemic inequities than men (e.g., Hawkesworth 2003), their intersectional identities foster creative and adaptive approaches to legislating (e.g., Dittmar, Sanbonmatsu, and Carroll 2018; Holman and Mahoney 2018; Reingold,Widner, and Harmon 2020). Moreover, the mixed nature of these findings is further influenced by methodological limitations in the existing literature. Endogeneity and causality issues remain significant obstacles, making it difficult to establish clear relationships between race, ethnicity, and legislative behavior.

In this article, I examine whether racial minority legislators engage in bill sponsorship and cosponsorship activity differently from their non-minority peers. I consider how the presence of institutional marginalization affects the representation style of minority representatives. Confronted with systemic barriers that limit their ability to successfully sponsor legislation, I argue that minority legislators intentionally use cosponsorship as a strategic tool to achieve policy goals, build coalitions, and align with high-profile legislative initiatives. Using individual-level bill sponsorship and cosponsorship data from the 113th to 116th Congresses (2013–2020), I apply the synthetic difference-in-differences (SDID) estimator and find that minority legislators sponsor fewer bills while cosponsoring more legislation than non-minority legislators.¹ Additionally, I identify race-gendered effects in sponsorship behavior, with women of color sponsoring significantly less legislation than both non-minority legislators and men of color.

These findings highlight the distinct strategies minority legislators adopt to advance their policy goals. While sponsorship is often linked to agenda-setting and legislative leadership, cosponsorship reflects a collaborative and adaptive approach to influencing policy. By leveraging cosponsorship, minority legislators can shape legislative outcomes, despite the structural constraints that may limit their ability to dominate the agenda directly. This strategic use of cosponsorship underscores their role as active and innovative participants in the legislative process, finding alternative pathways to exert influence and represent marginalized communities effectively. More broadly, this work contributes to the literature on United States politics by emphasizing the role that racial and ethnic identity plays in political representation. It highlights the role of political institutions in the study of race and ethnicity and how they should be considered when trying to understand minority representation.

Bill (Co)Sponsorship and the Marginalization of Minority Legislators

Scholarship on representation suggests that congressional legislators pursue three primary goals: reelection, the creation of good public policy, and influence within the institution (Fenno 1978), with an emphasis on reelection security as the top priority (Mayhew 2004). As a result, elected officials continuously engage in activities that can aid reelection prospects, including roll call voting, making public statements, and taking positions on issues (e.g., Jones and Baumgartner 2004; Rocca and Gordon 2010). Bill sponsorship and cosponsorship are tools that legislators use to achieve electoral and policy goals.

(Co)Sponsorship as Legislative Tools

Sponsorship of a bill typically involves introducing it and championing it through drafting, negotiation, and advocacy, thereby signaling leadership on a particular issue (e.g., Rocca and Gordon 2010). Although modern resources such as stock language, messaging bills, and institutional supports like the House Legislative Council have reduced some of the technical burdens of sponsorship, it remains a resource-intensive and politically costly activity, especially in the advocacy and negotiation phases (e.g., Schilling, Matthews, and Kreitzer 2023). By contrast, bill cosponsorship offers legislators a comparatively lower-cost and more collaborative route to align with key policy initiatives (e.g., Bratton and Rouse 2011; Kessler and Krehbiel 1996; Koger 2003). It allows members to demonstrate support for legislation at varying stages—early or late—so they can signal commitment, gauge political dynamics, and minimize potential backlash (e.g., Box-Steffensmeier, Arnold, and Zorn 1997; Kessler and Krehbiel 1996). In this sense, cosponsorship enhances coalition-building by broadening a bill’s base of support, which can bolster its perceived viability (e.g., Bernhard and Sulkin 2013; Schilling, Matthews, and Kreitzer 2023).

As the political landscape has evolved, the strategic value of cosponsorship has also expanded. Legislators increasingly take credit in media outlets and public discourse for bills they only cosponsor, effectively blurring the distinctions between sponsors and cosponsors (e.g., Eatough and Preece 2024; Grimmer 2013; Grimmer, Messing, and Westwood 2012). This occurrence may arise in part from the institutional limitation of allowing only one official sponsor per bill. Given the inherently collaborative nature of the legislative process, legislators who contribute significantly to the development of a bill but are not listed as sponsors often seek to claim credit through cosponsorship (e.g., Eatough and Preece 2024). Although sponsorship traditionally provides a more direct path to claiming legislative achievements, contemporary cosponsorship dynamics narrow the gap in benefits between both forms of bill engagement, thus significantly shaping a member’s reputation for efficacy and responsiveness.

