Worse for Women,Bad for All: A 62-Nation Study Confirms and Extends Ambivalent Sexism Principles to Reveal Greater Social Dysfunction in Sexist Nations

Abstract

We retested core ambivalent sexism theory tenets and explored novel correlations with national outcomes in 62 nations. Replicating Glick et al., cross-national analyses supported (a) hostile sexism (HS) and benevolent sexism (BS) as cross-culturally recognizable, complementary ideologies associated with gender inequality; (b) women appearing to be influenced by, but also resisting men’s HS and embracing BS to counter men’s HS (outscoring men in some highly sexist nations). Novel cross-national comparisons showed (a) men’s HS and both genders’ BS correlated with fewer women in paid work, whereas only BS correlated with domestic labor inequity, (b) both HS and BS correlated with accepting intimate partner violence toward women. Finally, HS and BS correlated with generally dysfunctional national outcomes: antidemocratic tendencies, less productivity, more collective violence, and lower healthy lifespan for both genders. Results reinforce that BS harms women and suggest men also have a stake in reducing sexist ideologies.

Keywords

ambivalent sexism hostile sexism benevolent sexism cross-cultural study attitudes to women

Ambivalent sexism theory (AST) contends that male dominance and heterosexual interdependence (both common across societies) create sexist ambivalence (Glick & Fiske, 1996). Male dominance fosters hostile sexism (HS), antagonism toward women exercising power. Heterosexual interdependence produces benevolent sexism (BS), a patronizing attitude idealizing women in traditional roles that support men. Despite their opposing affective tones, HS and BS represent complementary ideologies that reconcile men’s power with intimate dependence on women (Glick & Fiske, 1996, 2001). Specifically, AST views BS as crucial to gain women’s support for inequality by portraying women as benefiting from powerful men who protect and provide. AST’s core tenets were supported in cross-national research conducted 20 years ago in 19 nations (Glick et al., 2000). The current study tested (a) replication in contemporary, less WEIRD-dominated samples (Henrich et al., 2010) from 62 nations (preregistered at https://osf.io/wyrb3) and (b) whether HS and BS correlate with previously unexamined gender inequality indicators and diverse, dysfunctional national outcomes (economy, politics, violence, health) affecting both sexes.

Need for Replication

Cross-national research can uniquely test core AST tenets by examining both systemic and individual variation in sexism. Yet, large-scale cross-national research remains rare. Except for the work by Glick et al. (2000, 2004) and Zawisza et al. (2012, 2015), “most [ambivalent sexism] articles report samples collected in a single country, which prevents reliable cross-cultural comparisons” (Bareket & Fiske, 2023, p. 673). Replicating Glick et al.’s findings has particular urgency given changes in women’s roles and gender attitudes. A 57-nation comparison showed that hostile attitudes toward women in powerful roles (a proxy for HS) have decreased over time (Brandt, 2011). Correspondingly, gender inequality has also lessened across nations (Global Gender Gap Report, 2023), though not without backlash (e.g., Lobban et al., 2020; Valentino et al., 2018). Despite these changes, AST suggests that even if HS and BS endorsement has diminished over time, both ideologies should remain correlated with each other and with national gender inequality.

Furthermore, Glick et al.’s (2000) comparisons involved 19, mostly WEIRD nations (e.g., Western Europe, the United States, Australia; Henrich et al., 2010). The limited number and diversity of nations may have yielded spurious findings. Although Glick et al. (2004) replicated results in a 16-nation study, four samples were recycled from the work by Glick et al. (2000) and only six new nations were represented. The current 62-nation study provides increased statistical power and better represents global diversity by including more non-WEIRD societies. In addition, we used previously unavailable analyses to test psychometric isomorphism and conduct multilevel modeling, increasing reliability and validity, making the current study a robust, independent replication. The following sections present previously supported replication and novel hypotheses, labeled H_R and H_N, respectively.

Replication Hypotheses: Retesting Core AST Tenets

All replication hypotheses represent core AST principles supported in the work by Glick et al. (2000) (for brevity, we omit repeated citation below). AST views HS and BS as human universals because power difference and intimate interdependence characterize gender relations across nations. Therefore, H_R1: across nations, HS and BS constitute recognizable ideologies with similar factor structures. At the systemic level, AST characterizes BS as a necessary complement to HS. Specifically, BS legitimizes and preserves gender inequality, undermining women’s resistance by promising “benefits,” such as male protection and provision (Becker & Wright, 2011). Therefore, high HS cultures theoretically must promote BS to maintain systemic inequality, leading to H_R2: national HS and BS averages correlate positively and strongly, and H_R3: national HS and BS averages each correlate negatively with structural gender equality.

Because both ideologies justify male dominance, HS and BS also correlate positively at the individual level. However, while HS societies systemically require high BS to preserve inequality, individuals are freer to endorse each ideology to different degrees. Therefore, H_R4: among individuals within nations, HS and BS correlate positively but moderately. Furthermore, respondent gender and societal gender inequality should moderate how strongly HS and BS correlate. Whereas men directly benefit (gain power) from endorsing HS, women lose power by doing so. BS’s promised benefits (protection, provision) therefore become critical to leveraging HS endorsement among women (Sibley et al., 2007). Thus, H_R5a: HS and BS correlate more strongly for women than for men. Similarly, in gender-traditional nations, social norms permit individuals to openly express HS; by contrast, in more egalitarian nations where norms discourage overt HS, endorsing BS (which idealizes women) legitimizes expressing HS toward non-traditional women. Therefore, H_R5b: HS and BS correlate more strongly among individuals in relatively egalitarian versus sexist nations.

Theoretically, because HS and BS reinforce male dominance, these ideologies should have greater appeal to men. Therefore, H_R6: across nations, men endorse HS and BS more than women. However, dominant groups generally exert ideological influence over subordinated groups (Sidanius & Pratto, 2012) and AST posits that interdependence increases such influence in gender relations. Therefore, H_R7: across nations, the more men endorse HS or BS, the more women do as well (i.e., cross-nationally, women’s scores parallel men’s). However, AST proposes that women more readily accept BS’s “palliative” ideology (Kay & Jost, 2003), which offers positive stereotypes (e.g., warmth) and alleged benefits (e.g., male protection), compared with HS’s overt negativity. Therefore, H_R8: across nations, the HS gender gap (men’s minus women’s scores) exceeds the BS gender gap.

Indeed, exposing women to HS increases, whereas BS exposure reduces women’s resistance to inequality (Becker & Wright, 2011). Similarly, although women in highly sexist (versus more egalitarian) nations score higher on HS, they simultaneously show increased resistance to endorsing HS relative to men (i.e., the gender gap in HS endorsement increases in highly sexist countries). Therefore, H_R9: across nations, the more men endorse HS, the greater the HS gender gap (women scoring lower than men). Thus, for HS, we not only expect both ideological correspondence (women’s national HS averages parallel men’s) but also resistance (in nations where men strongly endorse HS, women show increasing distance from men).

BS shows a different dynamic, labeled the protection racket hypothesis. Across nations, Glick et al. (2000) found that as men’s HS increased, women more strongly embraced BS. Thus, the BS gender gap lessened and even reversed (women scoring higher on BS than men). AST suggests that men’s HS constitutes a perceived threat to women, who fear violence and punishment (e.g., withdrawn protection) from men. Thus, women in high HS environments endorse BS, which prescribes male protection to counter male threat. By contrast, women in low HS (i.e., lower threat) societies can more freely reject BS. Therefore, H_R10: across nations, as men’s HS endorsement increases, the BS gender gap shrinks or reverses (i.e., women endorse BS more than men). Figure 1 summarizes the hypotheses.

