Article

Gender, Bilingualism, and Conflict Management Styles: Evidence from an Adult Sample in the United States

Authors

• Zhimin Hu Zhimin Hu ORCID profile. (opens in new tab) , zhi-min.hu@polyu.edu.hk(compose email, opens in email app.)
• Mark James Mark James ORCID profile. (opens in new tab)
• Eduardo Navarrete Eduardo Navarrete ORCID profile. (opens in new tab)

Abstract

This study investigates whether and how bilingualism intersects with gender to affect preferences for conflict management styles (CMS). Specifically, we compared gender differences across active and passive CMS in monolingual and bilingual individuals. Drawing on managerial and psycholinguistic research, we hypothesized that bilingualism would moderate gender differences in CMS. A pilot study (N = 64) and a main study (N = 371) were conducted with adult samples of U.S. born-and-raised monolinguals and bilinguals. In the main study, participants completed a refined 22-item instrument measuring CMS aggregated into active (i.e., dominating, integrating, compromising) and passive (i.e., avoiding, obliging) CMS. Multivariate analysis confirmed self-identified gender as a robust predictor of CMS differences. While further univariate analyses showed no effects for active styles, they revealed a significant interaction between gender and bilingualism for passive styles (p = .025). Post-hoc comparisons revealed that while monolingual women reported higher passive CMS scores than monolingual men (p < .001), this gender gap was absent among bilingual participants (p = .970). We interpret these findings through enhanced cognitive control afforded by managing two languages, which might equip bilinguals to better manage socialized passive defaults. Ultimately, these findings identify bilingualism as a subtle but meaningful boundary condition for CMS, highlighting linguistic identity as a resource for fostering more adaptive and less stereotyped conflict resolution in modern society.

Keywords:

interpersonal conflict, conflict resolution styles, gender conflict management, bilingualism conflict management, active-passive conflict styles

How to Cite:

Fueled by increasing globalization and emphasis on equity, modern societies and organizations are characterized by unprecedented demographic diversity (Dai & Chen, 2022; De Dreu & Gelfand, 2008; Holt & DeVore, 2005). The convergence of diverse values, norms, and behavioral expectations inherently increases the potential for interpersonal conflict (Boardman & Horowitz, 1994; Caputo et al., 2023; Gomez & Taylor, 2018; Korsgaard et al., 2008). Rather than viewing interpersonal conflict destructively, contemporary scholarship posits it as an inevitable yet dynamic process that, when managed constructively, can become highly beneficial (Deutsch, 2006; Honeycutt, 2003; Mikkelsen & Clegg, 2018; Tjosvold, 2006). For example, highly competitive or avoidant CMS often lead to relationship breakdown, emotional exhaustion, and reduced productivity (Bear et al., 2014; Benitez et al., 2018; Guerrero, 2020; Gugercin et al., 2023), cooperative CMS foster creativity, yield innovation, and enhance decision-making (Chua & Jin, 2020; De Dreu, 2012; T. Wang et al., 2021). The awareness of individual differences in conflict management styles (CMS, i.e., the characteristic patterns individuals employ to navigate conflict) is therefore crucial for improving interpersonal relationships (Deutsch, 1990; Rahim, 1983; Shabani et al., 2022; Wertheim, 2011). More nuanced understanding of the often overlapping identities driving CMS differences, thus, has important implications for management and negotiation research in an era of increasing diversity (Chua & Jin, 2020; Rahim & Katz, 2019; Riaz et al., 2016; Y. Wang et al., 2024).