Strategic Response to Barriers to Minority Legislating

Despite these opportunities for legislative participation, minority legislators face ingrained structural barriers that diminish their capacity to influence policy. Scholars point to repeated instances of silencing, stereotyping, and exclusion from leadership roles that undermine the authority and visibility of legislators from marginalized groups (e.g., Hawkesworth 2003). Such interpersonal biases can manifest in the dismissal of proposals tied to marginalized communities (e.g., Tyson 2016), effectively limiting the scope and acceptance of issues that minority legislators champion. In committee work, Black lawmakers endure higher rejection rates for bills, particularly those addressing Black-interest areas (e.g., Peay 2021; Volden and Wiseman 2014), while women face gendered power dynamics—including increased interruptions in hearings and diminished recognition of their expertise—that constrain their effectiveness (e.g., Ban et al. 2022; Miller and Sutherland 2023). These race-gendered hierarchies are even more pronounced for women of color, who navigate overlapping biases related to both race and gender (e.g., Hawkesworth 2003; Wineinger 2023).

For marginalized legislators, sponsorship and cosponsorship decisions take on heightened strategic importance. Sponsorship remains valuable for signaling policy leadership, yet it is costly and subject to a higher likelihood of rejection. In response, I argue that minority lawmakers increasingly turn to cosponsorship to overcome these institutional barriers. Cosponsorship allows them to build coalitions and influence broader bills by negotiating amendments or provisions that address their communities needs while minimizing the political costs inherent in leading legislation. Moreover, because minority legislators often place a premium on substantive policy gains (e.g., Ban et al. 2022; Reingold, Widner, and Harmon 2020), cosponsorship becomes an attractive pathway to achieve tangible results while still allowing them to showcase commitment to issues, align themselves with high-profile legislative initiatives, and gain credit among constituents and advocacy groups.

In this context, the use of bill cosponsorship is not merely instrumental for reelection or influence; it also reflects an adaptive response to the visible marginalization that limits more direct forms of legislative leadership. Similar strategies have been documented in other contexts, where minority legislators, faced with systemic barriers to successfully passing legislation, rely on alternative mechanisms to deliver resources and provide effective representation (e.g., Strawbridge et al. 2024). I argue that these approaches highlight the creative and strategic efforts of minority legislators to navigate an environment often resistant to their proposals. Taken together, these considerations lead to the expectation that, compared to their non-minority counterparts, minority legislators will sponsor significantly fewer bills while engaging in much higher levels of cosponsorship.

Data and Design

To test this expectation, I collect individual-level data on U.S. House Representatives for the 2013 – 2020 period and look at the electoral turnovers that occurred in the 2016 and 2018 elections in order to compare sponsorship and cosponsorship outcomes between those who were elected and those who were in office prior.² These outcome measures were collected from the Congress.gov site, whereas data on legislator characteristics (i.e., race, gender, and political party) were obtained from legislative House data belonging to the Center for Effective Lawmaking.

I restricted the study to this period for two reasons. First, out of all the previous congressional sessions, the congressional sessions in this period contain the highest number of minority legislators elected to office. Choosing this time period ensures the largest possible sample of minority House Representatives. Secondly, extending the period further back could create problems of endogeneity resulting from the decennial redistricting process. The redrawing of congressional boundaries results in the creation and dismantlement of congressional districts every 10 years—where the process begins during the first year of the decade and is settled by the second to third year.³ Changes in redistricting can influence legislative behavior (e.g., Bertelli and Carson 2011; Casellas 2011 Grose 2011; Sanchez 2023; Vishwanath 2024). As a result, including periods where redistricting occurs could endanger the validity of the study.

I identify congressional districts where: (1) racial minority representatives replaced Non-Hispanic White ones during either of the two elections (Treatment Group), (2) Non-Hispanic White Representatives replaced Non-Hispanic White ones (Placebo Group A), and (3) racial minority representatives replaced racial minority ones (Placebo Group B). I then compare bill sponsorship and cosponsorship trends between these three groups to congressional districts where: (1) Non-Hispanic White representatives (Control Group A) and (2) racial minority representatives (Control Group B) remained in office throughout the entire study period. Because almost all minority legislators that entered Congress during the 2016 and 2018 elections were Democrat candidates replacing White Democrats, I restrict the control sample to only include congressional district representatives that are Democratic throughout the entire study period.⁴