Figure 1

Graphic Summary of the Hypotheses and Theoretical Model

Novel Gender Inequality Hypotheses

We used previously unexamined national indices to test whether HS and BS correlate with factors that drive gender inequality: tolerating intimate partner violence and gendered divisions of labor.

Intimate Violence Against Women

Worldwide, almost one in three women experience physical or sexual violence, often from intimate partners, at least once (World Health Organization [WHO], 2021b). A meta-analysis found positive HS and BS correlations with attitudes supporting violence against women among both female and male respondents (Gutierrez & Leaper, 2024; see also Agadullina et al., 2022). Therefore, H_N1: across nations, HS and BS correlate with increased justification for intimate partner violence toward women.

Gendered Labor

Women’s lower participation in paid work and overrepresentation in unpaid domestic labor allow men to amass more resources and power, entrenching inequality (Wood & Eagly, 2012). Studies link HS to resisting women in male-dominated, higher-status jobs and BS with prescribing women to devote themselves to domestic roles (e.g., Gaunt, 2013). Within heterosexual couples, BS predicts traditional task divisions (Silván-Ferrero & Bustillos López, 2007) and women’s HS predicts maternal gatekeeping, diminishing fathers’ child care participation (Gaunt & Pinho, 2018). Therefore, across nations H_N2: HS and BS correlate with lower female participation in paid work, and H_N3:across nations, HS and BS correlate with a larger gender gap in unpaid domestic labor (women contributing more than men).

Novel Hypotheses About General Social Dysfunctions

Prior research suggests sexist attitudes correlate with varied social ills. We tested whether sexist societies fare worse on economic, political, social, and health indicators for both genders.

Economic Productivity

Sexism reduces human capital by restricting women’s education and job opportunities (Klasen, 2000), leading to lower economic productivity (e.g., Bertay et al., 2020). Therefore, as ideologies that support inequality, H_N4: across nations, HS and BS correlate with lower economic productivity.

Political Practices and Attitudes

Duckitt and Sibley (2017) have shown that antidemocratic, hierarchy-enhancing attitudes correlate with ambivalent sexism. Specifically, (a) social dominance orientation (Sidanius & Pratto, 2012), which views intergroup relations as a ruthless competition, correlates with HS; (b) right-wing authoritarianism, which favors tough leaders who enforce traditional gender roles, correlates with BS. Therefore, H_N5: across nations, HS and BS correlate with antidemocratic, hierarchy-enhancing political practices and attitudes.

Collective and Individual Violence

Men (compared with women) show greater propensity toward both collective and individual violence (United Nations, 2019). Male leaders typically initiate wars, and militaries remain male-dominated (Portillo et al., 2022). Interpersonal violence is disproportionately male: worldwide, men commit more than 90% of homicides (United Nations, 2019). Male violence correlates with sexist, masculine norms (Bosson & Vandello, 2011). Therefore, H_N6: across nations, HS and BS correlate with greater collective violence (H_N6a) and interpersonal violence (H_N6b).

Women’s and Men’s Health

Sexist ideologies can compromise both sexes’ health. For women, sexism promotes medical discrimination: women’s health issues receive less medical research (Mirin, 2021) and physicians find women’s medical complaints less credible, causing undertreatment (Braksmajer, 2018). For men, sexist attitudes prescribe denying physical or mental weakness, inhibiting help-seeking (Addis & Mahalik, 2003; Vandello et al., 2019). In addition, sexist norms promote risk-taking (e.g., avoiding seatbelts, aggression; Schrader & Wann, 1999), resulting in men dying younger in countries higher in precarious manhood beliefs (Vandello et al., 2023). Therefore, H_N7: across nations, HS and BS correlate with lower healthy lifespan for both sexes.

Method

Participants

After ethical approval in all nations, data for the current research (available at https://osf.io/fqd4p/) were collected between January 2018 and February 2020 as part of a larger Towards Gender Harmony project (https://towardsgenderharmony.ug.edu.pl/). The initial sample, N = 33,313 (already cleansed of those who failed control questions), was further winnowed, excluding respondents who did not complete all focal questions: Ambivalent Sexism Inventory (ASI), gender, and age. We obtained too few gender minority individuals for statistical tests; thus, we analyzed only male- or female-identifying participants, N = 29,518, mostly student volunteers. Target sample size was 200 per nation (50% women), reflecting good practice in multination studies (preregistration link https://osf.io/fqd4p/). Table 1 reports sample sizes, gender distribution, age, descriptive statistics, and omega coefficients for Confirmatory Factor Analysis (CFA)-standardized HS and BS scores.

Table 1

Sample Composition and Omega Coefficients ( $ω$ ) for HS and BS Measures by Country.