The traditional dual-concern model classifies CMS based on the internal motives of “concern for self” and “concern for others” (Blake & Mouton, 1964; Rahim, 1983; Rubin, 1994), identifying five distinct styles (viz., dominating, integrating, compromising, obliging, and avoiding). However, because internal concerns are intrapersonal and difficult to objectively observe, scholars in the field have often relied on a meta-taxonomy that condenses CMS into higher-order categories, most notably along the active-passive¹ dimension (A. S. Chen et al., 2014; DeChurch & Marks, 2001; Tidd & Friedman, 2002; Van De Vliert & Euwema, 1994; Van De Vliert & Hordijk, 1989). This dimension differentiates CMS based on whether they manifest as a responsive and direct resolution versus an inert and indirect resolution (A. S. Chen et al., 2016; Van De Vliert & Euwema, 1994). Despite the different motivational underpinnings, dominating, integrating, and compromising styles are theoretically unified as active CMS by their reliance on deliberate engagement, active confrontation of the problem, and a “take-charge” behavioral orientation (Dijkstra et al., 2011; Fousiani et al., 2025; Guerrero, 2020; Syna Desivilya & Eizen, 2005). In contrast, avoiding and obliging can be grouped into passive CMS, as both are characterized by evasion, non-confrontation, and an “escape” orientation toward the conflict (Beitler et al., 2018; Davis et al., 2023; Guerrero & Gross, 2014; Tidd & Friedman, 2002). As noted by DeChurch and Marks (2001), collapsing the five styles into these higher-order categories allows for a more parsimonious and behaviorally focused investigation of how diverse populations, such as individuals with differing gender and linguistic identities, navigate interpersonal conflicts.

Background

Gender and Conflict Management Styles

While some literature posits a male-female divide in CMS (e.g., Brahnam et al., 2005; Brewer et al., 2002; Holt & DeVore, 2005), others observed that the effects tend to be weak, contradictory, or entirely non-significant (see Al Wekhian, 2015; Boonsathorn, 2007; Kozan, 2002; Shockley-Zalabak, 1981; Sternberg & Soriano, 1984). This ambiguity could stem from several methodological limitations in prior work. First, gender effects on CMS are highly context-dependent, fluctuating significantly based on organizational status, managerial experience, and relational power dynamics (Chua & Jin, 2020; Chusmir & Mills, 1989; Cingöz-Ulu & Lalonde, 2007; Korabik et al., 1993). Second, previously observed mixed findings may have been linked to the conflation of biological sex and psychological gender roles (Bordean et al., 2020; Holley et al., 2010). As psychological gender identity is often a far stronger predictor of CMS than biological sex (Brahnam et al., 2005; Brewer et al., 2002), accordingly, the present study focuses on interpersonal peer conflict and operationalizes gender as individual self-identification rather than strict biological sex to offer a more contextualized and precise evaluation of gender differences in CMS.

By isolating self-identified gender, we expected clear CMS differences to emerge along the active-passive spectrum. Individuals are profoundly socialized to adhere to disparate gender-role expectations (Benharda et al., 2013; Eagly & Wood, 1991; Jurma & Powell, 1994), resulting in differential preferences of CMS in men and women. Men are frequently encouraged to adopt an agentic or masculine orientation prioritizing independence, assertiveness, and control, which naturally aligns with a direct, take-charge, active CMS orientation (Bear et al., 2014; Brewer et al., 2002; Holt & DeVore, 2005; Rahim & Katz, 2019). Conversely, women face disproportionate societal pressure to cultivate a communal or feminine orientation focused on interdependence, caregiving, and relationship maintenance (Bear et al., 2014; Brewer et al., 2002; Chua & Jin, 2020; Valentine, 2001). Thus, they are typically socialized to utilize passive CMS to minimize interpersonal friction and preserve relational harmony (Carli, 1989; Gbadamosi et al., 2014; Holt & DeVore, 2005). Therefore, we proposed the following:

H1. Gender will demonstrate a significant main effect on active CMS, such that men will report higher scores than women.

H2. Gender will demonstrate a significant main effect on passive CMS, such that women will report higher scores than men.