Overall, with all the data restrictions, I consider sponsorship and cosponsorship observations for a total of ${N_{co}}$ = 125 control district representatives and ${N_{tr}}$ = 35 treated congressional district representatives, where 18 belong to the treatment group, 9 to the placebo group A, and 8 to the placebo group B. Out of the 26 minority legislators in the treatment group and placebo group B, 3 of them are Asian, 12 of them are Black, 10 of them are Latine, and 1 of them is Native American.⁵

Synthetic Difference-in-Differences

Instead of arbitrarily selecting congressional district representatives from the control pool to compare sponsorship and cosponsorship outcomes, I draw on the synthetic difference-in-differences (SDID) estimator (Arkhangelsky et al. 2021) to rely on an algorithmic strategy to optimally select the best weighted combination of them to serve as a proper comparison group. SDID uses a data-driven approach to find unit weights ( ${\hat \omega _{sdid}}$ ) that assist in the construction of a counterfactual whose control units’ outcomes are, on average, similar to the pre-treatment trends of the treated units’ outcomes.

In this context, these unit weights would place more weight on the congressional district representatives whose cosponsorship and sponsorship trends are similar to those congressional district representatives who eventually transition out of office. In addition to these unit weights, the counterfactual produced by SDID also includes a set of time weights ( $\hat \lambda _t^{sdid}$ ) that give higher importance to time periods throughout the pre-treatment period that are, on average, most similar to post-treatment period observations across all selected control units (Clarke et al. 2023). Together, these weights along with the use of a two-way fixed effects regression are used by the estimator to produce the average causal effects of exposure to a treatment ( $\tau $ ):⁶

(1) $$\left( {{{\hat \tau }_{{\rm{sdid}}}},\hat \mu, \hat \alpha, \hat \beta } \right) = {\rm{arg}}\mathop {{\rm{min}}}\limits_{\tau, \mu, \alpha, \beta } \left\{ {\mathop \sum \limits_{i = 1}^N \,\mathop \sum \limits_{t = 1}^T \,{{\left( {{Y_{it}} - \mu - {\alpha _i} - {\beta _t} - {W_{it}}\tau } \right)}^2}\hat \omega _i^{sdid}\hat \lambda _t^{sdid}} \right\}$$

where ${Y_{it}}$ are the levels of sponsorship and cosponsorship from each representative for each session, $\mu $ is a constant term, ${\alpha _i}$ are congressional district representative fixed effects, ${\beta _t}$ are congressional session fixed effects, and ${W_{it}} \in $ {0,1} represents an electoral turnover where a new legislator takes over the congressional district.

As mentioned previously, SDID automates the process of adjusting the data to create a control group that can exhibit parallel trends up to the point of receiving treatment to make causal claims. Unit and time weights in SDID makes the estimator more robust, as it only uses similar units and periods across the panel, which eliminates biases and increases estimation precision (Arkhangelsky et al. 2021). At the same time, the inclusion of unit and time fixed effects that are normalized to zero helps avoid multicollinearity while enabling a flexible estimation of shared temporal aggregate factors and unit-specific factors (Clarke et al. 2023). These features make SDID well-suited for studies with limited treated units, as it allows for precise estimation while reducing the influence of noise and irrelevant variation. Moreover, the robustness of SDID in small-sample contexts is enhanced through its variance estimation techniques, such as block bootstrapping, which provide reliable confidence intervals and facilitate conventional inference.⁷

Results

Main Analysis

To ensure the validity of the causal estimates, the SDID estimator requires the parallel trends assumption, meaning that the synthetic control group should exhibit similar trends to the treatment group in the pre-treatment period. This assumption is validated by comparing pre-treatment trends for cosponsorship and sponsorship between treated units and their synthetic controls. As shown in Figures 1, 3, and 5 in Appendix Section 5, the pre-treatment trends for both sponsorship and cosponsorship closely align between the treatment groups and their constructed synthetic controls. This alignment supports the appropriateness of the SDID estimator for causal inference in this context.

In addition to verifying the parallel trends assumption, the SDID estimator enables the calculation of robust variance estimates, facilitating inference on the treatment effects observed across groups. Table 1 reports the weighted average treatment effects on the treated (ATT), derived from the SDID model specified in Equation 1.⁸ Column 1 presents the ATT for all treated minority legislators, capturing the overall results, while columns 2–4 provide robustness checks and subgroup analyses to evaluate the consistency of these findings. Using the control pool of legislators as a baseline, the average sponsorship and cosponsorship activity of White legislators is established as 22 bills (with a standard deviation of 13 bills) and 408 bills (with a standard deviation of 194 bills), respectively. These benchmarks provide context for interpreting the magnitude of the observed treatment effects.