Country	N	% Male/female	Age (years)		HS (CFA standardized scores)					BS (CFA standardized scores)
Country	N	% Male/female	M	SD	M	SD	M weight	SD weight	$ω$	M	SD	M weight	SD weight	$ω$
Albania	227	38/62	23.09	4.96	0.72	0.99	0.80	1.00	.74	0.78	0.90	0.80	0.91	.46
Argentina	354	47/53	32.53	12.29	−0.26	1.01	−0.25	1.01	.76	−0.41	1.05	−0.40	1.05	.60
Armenia	204	58/42	19.98	1.84	0.80	0.88	0.77	0.88	.63	1.06	0.84	1.03	0.85	.61
Australia	629	34/66	29.93	11.23	−0.24	0.79	−0.19	0.80	.80	−0.35	0.78	−0.30	0.79	.53
Belgium	1,809	48/52	21.59	6.12	−0.23	0.77	−0.22	0.77	.72	−0.12	0.89	−0.11	0.89	.60
Bosnia	187	47/53	23.03	6.04	0.96	0.90	0.98	0.90	.68	1.17	0.78	1.17	0.77	.61
Brazil	1,024	32/68	23.89	7.53	−0.40	0.87	−0.33	0.90	.72	−0.35	1.04	−0.26	1.06	.58
Canada	887	31/69	19.88	3.28	−0.31	0.76	−0.23	0.78	.71	−0.31	0.83	−0.21	0.84	.56
Chile	132	42/58	21.83	5.23	−0.21	0.87	−0.18	0.88	.72	−0.25	0.98	−0.24	0.98	.59
China	187	40/60	19.35	1.25	−0.12	0.59	−0.09	0.60	.71	−0.31	0.57	−0.30	0.58	.44
Columbia	559	40/60	21.48	4.83	−0.13	0.91	−0.06	0.93	.76	−0.19	1.02	−0.11	1.03	.62
Croatia	312	22/78	23.21	5.86	0.16	0.96	0.30	0.98	.77	0.41	0.92	0.54	0.91	.58
Czechia	386	74/26	28.11	8.61	0.30	0.84	0.23	0.86	.75	0.51	0.85	0.45	0.88	.64
Denmark	246	39/61	25.44	4.78	−0.15	0.87	−0.06	0.87	.79	−0.54	0.84	−0.45	0.84	.53
England	709	40/60	22.34	7.63	−0.19	0.86	−0.15	0.87	.79	−0.34	0.93	−0.30	0.94	.64
Finland	284	12/88	26.19	7.26	−0.75	0.69	−0.41	0.93	.80	−1.04	0.71	−0.76	0.90	.58
France	399	18/82	22.22	6.68	−0.52	0.77	−0.43	0.77	.74	−0.39	0.97	−0.32	0.96	.66
Georgia	170	49/51	21.85	3.55	0.34	0.87	0.34	0.87	.55	0.37	0.94	0.37	0.94	.58
Germany	1,281	35/65	29.88	10.49	−0.26	0.84	−0.22	0.85	.79	−0.46	0.87	−0.41	0.87	.61
Ghana	292	39/61	20.21	2.58	1.08	0.98	1.13	0.97	.70	1.28	0.74	1.28	0.74	.46
Greece	269	27/73	26.41	8.96	−0.05	0.81	0.07	0.83	.71	0.00	0.91	0.08	0.92	.61
Hungary	681	19/81	22.35	4.30	0.04	0.82	0.14	0.81	.72	0.21	0.91	0.28	0.90	.65
India	288	39/61	21.89	5.46	0.27	0.76	0.34	0.77	.67	0.41	0.87	0.48	0.86	.61
Indonesia	217	47/53	21.02	3.96	0.85	0.76	0.86	0.76	.61	0.57	0.85	0.54	0.85	.77
Iran	157	39/61	29.23	8.24	0.40	0.88	0.49	0.89	.74	0.79	0.65	0.81	0.66	.53
Ireland	554	46/64	19.84	3.71	0.14	0.94	0.16	0.94	.79	−0.07	0.93	−0.05	0.93	.55
Italy	2,311	34/66	22.84	5.32	−0.27	0.87	−0.19	0.88	.75	−0.24	1.01	−0.17	1.01	.69
Japan	201	41/59	21.66	3.72	0.08	0.73	0.10	0.72	.65	0.05	0.80	0.08	0.79	.61
Kazakhstan	329	43/57	20.18	3.84	0.72	0.89	0.75	0.89	.66	0.92	0.84	0.92	0.83	.58
Kosovo	394	40/60	20.25	3.86	0.23	1.04	0.31	1.04	.76	0.32	1.06	0.39	1.06	.63
Lebanon	119	31/69	19.61	0.87	0.17	0.88	0.29	0.87	.70	0.16	0.97	0.29	0.94	.57
Lithuania	296	32/68	23.96	6.80	0.42	0.96	0.53	0.94	.77	0.43	0.91	0.50	0.86	.57
Luxembourg	174	35/65	24.56	5.32	−0.43	0.67	−0.37	0.70	.73	−0.46	0.75	−0.39	0.76	.68
Malta	243	35/65	27.01	10.13	0.00	0.91	0.09	0.94	.74	−0.09	0.96	−0.01	1.00	.64
Mexico	287	47/53	23.80	9.05	0.13	0.99	0.15	1.00	.75	0.09	1.05	0.11	1.05	.61
Morocco	265	46/54	28.99	9.67	0.49	0.93	0.52	0.93	.76	0.48	0.79	0.48	0.78	.60
Nepal	200	37/63	22.40	5.51	0.41	0.81	0.47	0.80	.61	0.47	0.83	0.51	0.83	.51
Netherlands	869	33/67	20.65	3.43	−0.14	0.73	−0.07	0.76	.69	−0.15	0.81	−0.08	0.82	.53
New Zealand	214	29/71	19.01	2.34	−0.31	0.75	−0.24	0.76	.81	−0.26	0.78	−0.18	0.79	.54
Nigeria	401	44/56	21.16	3.22	1.31	0.94	1.33	0.93	.54	1.50	0.71	1.51	0.71	.57
Northern Ireland	293	39/61	22.10	5.58	−0.29	0.90	−0.24	0.91	.83	−0.44	0.93	−0.39	0.95	.60
Norway	195	45/55	22.98	3.82	−0.37	0.76	−0.35	0.76	.74	−0.81	0.73	−0.80	0.73	.55
Pakistan	398	44/56	22.07	3.74	0.87	0.81	0.87	0.80	.64	0.91	0.81	0.90	0.80	.59
Philippines	435	50/50	19.81	2.06	0.01	0.91	0.01	0.91	.77	0.06	0.94	0.06	0.94	.56
Poland	736	44/56	22.99	4.71	0.38	0.92	0.42	0.91	.72	0.29	0.90	0.31	0.89	.63
Portugal	169	18/82	22.17	4.94	−0.42	0.65	−0.38	0.69	.56	−0.18	0.90	−0.13	0.98	.54
Romania	241	42/58	22.84	4.65	0.69	0.93	0.71	0.93	.74	0.61	0.96	0.62	0.95	.62
Russia	646	32/68	21.94	7.00	0.23	0.04	0.33	1.05	.79	0.10	1.03	0.12	1.02	.64
Serbia	646	24/76	22.26	5.35	0.34	0.97	0.41	0.94	.72	0.64	0.83	0.67	0.79	.56
Slovak Republic	552	47/53	21.93	4.50	0.51	0.89	0.52	0.89	.69	0.46	0.93	0.46	0.93	.58
South Africa	365	41/59	20.56	2.69	0.55	0.82	0.60	0.81	.67	0.72	0.83	0.75	0.82	.59
Spain	1,100	37/63	25.65	8.74	−0.72	0.76	−0.65	0.80	.78	−0.89	0.86	−0.83	0.88	.58
Suriname	172	46/54	22.95	5.66	0.53	0.89	0.55	0.89	.68	0.60	0.91	0.61	0.91	.62
Sweden	627	49/51	26.37	7.49	−0.53	0.84	−0.53	0.84	.81	−0.80	0.88	−0.79	0.88	.55
Switzerland	545	35/65	23.49	5.31	−0.33	0.81	−0.30	0.82	.75	−0.32	0.92	−0.28	0.93	.59
Turkey	1,397	32/68	22.28	4.08	0.03	0.97	0.15	0.99	.75	0.10	1.07	0.19	1.06	.62
UEA	496	34/66	20.01	1.47	0.28	0.88	0.35	0.89	.70	0.39	0.91	0.47	0.91	.53
Ukraine	262	34/66	19.13	1.44	0.44	0.98	0.55	0.99	.72	0.54	0.99	0.60	0.97	.69
Uruguay	183	38/62	22.69	6.59	−0.36	0.83	−0.31	0.83	.73	−0.35	0.95	−0.30	0.95	.60
United States	744	31/69	20.29	4.32	−0.04	0.88	0.02	0.87	.75	−0.09	0.96	0.02	0.97	.64
Vietnam	372	27/73	22.47	6.84	0.61	0.86	0.68	0.86	.64	0.76	0.84	0.79	0.84	.49
Wales	197	35/65	30.47	10.36	−0.38	0.94	−0.29	0.95	.83	−0.55	0.93	−0.46	0.93	.67
Total	29,518	37/63	23.11	6.91	0.00	0.96	0.06	0.97	.77	0.00	1.04	0.05	1.04	.63

Note: M = Male, F = Female. To correct for differing gender ratios, we calculated Weighted Means (M weight) and Standard Deviations (SD weight) within each nation to provide equal gender representation in standardized HS and BS scores.