The Moderating Role of Bilingualism

While gender differences have been widely studied, the role of linguistic diversity in the modern global workforce has been largely overlooked in conflict management research (but see Barragan Diaz et al., 2026; Grant et al., 2023; Mills, 2006). For example, bilingualism is increasingly recognized as an important factor in conflict resolution, and bilingual education as a strategic advantage (Bekerman, 2005; Bekerman & Horenczyk, 2004; Bekerman & Shhadi, 2003; Grant et al., 2023). Given that the majority of the global population is bilingual (Grosjean, 2010) and that bilingualism is becoming more prevalent in historically monolingual contexts like the United States (Guiberson & Ferris, 2019), the interaction of gender and bilingualism on CMS thus warrants closer scholarly examination.

Contemporary psycholinguistic research establishes that both language systems of a bilingual individual are constantly active and competing for selection, even in single-language settings (Andras et al., 2023; Bialystok & Craik, 2022; Teubner-Rhodes et al., 2019). Managing this continuous cross-linguistic competition requires robust executive control, selective attention, and conflict monitoring skills (Abutalebi et al., 2012; Chung-Fat-Yim et al., 2022; Green, 2011). Over time, this linguistic regulation trains domain-general conflict resolution skills, such that during disputes, bilinguals can be less susceptible to emotional and normative interference (Ardila et al., 2017; Hu & Navarrete, 2024; Kazanas et al., 2019), and utilize more deliberate and reflective cognitive processing rather than automatic reactions (Ardila et al., 2017; Barragan Diaz et al., 2026; Hu et al., 2026). Therefore, we reason that enhanced cognitive control could serve as the primary mechanism influencing CMS.

Operating downstream from this primary cognitive mechanism are several complementary socio-cognitive phenomena. Because bilinguals utilize greater cognitive control, they are often less adherent to descriptive norms and stereotypes in a less dominant language (Geipel et al., 2015; Hu & Navarrete, 2024; Jankowiak et al., 2024) and, consequently, better equipped to suppress socialized default scripts by employing complex discursive strategies (e.g., strategic silence, code-switching, or narrative contestation) to resist or negotiate coercive patriarchal structures (Appalraju & De Kadt, 2002; Martin, 2003; Mills, 2006; Piller & Pavlenko, 2006). Furthermore, research has shown that bilingualism enhances perspective-taking abilities in men, bringing their scores up to the level of women (Tarighat & Krott, 2021), and that bilinguals often display more progressive, egalitarian attitudes toward gender roles (Luo & Wei, 2024; Pavlenko, 2001; Shen & Wei, 2025). In sum, by primarily boosting cognitive control, which subsequently facilitates perspective-taking and loosens rigid gender ideologies, we expected bilingualism to moderate the gender gaps typically observed in monolingual individuals. Therefore, we proposed the following hypotheses:

H3. Bilingualism will moderate the relationship between gender and active CMS, such that the gender difference will be attenuated among bilinguals compared to monolinguals.

H4. Bilingualism will moderate the relationship between gender and passive CMS, such that the gender difference will be attenuated among bilinguals compared to monolinguals.

Methods

To address the lack of cross-cultural metric equivalence and to ensure an updated psychometric consistency of traditional CMS inventories (Filsecker et al., 2020; Kim & Leung, 2000; Lee & Rogan, 1991; Weldon & Jehn, 1995), we conducted a two-phase scale validation procedure (Boateng et al., 2018) via principal component analysis (PCA) to refine the instrument for measuring interpersonal CMS (i.e., Cai & Fink, 2002), before directly addressing these research questions and hypotheses. All analyses were performed using R (R Core Team, 2022).

Pilot Study

Scale Selection

A pilot study was conducted to evaluate the psychometric properties of the 29-item scale for managing interpersonal conflict (Cai & Fink, 2002) (see Supplementary Materials). The selected scale was theoretically grounded in past research which offered adequate initial internal consistency (Rahim, 1983; Rahim & Magner, 1995; Weider-Hatfield, 1988).