Table 1. SDID weighted estimation results for legislative activity in treatment group

* p < .10, **p < .05, ***p < .01.

Note: Bootstrap standard errors in parentheses are based on 1,000 replications. All models are for the Treatment group where racial minority legislators replace non-racial minority legislators.

The main effects, shown in column 1, reveal that newly elected minority legislators sponsored an average of 9 fewer bills compared to the White legislators they replaced. This represents a statistically significant reduction (p < .01) and constitutes a 41% decrease in sponsorship activity relative to the average of 22 bills. In standardized terms, this decline corresponds to .69 standard deviations, signaling a substantial shift away from legislative sponsorship. In contrast, minority legislators cosponsored an average of 74 more bills than their White predecessors, an increase that is also statistically significant (p < .05). Relative to the benchmark of 408 bills, this reflects an 18% increase in cosponsorship activity, equivalent to .38 standard deviations. This finding suggests a moderate yet meaningful increase in legislative engagement through cosponsorship. Overall, part of these results align with some prior literature on legislative behavior, which has similarly found that minority legislators tend to sponsor fewer bills but engage more actively in cosponsorship compared to their White counterparts (e.g., Rocca and Sanchez 2008).

To ensure that the observed effects are not influenced by party changes, districts where the predecessor was a Republican White legislator replaced by a minority Democratic legislator were excluded from the analysis in column 2. This robustness check is crucial, as previous research (e.g., Garand and Burke 2006) highlights the significant role of party affiliation in shaping sponsorship and cosponsorship behavior. After excluding these districts, the results in column 2 remained consistent with the main analysis. Minority legislators sponsored an average of 11 fewer bills (compared to 9 in the main results) and cosponsored an average of 91 more bills (compared to 74 in the main results). Both effects are statistically significant (p < .01) and retain their direction and magnitude. These findings reinforce the conclusion that the observed changes in legislative behavior are not attributable to changes in party affiliation.

Intersectional Differences in (Co)Sponsorship

The main analysis highlights significant shifts in legislative behavior when White legislators are replaced by racial minority legislators. These findings suggest that, on average, racial minority legislators sponsor fewer bills but engage in significantly higher levels of cosponsorship compared to their White predecessors.

To further investigate the dynamics underlying these effects, an analysis was conducted to explore whether the intersection of race and gender contributes to variations in sponsorship and cosponsorship patterns. Existing scholarship documents the compounded structural barriers faced by women of color in legislative institutions (e.g., Hawkesworth 2003; Wineinger 2023). Simultaneously, other research suggests that women, including women of color, may demonstrate greater legislative effectiveness by sponsoring and cosponsoring more bills than men (e.g., Anzia and Berry 2013). This raises an important question: does separating the analysis by gender reveal patterns that align with the documented legislative effectiveness of women, or do the results instead highlight the compounded marginalization experienced by women of color?

The results of the subgroup analysis, presented in columns 3 and 4 of Table 1, reveal notable differences in sponsorship activity between minority men and women. Women of color drive the observed decrease in sponsorship activity, sponsoring an average of 13 fewer bills than their White predecessors would have, a statistically significant reduction (p < .01) consistent with the marginalization they face in legislative settings. By comparison, minority men sponsor an average of 4 fewer bills, a smaller and statistically insignificant reduction, suggesting that they may face fewer barriers to independently initiating legislation than women of color.

In contrast, cosponsorship patterns reveal significant increases for both minority men and women compared to their White predecessors. Women of color cosponsor an average of 95 more bills (p < .01), while minority men cosponsor an additional 78 bills on average (p < .05). The magnitude of these increases is broadly similar across genders, indicating that cosponsorship serves as an effective strategy for both groups to navigate legislative institutions and amplify their influence.

Placebo Tests

To ensure further robustness of the main analysis’ results, placebo tests were conducted to verify that the observed effects are attributable to racial and ethnic identity rather than alternative explanations, such as freshmen status. If freshman status, rather than race or ethnicity, drives the observed changes in legislative behavior, similar significant effects would be expected in groups where White legislators replaced White predecessors (Placebo Group A) and where minority legislators replaced minority predecessors (Placebo Group B). By contrast, for the main effects to hold, sponsorship and cosponsorship outcomes in Placebo Group A should show no significant differences.⁹

Table 2 presents the results of these placebo tests. In Placebo Group A, where White legislators replaced White predecessors, the results show that incoming legislators sponsored an average of 16 fewer bills and cosponsored 57 more bills than their predecessors. However, neither effect is statistically significant (p > .10), as indicated by the large standard errors (11.39 and 104.60, respectively). These findings suggest no meaningful differences in legislative behavior between incoming and outgoing White legislators, reinforcing the validity of the main analysis.