Procedure

Participants completed a six-item ASI using a 0 (strongly disagree) to 5 (strongly agree) scale. We selected three BS and three HS items based on prior high-factor loadings (Rollero et al., 2014) to represent BS’s three subfactors and to cover HS’s varied themes. Back-translation (English to target language and back, van de Vijver & Leung, 2021) resulted in 29 language versions, see https://osf.io/fqd4p/. Items included: “Women should be cherished and protected by men” (BS) and “Women seek to gain power by getting control over men” (HS). See Table S2 in Supplementary Materials for all items. We computed standardized HS and BS scores using CFA.

We selected indices assessing national outcomes based on geographic and temporal correspondence with our dataset. The Global Gender Gap Index (GGGI, World Economic Forum, 2020) assesses gender inequality (economic, educational, health, and political power), ranging from 0 (extreme disadvantage for women) to 1 (gender parity). The Violence Against Women Index (Organization for Economic Cooperation and Development [OECD], 2019) assesses percentage of women agreeing that male violence toward female partners is sometimes justified). Women’s Labor Force Participation (World Bank, 2019) assesses percentage of women (15 years and older) participating in paid work. The Unpaid Work Gap (OECD, 2019) measures women’s minus men’s time (minutes/week) performing unpaid domestic labor, assessing inequality at home.

Six national indicators assessed social dysfunctions affecting both sexes. Gross Domestic Product (GDP, World Bank, 2019) measures economic productivity (market value of all goods and services). The Democracy Index (Economist Intelligence Unit, 2019) assesses democratic governance (electoral process, government functioning, participation, political culture, civil liberties); score range: 0 (undemocratic) to 10 (democratic). The Power Distance Index (PDI , Hofstede et al., 2010) assesses cultural acceptance of hierarchical authority and power disparity; score range: 0 (low) to 100 (high). The Global Peace Index (GPI , Institute for Economics and Peace, 2019) assesses collective violence, combining 23 qualitative and quantitative indicators in three domains (safety and security, domestic and international conflict, militarization); score range: 1 (more peaceful) to 5 (less peaceful). Estimated Murder Rates (United Nations Office on Drugs and Crime [UNDOC], 2019) assesses homicides per 100,000 population, disaggregated by gender. Healthy Life Expectancy for Women and Men (WHO, 2021a) estimates years women and men live without chronic disease or disability using morbidity and mortality data.¹

Transparency and Openness

All data and materials are available at https://osf.io/fqd4p/ and R code on request. The project, hypotheses, design, and analyses were preregistered https://osf.io/wyrb3 (see Supplementary Materials for exceptions).

Results

Analytical Strategy

To maintain consistency with the work by Glick et al. (2000), replication hypotheses about national-level variation (H_R2, H_R3, H_R4, H_R7, H_R9, H_R10) and simple gender differences (H_R6 and H_R8) were tested using correlations and paired t-tests, respectively. However, to enhance rigor, we tested hypotheses involving both individual and systemic variance using multilevel analyses: multilevel CFA tested whether ASI items had consistent factor loadings across individuals and countries (H_R1). Multilevel modeling (Heck & Thomas, 2020) tested hypotheses about whether gender and national gender parity (GGGI) moderate within-nation HS and BS correlations (H_R5a, H_R5a). Linear regressions tested novel hypotheses about gender inequality and social dysfunctions (H_N1–H_N7). Table 8 indicates analyses used for each hypothesis.

Replication Analyses

Are HS and BS Universally Recognizable?

We tested H_R1 (HS and BS as universally recognizable ideologies) using CFA (Figure 2). Tay et al.’s (2014) simultaneous estimation method tested psychometric isomorphism (Fontaine, 2008; van de Vijver & Watkins, 2006), assessing whether items have similar conceptual meaning across individuals and nations in two ways: configural isomorphism (similar factors and item loadings) and metric isomorphism (consistent factor loadings). Results supported H_R1. Table 2 reveals excellent fit indices (CFI > .95, RMSEA; SRMR < .080; see Brown, 2015) for a two-factor ASI structure across the entire sample (Model 1). Models 2 and 3 demonstrated configural and metric isomorphism.²

Figure 2

Multilevel CFA Results (Standardized Coefficients)

Table 2

Multilevel Confirmatory Factor Analysis for the Short ASI

Model	Fit statistics
Model	SABIC	CFI	RMSEA	SRMR_W	SRMR_B
Single-level structure (Model 1)	634,456	.996	.025	.011	–
Configural isomorphism (Model 2)	619,560	.996	.016	.010	.024
Metric isomorphism: all loadings constrained to be equal across levels (Model 3)	619,546	.996	.015	.010	.042

Note. N = 29,518 from 62 countries; SABIC = Sample-size Adjusted Bayesian Information Criterion; CFI = Comparative Fit Index; RMSEA = Root Mean Square Error of Approximation; SRMR_W = Standardized Root Mean Square Residual Within Covariance Matrix; SRMR_B = Standardized Root Mean Square Residual Between Covariance Matrix.

Omega (ω) coefficients ranged between .54 and .83 for HS (.77 for entire sample) and .44 and 0.77 for BS (.63 for entire sample) indicating acceptable reliability for three-item scales in most countries (see Table 1). However, for HS (three nations) and BS (30 nations), $ω$ was less than .60 (lower than recommended even for short scales; Graham, 2006, in italics in Table 1), increasing risk for attenuated correlations and warranting caution when interpreting analyses for BS.³ In sum, CFA supported H_R1 that HS and BS constitute recognizable, conceptually related ideologies across nations, despite less-than-ideal reliability for the multidimensional BS scale.

HS and BS as Complementary Justifications for Inequality

Supporting H_R2 (HS and BS as systemically complementary), national HS and BS averages correlated strongly and positively: r(60) = .92 (p <. 01) for women; r(60) = .74 for men (p < .01). Supporting H_R3 (HS and BS justify inequality), men’s and women’s cross-national HS and BS averages correlated negatively with gender equality (GGGI, see Table 3). Supporting H_R4 (individual-level complementarity), within-nations, HS–BS correlations were usually moderately positive, attaining significance in 53/62 countries for men and 59/62 countries for women (see Table 4).

Table 3

Coefficients of Linear Regression Models Testing Relationships Between Country-Level BS and HS With Country’s Gender Inequality

Predictor	Women			Men			All
Predictor	B	SE	Beta	B	SE	Beta	B	SE	Beta
Model 1 for GGGI (N = 62)
BS	−.05	< .01	−.59**	−.06	.01	−.53**	−.05	< .01	−.59**
Model 2 for GGGI (N = 62)
HS	−.06	< .01	−.54**	−.05	.01	−.49**	−.05	.01	−.52**