Participants

Sixty-four undergraduate and graduate students (M _age = 26.30, SD = 8.60; 33 women) from a medium-sized public university in southern U.S. completed the questionnaire as part of their class assignment. All respondents were U.S. citizens, native English-speakers, and born-and-raised in the U.S.

Procedure

The respondents were prompted to think within their own experience of recent conflicts with their peers (e.g., friends, coworkers, and classmates) and complete the 29-item CMS questionnaire using a 7-point Likert scale (1 = Strongly disagree, 7 = Strongly agree). At the end of the questionnaire, they answered questions regarding their demographic, linguistic, and socioeconomic background.

Scale Validation

PCA was conducted to assess the underlying factor structure. The data demonstrated adequate sampling adequacy (KMO = .70; χ²(406) = 1284.57, p < .001). Because behavioral conflict styles are theoretically expected to correlate, Promax rotation was utilized to maximize theoretical accuracy (Hair et al., 2019). Using an eigenvalue cutoff of 1.0, five initial components emerged (viz., dominating, compromising, integrating, avoiding, and obliging). Then, items were evaluated against conventional psychometric thresholds: two items were eliminated for failing to meet a primary factor loading of > .50 or for exhibiting secondary cross-loadings of > .30. The remaining items were subjected to content pruning. Specifically, three items from the compromising subscale were eliminated because they explicitly utilized the construct’s namesake (i.e., “compromise”). Two additional items were removed due to extreme semantic overlap with superior items in their clusters. Following the removal of these seven items, the finalized 22-item scale yielded a five-factor structure that explained 72.6% of the variance. Internal consistency for all retained subscales was high (Cronbach’s αs ranging from .85 to .90; see Supplemental Materials). Finally, minor wording adjustments were made to reduce semantic redundancy and improve clarity (see Table 1 for the refined 22-item scale).

Table 1 Main Study Questionnaire

Main Study

Participants

The target sample size for the main study was determined via two methodological benchmarks. First, the psychometric recommendation of a minimum 10:1 participant-to-item ratio (Costello & Osborne, 2005) would necessitate a baseline of 220 respondents. To ensure sufficient statistical power, an a priori power analysis was conducted using G*Power 3.1 (Faul et al., 2007). The model was specified for a two-way MANOVA (main effects and interactions). To detect a conservative small effect size f²(V) = 0.02 across two dependent variables with 80% power at an α = .05 significance level, a minimum of 344 participants was required. A total of 390 respondents completed the survey via Prolific.

A persistent methodological challenge in this field is the conflation of language and culture. Observed cognitive and behavioral differences in bilingual populations could stem from immigrant acculturation or cultural frame-switching rather than the actual cognitive and social demands of managing two languages (S. X. Chen, 2015; Lehtonen et al., 2018; Samuel et al., 2018; Xie et al., 2022). To rigorously isolate the effects of bilingualism from the confounding bicultural effects often experienced by immigrants or late-stage language learners, the bilingual sample was restricted to early simultaneous bilinguals. All participants were required to be U.S. citizens that are born and raised in the U.S. The specific pre-screeners for monolinguals were being raised monolingual and not being fluent in another language, whereas those for bilinguals were being raised bilingual and being fluent in another language. Participants showing a mismatch between Prolific pre-screeners and self-reports (4 respondents reported being nonnative English speakers) and participants showing low response variation (15 respondents with low response variation SD < 0.50) were eliminated from further analyses. The final sample consisted of 371 individuals (M _age = 36.00, SD = 11.44; N _monolingual = 216, N _bilingual = 155²; N _men = 211, N _women = 160).

Procedure

The respondents were prompted to draw upon their own experience of recent conflicts with their peers (e.g., friends, coworkers, and classmates) and complete the refined 22-item CMS questionnaire (see Table 1) using a 7-point Likert scale (1 = Strongly disagree, 7 = Strongly agree). At the end of the questionnaire, they answered questions regarding their demographic, linguistic, and socioeconomic background. This study was approved by the Institutional Review Board of the second author’s affiliation and all participants provided informed consent before starting the survey.