Table 2. SDID weighted estimation results for legislative activity in treatment group

* p < .10, **p < .05, ***p < .01.

Note: Bootstrap standard errors in parentheses are based on 1,000 replications. [a] Placebo group consists of 4 Black and 4 Latine legislators.

In Placebo Group B, which examines minority legislators replacing other minority legislators, the results are mixed. Incoming minority legislators sponsored around 1 more bill on average than those they replaced, but this effect was not statistically significant (p > .05). Conversely, for cosponsorship, incoming minority legislators cosponsored 105 fewer bills on average compared to their minority predecessors would have, a large statistically significant decrease (p < .05). This suggests a potential freshman effect for cosponsorship among minority legislators in this group, though it does not undermine the broader findings regarding differences between minority and non-minority legislators in the main analysis.

Overall, the placebo tests in Table 2 confirm that the main findings in Table 1 are not driven by freshman effects. The lack of significant effects in Placebo Group A supports the conclusion that racial and ethnic identity plays a critical role in shaping the legislative behavior observed in the main analysis. While the significant decrease in cosponsorship in Placebo Group B warrants further investigation, it does not challenge the main results that minority legislators, on average, sponsor fewer bills but cosponsor significantly more bills compared to their non-minority counterparts. In addition, when considering other mechanisms that can affect the main results’ estimates, such as primary election outcomes, I do not find evidence of them driving the results observed in them.¹⁰

Conclusion

I find strong causal evidence that racial minority legislators engage in legislative behavior distinct from their White counterparts. Specifically, minority legislators sponsor fewer bills but cosponsor significantly more, illustrating a shift in legislative strategy that prioritizes collaboration and coalition-building over direct agenda-setting. In addition, I find that this pattern is unique to minority legislators, as new non-minority legislators do not exhibit similar sponsorship and cosponsorship dynamics, indicating that being a freshman legislator alone doesn’t explain these differences.

These results highlight the strategic adaptation of minority legislators, who use cosponsorship to amplify their legislative influence in the face of systemic barriers. Unable to dominate the agenda-setting process through sponsorship alone, minority legislators turn to cosponsorship to build alliances, demonstrate productivity, and align with legislative initiatives that reflect their priorities. By cosponsoring a high volume of bills, minority legislators signal their commitment to addressing the needs of their constituencies while navigating institutional barriers.

The broader implications of these findings point to the need for further research into the intersection of race, institutional marginalization, and legislative strategies. While this study isolates the causal impact of racial turnover, future research should explore whether these patterns persist over time. Do minority legislators continue to rely on cosponsorship as they gain seniority and institutional power, or does their ability to sponsor bills increase with tenure and leadership positions? Examining sponsorship and cosponsorship as a longitudinal process rather than a static behavioral difference could provide deeper insights into how racial legislative strategies evolve.

Additionally, the role of constituency expectations and electoral pressures in shaping legislative strategies remains an open question. Minority legislators frequently represent racially diverse and politically competitive districts, which can incentivize them to engage in more cosponsorship to demonstrate legislative engagement and responsiveness to their constituents. Future work could examine whether sponsorship and cosponsorship behaviors are primarily shaped by institutional constraints within Congress or by external electoral factors that push minority legislators toward coalition-based strategies.

Finally, while this study leverages an SDID approach to estimate causal effects, it is important to recognize that, like other causal inference methods such as the Synthetic Control Method (SCM), SDID identifies the local average treatment effect (LATE)—capturing the impact of racial turnover within the specific set of analyzed districts. This means that while the findings provide strong causal evidence of how minority legislators behave differently when replacing White legislators in these contexts, they may not necessarily generalize to the full population of legislators in Congress. Addressing these questions can broaden our understanding of how race interacts with institutional constraints, electoral dynamics, and partisan structures to shape legislative behavior. The findings presented here highlight the importance of adaptation and strategic coalition-building for racial minority legislators, but further research is needed to fully capture the long-term trajectories, external influences, and broader applicability of these patterns in the U.S. Congress.