Table 4

Correlations Between HS and BS Among Women and Men in Different Nations

Nation	Six-item ASI
Nation	Women’s r	Men’s r	z
Albania	.34**	.35**	−.03
Argentina	.46**	.36**	1.18
Armenia	.22*	.22*	.02
Australia	.44**	.26**	2.43**
Belgium	.39**	.23**	3.76**
Bosnia	.40**	.15	1.79*
Brazil	.48**	.51**	−.73
Canada	.42**	.33**	1.50
Chile	.54**	.34*	1.36
China	.44**	.39**	.39
Columbia	.32**	.38**	−.77
Croatia	.43**	.46**	−.31
Czechia	.38**	.18**	1.90*
Denmark	.34**	.49**	−1.39
England	.49**	.35**	2.28**
Finland	.31**	.48**	−1.09
France	.40**	.45**	−.44
Georgia	.30**	.26*	.23
Germany	.49**	.38**	2.43**
Ghana	.14	.34*	−1.74*
Greece	.30**	.34**	−.29
Hungary	.37**	.19*	2.00*
India	.40**	.24*	1.46
Indonesia	.20*	.45**	−1.98*
Iran	.04	−.06	.59
Ireland	.43**	.28**	1.99*
Italy	.48**	.36**	3.19**
Japan	.43**	.00	3.16**
Kazakhstan	.29**	.12	1.57
Kosovo	.38**	.35*	.32
Lebanon	.44**	.02	2.24**
Lithuania	.48**	.11	3.21**
Luxembourg	.45**	.33*	.87
Malta	.27**	.34**	−.51
Mexico	.44**	.44**	−.06
Morocco	−.32**	.10	−3.43**
Nepal	.14	.15	−.12
Netherlands	.43**	.35**	1.33
New Zealand	.42**	.29*	.95
Nigeria	.17**	.35**	−1.89*
Northern Ireland	.36**	.42**	−.54
Norway	.27**	.50**	−1.85*
Pakistan	.30**	.15*	1.53
Philippines	.39**	.45**	−.75
Poland	.52**	.30**	3.62**
Portugal	.39**	.60**	−1.36
Romania	.44**	.39**	.51
Russia	.44**	.28**	2.11*
Serbia	.40**	.22**	2.20**
Slovak Republic	.37**	.23**	1.81*
South Africa	.35**	.17*	1.77*
Spain	.44**	.43**	.22
Suriname	.33**	.33**	.01
Sweden	.51**	.43**	1.29
Switzerland	.35**	.40**	−.69
Turkey	.38**	.27**	2.29**
UEA	.34**	.37**	−.40
Ukraine	.40**	.39**	.13
Uruguay	.44**	.49**	−.45
United States	.43**	.51**	−1.25
Vietnam	.36**	.26**	.87
Wales	.53**	.17	2.68**

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

Are HS–BS Correlations Higher for Women and People in Egalitarian Nations?

H_R5 predicted stronger HS and BS correlations among women versus men (H_R5a) and in more egalitarian versus sexist nations (H_R5b). Multilevel regression predicting HS from BS, with participant gender (Model 1) and national egalitarianism (GGGI; Model 2) as moderators (see Table 5) did not support H_R5a: participant gender did not interact with BS in predicting HS but supported H_R5b with a significant BS × GGGI interaction indicating stronger HS–BS correlations in nations with greater gender parity. Note that both these Hs were supported when using Glick et al.’s (2000) correlational approach on our data.

Table 5

Multilevel Regression Results for Predicting HS From BS With Gender and GGGI as Moderators

Predictor	Model 1		Model 2
Predictor	Estimate	SE	Estimate	SE
Intercept	2.11**	0.14	13.53**	1.71
Benevolent sexism	0.35**	0.01	−0.29**	0.07
Gender (male)	1.57**	0.09	–	–
Level of egalitarianism in a country (GGGI)	–	–	−15.11**	2.35
BS × gender	< −0.01	0.01	–	–
BS × GGGI	–	–	0.91**	0.10
Residual	10.11		10.62
Country	1.08		0.97
df	6		6
AIC	152,313		153,749
−2 log likelihood	152,302		153,737

Note. The BS main effect reflects support for HR₁ (HS and BS as complementary, correlated ideologies) and the participant gender’s main effect reflects support for HR₆ (men endorse sexism more than women).

Ideological Influence and Resistance

Supporting H_R6 (men support hierarchy-justifying gender ideologies more than women), averaging across nations, men scored higher on both HS (M = 2.20, SD = 0.59) and BS (M = 2.71, SD = 0.54) than women (M = 1.58, SD = 0.54 and M = 2.53, SD = 0.72 respectively); paired t(61) = 18.59, p < .001, d = 2.36 for HS and t(61) = 3.80, p <.001, d = 0.48 for BS. However, consistent with H_R7, (men’s ideological positions are related to women’s attitudes), cross-nationally women’s and men’s HS scores correlated at r(60) = .90, p < .01, and women’s and men’s BS correlated at r(60) = .85, p < .01. Supporting H_R8 (women prefer BS’s palliative ideology more than HS), we found a significantly larger gender difference in HS (M = 0.61, SD = 0.26) than in BS (M = 0.18, SD = 0.38) scores, paired t(61) = 7.12, p < .001, d = 0.9. See Table 6 for national HS and BS means.