Results

Principal Component Analysis

To verify the stability of the factor structure of the refined 22-item scale used in the main study, PCA was conducted. The data demonstrated high suitability for extraction (KMO = .86; χ²(231) = 5006.98, p < .001). Consistent with the pilot findings, the PCA utilizing Promax rotation yielded the expected five-factor structure, which cumulatively explained 73.0% of the total variance. All 22 items demonstrated adequate loadings on their theoretically assigned constructs, with no problematic cross-loadings (see Supplemental Materials for details). Internal consistency for the finalized subscales in the main study remained high (viz., dominating α = .90, compromising α = .88, integrating α = .88, avoiding α = .88, and obliging α = .86).

Data Aggregation and Analytical Strategy

Consistent with this established meta-taxonomy, the three engagement-oriented styles (i.e., dominating, integrating, and compromising) were aggregated to create a composite score for active CMS. The two withdrawal-oriented styles (i.e., avoiding and obliging) were aggregated to create a composite score for passive CMS. These two higher-order composite scores served as the dependent variables for subsequent analyses. Descriptive statistics for all variables are presented in Table 2.

Table 2 Descriptive Statistics for Active and Passive CMS

Note. Means (Standard Deviations) across Linguistic and Gender Groups.

Multivariate Analysis of Variance (MANOVA)

To address the research question regarding overall main and interactive effects of gender and bilingualism on CMS, a 2 (Gender: Men, Women) × 2 (Bilingualism: Monolingual, Bilingual) between-subjects MANOVA³ was conducted. The multivariate results (see Table 3) revealed a significant main effect of Gender on CMS (Wilks’ Λ = .974, F(2, 366) = 4.93, p = .008, η_p² = .026). The main effect of Bilingualism was statistically non-significant (Wilks’ Λ = .999, F(2, 366) = 0.14, p = .868) and the multivariate interaction between Gender and Bilingualism did not cross the conventional significance threshold (Wilks’ Λ = .986, F(2, 366) = 2.54, p = .080, η_p² = .014). Conjointly, these results respond to the research questions: while gender held as a robust predictor of CMS, bilingualism did not show a blanketing effect; nonetheless, because gender and bilingualism showed a trending interaction, further analyses at the univariate level were conducted.

Table 3 Multivariate (MANOVA) and Univariate (ANOVA) Analysis of Variance for Conflict Management Styles

Univariate Analyses of Variance (ANOVA)

ANOVAs were conducted for active and passive CMS, respectively (see Table 3 and Figure 1). On one hand, the univariate results regarding active CMS showed no significant main effect of Gender (F(1, 367) = 3.35, p = .068, η_p²= .008), though men trended toward higher scores than women; also, there was no significant interaction between Gender and Bilingualism (F(1, 367) = 0.38, p = .535). These results failed to support H1 and H3, respectively. On the other hand, however, the univariate analysis of passive CMS revealed a significant main effect of Gender (F(1, 367) = 4.79, p = .029, η_p² = .013), fully supporting H2. Crucially, a significant Gender × Bilingualism interaction emerged (F(1, 367) = 5.05, p = .025, η_p² = .014), supporting H4. Post hoc pairwise comparisons within passive CMS further revealed a significant gender difference among monolinguals, with women scoring significantly higher than their male counterparts (t(367) = 3.47, p < .001); whereas, among bilingual participants, this gender gap was unobserved (p = .970) (see Figure 1).

Figure 1 Interaction Effects of Bilingualism and Gender on Active and Passive CMS

Note. Violins represent the kernel density distribution of the data, while jittered points represent individual respondent scores. The central black points represent group means, and the error bars indicate 95% confidence intervals. Active CMS is a composite score comprising dominating, integrating, and compromising styles; Passive CMS is a composite score comprising avoiding and obliging styles. Statistical annotations indicate the results of two-way univariate ANOVAs for interaction effects and follow-up pairwise comparisons for gender differences within each linguistic group; ns = non-significant (p > .05).