Table 6

Means and Standard Deviations for HS and BS by Gender and Nation

Country	HS female (SD)	HS male (SD)	BS female (SD)	BS male (SD)	n (Female, Male)
Albania	2.21 (1.24)	3.15 (1.34)	3.57 (1.06)	3.24 (1.16)	141, 91
Argentina	1.21 (1.32)	1.73 (1.4)	1.78 (1.2)	2.29 (1.36)	214, 202
Armenia	2.37 (1.23)	2.81 (1.25)	3.65 (1.17)	3.73 (1.08)	93, 128
Australia	1.24 (1.02)	1.67 (1.15)	1.9 (0.98)	2.12 (1.01)	424, 229
Belgium	1.13 (0.93)	1.6 (1.08)	2.25 (1.16)	2.54 (1.16)	982, 906
Bosnia	2.51 (1.32)	3.06 (1.17)	3.66 (1.05)	3.63 (0.91)	100, 97
Brazil	1.02 (1.06)	1.51 (1.25)	2.09 (1.24)	2.55 (1.29)	726, 347
Canada	1.14 (0.94)	1.61 (1.13)	1.91 (1.01)	2.42 (1.11)	627, 283
Chile	1.15 (1.1)	1.62 (1.31)	1.89 (1.28)	2.04 (1.33)	148, 80
China	1.4 (0.7)	1.81 (0.87)	1.98 (0.7)	2.16 (0.75)	382, 205
Columbia	1.17 (1.08)	2.09 (1.22)	2.03 (1.26)	2.67 (1.3)	348, 228
Croatia	1.65 (1.26)	2.36 (1.32)	2.98 (1.14)	3.28 (1.04)	248, 72
Czechia	1.72 (1.21)	2.05 (1.13)	2.86 (1.19)	3.03 (1.11)	104, 295
Denmark	1.16 (1.1)	2.22 (0.99)	1.44 (0.98)	2.26 (0.96)	153, 100
England	1.31 (1.09)	1.73 (1.22)	1.89 (1.13)	2.24 (1.21)	438, 294
Finland	0.67 (0.75)	1.83 (1.38)	1.24 (0.91)	1.97 (1.25)	257, 35
France	0.91 (1.01)	1.32 (1.0)	2.1 (1.3)	2.25 (1.23)	342, 75
Georgia	1.84 (1.14)	2.36 (1.21)	2.72 (1.4)	2.75 (1.15)	95, 99
Germany	1.27 (1.06)	1.64 (1.18)	1.77 (1.12)	2.1 (1.1)	868, 497
Ghana	2.66 (1.43)	3.34 (1.26)	4.03 (0.99)	3.66 (0.93)	196, 124
Greece	1.44 (1.03)	2.13 (1.14)	2.39 (1.2)	2.58 (1.16)	205, 79
Hungary	1.57 (1.13)	2.04 (1.06)	2.72 (1.22)	2.75 (1.25)	566, 133
India	1.67 (0.91)	2.48 (0.95)	2.9 (1.05)	3.42 (0.96)	225, 143
Indonesia	2.28 (1.03)	3.49 (0.89)	3.73 (1.07)	1.99 (0.72)	115, 102
Iran	1.55 (1.09)	2.91 (1.19)	3.35 (0.82)	3.16 (1.01)	102, 72
Ireland	1.5 (1.13)	2.39 (1.25)	2.05 (1.13)	2.52 (1.12)	301, 261
Italy	1.08 (1.04)	1.77 (1.2)	2.18 (1.31)	2.57 (1.26)	1,589, 817
Japan	1.64 (0.99)	1.98 (0.96)	2.46 (1.01)	2.71 (1.07)	122, 84
Kazakhstan	2.26 (1.27)	2.84 (1.17)	3.54 (1.1)	3.2 (1.07)	189, 147
Kosovo	1.49 (1.23)	2.62 (1.35)	2.82 (1.35)	3.31 (1.2)	247, 165
Lebanon	1.66 (1.15)	2.41 (1.1)	2.45 (1.26)	3.11 (1.02)	89, 37
Lithuania	1.94 (1.3)	2.8 (1.18)	2.84 (1.22)	3.08 (0.92)	211, 103
Luxembourg	0.98 (0.75)	1.44 (1.02)	1.71 (0.88)	2.22 (1.03)	113, 61
Malta	1.41 (1.1)	2.21 (1.32)	2.2 (1.16)	2.51 (1.41)	167, 91
Mexico	1.43 (1.14)	2.35 (1.36)	2.36 (1.25)	2.98 (1.25)	178, 157
Morocco	1.92 (1.4)	2.75 (1.21)	3.05 (1.33)	2.65 (0.97)	157, 135
Nepal	1.94 (1.12)	2.52 (1.03)	2.96 (1.08)	3.18 (1.04)	133, 80
Netherlands	1.35 (0.88)	1.82 (1.1)	2.23 (0.99)	2.52 (1.06)	596, 292
New Zealand	1.12 (0.97)	1.55 (1.05)	2.03 (0.99)	2.46 (1.04)	152, 63
Nigeria	2.99 (1.35)	3.52 (1.23)	4.17 (0.97)	3.94 (0.88)	252, 191
Northern Ireland	1.15 (1.18)	1.7 (1.23)	1.77 (1.13)	2.14 (1.24)	187, 117
Norway	1.19 (1.04)	1.5 (1.04)	1.31 (0.97)	1.6 (0.94)	112, 90
Pakistan	2.52 (1.25)	2.81 (1.09)	3.5 (1.11)	3.19 (1.03)	284, 247
Philippines	1.49 (1.15)	1.87 (1.26)	2.45 (1.17)	2.69 (1.15)	229, 223
Poland	1.86 (1.21)	2.57 (1.16)	2.6 (1.17)	2.89 (1.01)	416, 324
Portugal	1.06 (0.81)	1.23 (0.96)	2.47 (1.12)	2.5 (1.37)	139, 32
Romania	2.39 (1.27)	2.76 (1.28)	3.17 (1.25)	3.07 (1.11)	148, 104
Russia	1.69 (1.3)	2.6 (1.43)	2.38 (1.33)	2.18 (1.22)	448, 219
Serbia	1.92 (1.37)	2.34 (1.23)	3.13 (1.14)	2.98 (0.92)	527, 162
Slovak Republic	2.12 (1.19)	2.57 (1.23)	3.04 (1.19)	2.89 (1.19)	300, 284
South Africa	2.03 (1.11)	2.8 (0.98)	3.21 (1.12)	3.44 (0.99)	227, 159
Spain	0.57 (0.8)	1.25 (1.16)	1.42 (1.06)	1.8 (1.15)	730, 427
Suriname	2.1 (1.19)	2.66 (1.16)	3.19 (1.25)	3.08 (1.14)	98, 82
Sweden	0.82 (0.98)	1.39 (1.2)	1.36 (1.15)	1.54 (1.1)	342, 325
Switzerland	1.2 (1.05)	1.42 (1.13)	1.97 (1.23)	2.31 (1.17)	375, 207
Turkey	1.43 (1.19)	2.31 (1.35)	2.53 (1.39)	2.78 (1.32)	982, 469
UEA	1.76 (1.12)	2.38 (1.21)	2.86 (1.14)	3.19 (1.04)	344, 177
United States	1.5 (1.17)	1.9 (1.11)	2.23 (1.2)	2.58 (1.23)	533, 239
Ukraine	1.87 (1.22)	2.88 (1.25)	3.02 (1.29)	3.15 (1.12)	180, 98
Uruguay	1.02 (1.04)	1.53 (1.13)	2.05 (1.21)	2.47 (1.16)	116, 73
Vietnam	2.27 (1.2)	2.68 (1.15)	3.38 (1.07)	3.4 (1.06)	288, 103
Wales	0.99 (1.19)	1.67 (1.3)	1.47 (1.11)	2.14 (1.21)	132, 74

Supporting H_R9 (the more men endorse HS, the more women, relative to men, resist HS), men’s national HS scores correlated with an increased HS gender gap (men’s minus women’s scores), r(60) = .47, p < .01. By contrast, men’s average BS scores did not correlate with the HS gender gap, r(60) = .18, ns. Results supported the protection racket hypothesis, H_R10 (women counter men’s HS through increased BS). Cross-nationally, as men’s HS increased, the BS gender gap shrank, r(60) = −.57, p < .01 or reversed. Women score significantly higher than men on BS in seven nations (6/7 in the top 10 for men’s HS). See Figures 3 and 4. By contrast, men’s average BS scores did not correlate with the BS gender gap, r(60) = −.18, ns. In sum, correlational analyses supported all system justification hypotheses.

Figure 3

Mean HS Scores for 62 Countries Divided by Gender and Ordered by Men’s HS Scores

Figure 4

Mean BS Scores for 62 Countries Divided by Gender and Ordered by Men’s BS Scores

Novel Hypotheses

Gender Inequality

See Table 7 for the outcomes of relevant regression. Supporting H_N1, as HS and BS increased across nations, so did justifying violence toward women. Partially supporting H_N2, the higher both men’s HS and BS, and women’s BS (but not HS), the less women participated in paid work. Partially supporting H_N3, across nations, women’s and men’s BS, but not HS, predicted a larger gap in women’s versus men’s contribution to domestic labor.

Table 7

Coefficients of Linear Regression Models Testing Relationships Between Country-Level BS and HS with Other Indicators at the National Level

DV	Predictor	Female			Male			Overall^a
DV	Predictor	B	SE	Beta	B	SE	Beta	B	SE	Beta
Violence against women index (N = 55)	BS	7.23	2.78	.34*	8.20	3.79	.28*	8.35	3.32	.33*
Violence against women index (N = 55)	HS	10.43	3.69	.36**	8.24	3.32	.32*	9.69	3.57	.35**
Unpaid work gap (N = 26)	BS	73.58	18.63	.63**	82.31	20.28	.64**	80.70	19.50	.64**
Unpaid work gap (N = 26)	HS	63.69	31.59	.38	46.35	24.71	.36	58.27	28.70	.38
Labor force participation (N = 61)	BS	−4.80	1.94	−.31*	−7.02	2.56	−.34**	−6.15	2.28	−.33**
Labor force participation (N = 61)	HS	−4.44	2.71	−.21	−5.75	2.34	−.30*	−5.44	2.57	−.27*
Gross domestic product (N = 43)	BS	−21,857	4,857	−.58**	−21,852	7,075	−.43**	−25,469	6,032	−.55**
Gross domestic product (N = 43)	HS	−24,247	7,365	−.46**	−20,619	5,759	−.49**	−23,682	6,602	−.49**
EIU democracy score (N = 61)	BS	−1.77	.27	−.65**	−2.11	.39	−.58**	−2.08	0.32	−.64**
EIU democracy score (N = 61)	HS	−2.25	.39	−.60**	−2.05	.34	−.62**	−2.25	0.36	−.63**
Power difference index (N = 61)	BS	19.78	2.79	.68**	21.97	4.20	.56**	22.61	3.41	.65**
Power difference index (N = 61)	HS	23.71	4.16	.60**	19.77	3.80	.56**	22.62	4.01	.59**
Global peace index (N = 59)	BS	0.21	0.08	.33*	0.31	0.10	.37**	0.28	0.09	.36**
Global peace index (N = 59)	HS	0.27	0.11	.31*	0.31	0.09	.40**	0.31	0.10	.37**
Murder rate men (log) (N = 49)	BS	0.32	0.31	.15	0.60	0.37	.23	0.46	0.34	.19
Murder rate men (log) (N = 49)	HS	0.27	0.42	.09	0.52	0.35	.21	0.44	0.40	.16
Murder rate women (log) (N = 50)	BS	0.09	0.19	.07	0.25	0.22	.16	0.16	0.21	.11
Murder rate women (log) (N = 50)	HS	0.07	0.25	.04	0.22	0.21	.14	0.16	0.24	.10
Women’s healthy life expectancy (N = 57)	BS	−5.17	0.69	−.71**	−6.06	1.02	−.63**	−6.05	0.83	−.70**
Women’s healthy life expectancy (N = 57)	HS	−6.92	0.96	−.70**	−6.30	0.85	−.71**	−6.92	0.90	−.72**
Men’s healthy life expectancy (N = 58)	BS	−5.47	0.66	−.74**	−6.60	0.97	−.67**	−6.47	0.79	−.74**
Men’s healthy life expectancy (N = 58)	HS	−7.37	0.91	−.73**	−6.69	0.81	−.74**	−7.35	0.85	−.76**

Note. See Table S4 in Supplementary Materials list countries where DVs were not available.

To ensure equal gender representation across samples, we computed weighted means to estimate overall country-level HS and BS; each row presents results for models with either BS or HS as a single predictor due to high correlations between HS and BS.

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

Novel Hypotheses About Social Dysfunctions

See Table 7. Regressions supported most hypotheses about ambivalent sexism’s relation to social dysfunctions affecting both sexes. Across nations, higher HS and BS (for each gender) correlated with: (H_N4) lower economic productivity (GDP), (H_N5) lower democracy and higher power distance scores, (H_N6a) higher collective conflict (Global Peace Index), and (H_N7), lower healthy life expectancy for both sexes. However, disconfirming H_N6b, HS and BS did not correlate with murder rates.

Discussion

This 62-nation study replicated core AST principles supported by in the work by Glick et al. (2000, 2004) and revealed novel correlations between ambivalent sexism and social dysfunctions affecting both sexes; see Table 8 for summary. Although consistent with AST’s causal hypotheses, our correlational analyses do not permit causal conclusions. AST posits that BS (rooted in heterosexual interdependence) represents a cross-culturally universal complement to HS (rooted in male dominance), legitimizing both HS and gender inequality. National-level analyses supported sexist ambivalence’s cross-cultural ubiquity, that BS and HS go hand-in-hand and each correlate with structural gender inequality. Individual-level analyses also supported HS and BS as complementary, especially in more egalitarian nations (where HS may be less socially acceptable without BS).

Table 8

Summary of Support for Hypotheses

Replication hypotheses (and test used):	Outcome
H_R1: Across nations, HS and BS are distinct yet correlated factors (CFA and multilevel CFA testing isomorphism)	Supported
H_R2: Across nations, national HS and BS are strongly correlated (multilevel CFA and correlation analysis)	Supported
H_R3: Across nations, men’s and women’s HS and BS negatively correlate with structural gender equality index (GGGI) (correlation analysis)	Supported
H_R4: At the individual level, HS and BS correlate modestly (correlation analysis)	Supported
H_R5: HS and BS correlate more strongly (H_R5a) for women than for men and (H_R5b) among people in more (vs. less) egalitarian societies (multilevel regression analysis)	Partial Support: Nations’ gender equality, but not participant gender, moderated the HS–BS relationship in multilevel regression. However, using original Glick et al.’s (2000) analytical approach replicated both the effects.
H_R6: Across nations, men generally endorse HS and BS more than women (paired t-tests)	Supported
H_R7: Across nations, women’s HS and BS scores strongly correlate with men’s scores (suggesting men’s ideological influence); (correlation analysis)	Supported
H_R8: Across nations, the gender gap (men’s minus women’s scores) in HS is larger than the gender gap in BS (women resist HS more than BS); (paired t-tests)	Supported
H_R9: Across nations, as men’s HS increases, the larger the HS gender gap (suggesting women increasingly resist men’s HS); (correlation analysis)	Supported
H_R10: Across nations, as men’s HS increases, the BS gender gap shrinks or reverses (suggesting a protection racket: women endorse BS to counter men’s HS); (correlation analysis)	Supported
Novel Hypotheses about Gender Inequality:
(all tested with linear regression, see Table 7)
H_N1: Across nations, as men’s and women’s HS and BS increases, justification for violence toward women also increases.	Supported
H_N2: Across nations, as men’s and women’s HS and BS increases, women’s participation in paid work decreases.	Mostly supported: Only women’s HS failed to correlate with paid work
H_N3: Across nations, the higher men’s and women’s BS, but not their HS, scores the larger gender gap in domestic labor with women contributing more than men.	Partially supported: BS, but not HS, correlated with domestic labor gender gap
Novel Hypotheses about Social Dysfunctions:
(all tested with linear regression, see Table 7)
H_N4: Across nations, the higher men’s and women’s HS and BS scores, the lower the nation’s economic productivity	Supported
H_N5: Across nations, the higher men’s and women’s HS and BS scores, the greater antidemocratic tendencies (less democratization, greater power distance)	Supported
H_N6: Across nations, the higher men’s and women’s HS and BS scores, the (H_N6a) greater collective violence (Global Peace Index) and (H_N6b) greater individual violence (homicide rates)	H_N6a supported, but H_N6b disconfirmed: HS and BS correlated with collective but not individual violence
H_N7: Across nations, the higher men’s and women’s HS and BS scores, the lower lifespan for both men and women	Supported

Consistent with AST, men endorsed HS and BS (ideologies justifying male dominance) more than women. However, AST posits a complex dynamic of ideological influence and resistance. Specifically, AST suggests men (the dominant group) influence women to accept sexist ideologies, but that women resist HS more than BS, and even encourage men’s BS when they feel most threatened. Indeed, women’s national HS and BS scores closely paralleled men’s. Yet, as men’s average HS increased, women scored lower on HS relative to men suggesting resistance. By contrast, the higher men scored on HS, the more women endorsed BS, supporting the protection racket hypothesis that women counter men’s HS by advocating BS, which prescribes male protection. This pattern represents a trap, reinforcing inequality because BS reduces women’s willingness to advocate for change (Becker & Wright, 2011). To further theory development, future research could explore whether similar ideological dynamics occur in other group relations, in which ostensibly benevolent ideologies (e.g., colonial paternalism; Jackman, 1994) complement and support hostile system-justifying ideologies, thereby inhibiting social change.