Discussion

Grounded in both conflict management and psycholinguistic research, the primary objectives of this study were twofold: to clarify the relationship between gender identity and active-passive CMS, and to examine whether linguistic identity (i.e., monolingual vs. bilingual) serves as a boundary condition for gender differences in CMS. Our results demonstrate a modest attenuation of gender differences, specifically within passive CMS. While monolingual women reported significantly higher scores of passive CMS than monolingual men, this disparity was statistically absent among bilinguals. As for active CMS, despite men showing higher scores than women, neither the gender main effect nor the gender and bilingualism interaction reached statistical significance. The combined results suggest that while bilingualism may modulate gender differences in CMS, such modulation can be dependent on the disparate social and psychological demands of conflict styles.

The attenuation of the gender gap in passive CMS for bilinguals might be rooted in enhanced cognitive control that can have downstream social and affective effects. The constant cognitive demand to manage cross-linguistic competition enhances domain-general executive functions in bilinguals (Bialystok et al., 2008; Green & Abutalebi, 2013; Mishra, 2018), which can be repurposed in social domains to disengage individuals from these socialized defaults (S. X. Chen, 2015; Hu & Navarrete, 2024; Jankowiak et al., 2024; Liu et al., 2021). Passive CMS (i.e., avoiding and obliging) represent an evasion or “escape” orientation toward conflict (Dijkstra et al., 2009, 2011; Ohbuchi & Takahashi, 1994; Tidd & Friedman, 2002), thus bilingual women might be less adherent to passive CMS compared to monolingual women, for whom avoidance is often a socialized default (Bear et al., 2014; Holt & DeVore, 2005). As for men, bilingualism was found to enhance perspective-taking (Tarighat & Krott, 2021), suggesting bilingual men might be equipped with better social awareness and pragmatic skills required to engage in less aggressive CMS compared to monolingual men. Furthermore, operating across languages often creates psychological distance and reduces the emotional resonance (Ardila et al., 2017; Caldwell-Harris et al., 2011; Kazanas et al., 2019), this may allow bilinguals to better manage negative affect in conflict situations, approaching disputes with more rationality rather than defaulting to emotionally driven avoidance (Barragan Diaz et al., 2026). Ultimately, bilingualism may empower women to resist socialized compliance and equip men with the cognitive flexibility for more agreeable behaviors, convergently moderating the traditional gender gap in passive CMS.

In contrast to passive CMS, the lack of significant interaction between gender and bilingualism in active CMS could be explained by their different personal and motivational demands (Davis et al., 2023). While all active styles (i.e., dominating, integrating, and compromising) inherently require responsive and direct engagement as well as the proactive assertion of agentic goals (DeChurch & Marks, 2001; Dijkstra et al., 2009; Guerrero & Gross, 2014; Winer et al., 2024), they rely on different cognitive and emotional mechanisms. Both the integrating and compromising styles utilize the open exchange of information, elaboration, and mutual concessions to solve problems or reach a middle ground (Chua & Jin, 2020; Dijkstra et al., 2009). The dominating style operates independently of emotion regulation, as it is primarily driven by stable motivational traits, such as extraversion, narcissism, and the need for dominance, rendering it largely immune to emotional control capabilities (Antonioni, 1998; Davis et al., 2023; Rosequist & Kromka, 2024). Therefore, while the enhanced cognitive and emotional regulation afforded by bilingualism helps individuals suppress socialized passive defaults, it does not alter the underlying, stable personality traits that drive highly competitive, proactive behaviors. Because the gender gap in active styles is heavily anchored in these stable, agentic motivations rather than socio-cognitive flexibility, gender differences in active styles may persist equally among both bilinguals and monolinguals.

It is also important to acknowledge that no main overall effect of bilingualism was observed in this study, suggesting that bilingualism operates as a moderating boundary condition rather than a universal driver of CMS. Furthermore, while the univariate interaction for passive CMS was modest in magnitude, this is in line with previous literature stating that the main effects of biological sex on CMS tend to be small or inconsistent across the broader population (Holley et al., 2010; Holt & DeVore, 2005; Thomas et al., 2008). Given that effect sizes for linguistic variables in large-scale social surveys are typically modest (Luo & Wei, 2024; Shen & Wei, 2025) and that gender socialization and bilingualism are deeply entrenched lifelong processes (Bialystok, 2017; Piller & Pavlenko, 2006), the observation of even modest interaction effects on CMS can be contextually meaningful.

Implications and Limitations

The finding that bilingualism can moderate gender differences in passive CMS preferences offers several practical applications for modern, multilingual organizations. First, human resource practitioners could recognize bilingualism not only as a functional communicative asset but also as a potential managerial tool for optimizing organizational harmony. For instance, in environments where traditional gender roles may lead to suboptimal outcomes, such as women over-relying on passive behaviors to escape conflict, bilingual individuals may be better equipped to suppress these reflexive defaults and maintain the psychological distance necessary to navigate the dispute. Second, for organizational mediators and managers, understanding the linguistic background of disputants may provide deeper insight into their behavioral trajectories (Ivanova-Gongne et al., 2023). Because language experience influences how individuals monitor and resolve social conflicts, leadership development programs could benefit from incorporating language learning into their conflict resolution training. Rather than treating language simply as a mechanical barrier, organizations could view linguistic diversity as a resource that fosters more flexible, emotionally regulated, and less stereotyped interpersonal dynamics (Grant et al., 2023).

This study has several limitations that provide directions for future research. First, the data were derived from self-report measures in a cross-sectional survey rather than observations of actual conflict management behaviors. While cross-sectional data limits our ability to make definitive causal assertions (Dijkstra et al., 2011; Huang, 2010) and self-reports can be subject to common response biases (Paulhus, 1991; Podsakoff & Organ, 1986), they remain the standard for capturing behavioral preferences in conflict management research (Bechtoldt et al., 2010; Chung-Yan & Moeller, 2010), for an individual’s predisposition toward a conflict style often dictates the initial tone of an interaction (Dallinger & Hample, 1995; Thomas, 1992). Second, although we theorized cognitive control as the primary mechanism driving these effects, this study did not directly measure executive functions via performance-based tasks. Future studies could consider supplementing behavioral assessments of CMS with direct cognitive and/or affective measures in their design and analyses. Finally, the scope of this study was limited to a U.S.-based adult sample. Since bilingualism is multifaceted, factors such as age of acquisition, language dominance, and code-switching habits can lead to different cognitive and social adaptations (Takahesu Tabori et al., 2018), we should therefore be cautious in generalizing these patterns to populations where language and power are more rigidly stratified (see Bekerman & Horenczyk, 2004; Bekerman & Shhadi, 2003). Future research could examine whether these effects hold as a universal feature or localized outcomes.

Conclusion

In addition to confirming the role of gender in affecting CMS differences, this research identified bilingualism as a subtle but meaningful boundary condition for CMS differences. In particular, our results demonstrated that while active CMS exhibited traditional gendered patterns regardless of linguistic identity, a modest attenuation of the gender gap in passive CMS emerged among bilinguals. Conjointly, these findings suggest that bilingualism may act through a socio-cognitive mechanism favoring more equitable styles in dealing with interpersonal conflict. Finally, this study highlights the necessity of integrating linguistic identities into the broader discussions in communication and conflict management to better reflect the behavioral complexities of modern society and workforce.

Author Note

All data, analyses and supplemental materials are openly available on the Open Science Framework (OSF) at https://osf.io/5sq2x/?view_only=c74fa3d725284812bcdc665c0d23e67b

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