Novel indicators supported that BS’s protection promises are hollow: national BS averages correlated with accepting intimate violence toward women (see Agadullina et al., 2022; Gutierrez & Leaper, 2024). In addition, increasing women’s vulnerability, national BS scores correlated with fewer women in paid work and a larger gender gap in domestic labor. By idealizing women’s conventional domestic role, BS may discourage women’s participation in paid work, reinforcing inequality. Finally, we found that national HS and BS averages correlate with social dysfunctions affecting both sexes: lower economic productivity, more antidemocratic tendencies, greater collective violence, and lower healthy lifespan.

For the replication hypotheses, the new multilevel modeling approach replicated higher HS–BS correlations in more egalitarian nations, but not higher correlations for women than men, though analyses similar to Glick et al.’s did. It is possible that the gender moderation found in the work by Glick et al. (2000) may have been a statistical artifact due to simpler analyses. Indeed, the multilevel approach accounts for the hierarchical structure of our data (i.e., individual responses nested within countries) and both individual and systemic variance. This allows for more accurate and nuanced understanding of the data (Heck & Thomas, 2020). Alternatively, increasing egalitarianism more than two decades has also increased the HS–BS correlation for men because they too may feel the need to endorse BS to justify HS (Jackman, 1994). In fact, our six-item ASI mean is 0.47 lower than in Glick et al.’s (2000, 2004) data: 0.57 HS drop (0.63 for men and 0.5 for women) and 0.37 BS drop (0.22 for men and 0.5 for women). However, we did not achieve temporal equivalence for all these countries, and hence, this interpretation requires caution and awaits further direct testing.

In addition, some novel hypotheses were not supported. Although men’s and women’s sexism generally correlated with lower female participation in paid work (H_N2), women’s HS did not. This may be because high HS men view women as competitors, whereas high (and low) HS women have a vested interest in gaining financial independence. Thus, although women high in HS may express hostility toward women seeking “power over men,” they may nevertheless view paid work as necessary for women. We also found that BS but not HS predicted the domestic labor gender gap (H_N3). In hindsight, this makes sense given that BS extols women’s compliance with traditional roles (e.g., household chores) while HS prohibits status-related role transgressions, such as seeking power, HS becomes less relevant than BS in predicting domestic labor. Finally, HS and BS predicted greater collective violence (H_N6a) but not greater individual violence (H_N6b). Although individual and collective violence tend to be initiated by men, societies differ greatly in homicide rates due to factors, such as individual gun ownership that may overwhelm the contributions made by sexist attitudes (Hemenway & Miller, 2000).

Of theoretical importance, our findings support AST across more and more diverse (non-WEIRD) nations than tested in prior research (Bareket & Fiske, 2023), extending to specific gender unequal practices (justifying violence against women, gender gaps in paid and domestic labor) at national level of analysis. Perhaps most significantly, we document associations of HS and BS with diverse social dysfunctions affecting both sexes across various consequential domains: authoritarian politics, collective violence, lower economic productivity, and poorer health. The unique national-level perspective and insights suggest that recent Bareket and Fiske’s (2023) model integrating AST research could be usefully extended from individual to country-level processes and from focus on implications of sexism for women to those for men. Going beyond AST, there is a question of whether the interplay of the iron fist (hostility) and velvet glove (benevolence) can similarly be documented at national level for other system justification ideologies (e.g., Jackman, 1994), such as racism or homoprejudice? Further large cross-cultural investigations are needed to answer this theoretical question.

Of practical importance, our results, almost 30 years after AST’s inception, support its contentions about how HS and BS interact to justify and reinforce gender inequality. Yet these dynamics, which include both sexism’s influence and resistance to it, offer hope and a potential blueprint for change by puncturing the BS protection racket. National policies enforcing formal protection for women (e.g., laws that reduce violence toward women or enforcing workplace equality) can free women to more effectively resist inequality. Reducing threats from men should theoretically increase women’s resistance toward HS and decrease their perceived need to endorse BS. Future research aimed at documenting temporal patterns in sexist ideologies and equality indices, and the effects of sexism on men (still severely under-researched; Bareket & Fiske, 2023) could reveal the most effective drivers of change.

Strengths and Limitations

This case presents the most comprehensive cross-national examination of ambivalent sexism, across a third of the world’s nations. Newer statistical techniques used here demonstrated psychometric isomorphism for the ASI, justifying cross-national comparisons. Impressively, we replicated all core AST findings 20 years after Glick et al.’s (2000, 2004) foundational studies. Furthermore, our relatively young and homogeneous samples (mainly undergraduates) should have limited confounds and also suggest that ambivalently sexist ideologies will continue to inhibit gender equality well into the future.

Nevertheless, our findings remain correlational and therefore cannot definitively test AST’s causal hypotheses. Other methodologies, however, help to fill this gap. For example, longitudinal studies show that endorsing BS influences women to accept HS (Sibley et al., 2007). Experiments show that women exposed to BS evinced increased system justification and reduced collective action (Becker & Wright, 2011; Jost & Kay, 2005). By contrast, women exposed to bogus poll results that men strongly endorse HS showed increased BS, supporting the protection racket hypothesis (Fischer, 2006).

Using short ASI scales created another limitation: reduced reliability, especially for BS, which has three subfactors (compared with HS’s unitary structure). Lower reliability, however, should have attenuated (not increased) BS’s correlations with other variables. Furthermore, the consistency between current and past cross-national studies increases confidence in our findings, suggesting that the three-item BS scale assessed the intended construct. Most reassuringly, multilevel CFA yielded stable results after removing the 32 countries where scale reliability coefficients did not meet the 0.6 criterion (see Footnote 3).

Finally, some samples had unequal gender representation and divergent age ranges. All samples had too few individuals indicating nonbinary gender identities to analyze their responses (ranging from 0% to 1.79%). However, additional multilevel CFA employing (binary) gender and age as covariates yielded similar results (see Supplementary Materials). Although obtaining undergraduate samples potentially reduced confounds, it may limit generalizability (e.g., with respect to education and political orientation; Bareket & Fiske, 2023). Furthermore, national-level indices (except for GGGI) were not available for all 62 countries, restricting generalizability for the novel findings (especially for the gender gap in unpaid work and gross domestic product). Ideally, future studies would have larger, representative samples with equal gender ratios.

Conclusion

We replicated and extended findings regarding core AST tenets that only cross-national comparisons can test. Results closely replicated the work by Glick et al. (2000), suggesting that HS and BS represent universally recognizable, persistent, and complementary ideologies correlated with nations’ structural gender inequality. At the systemic level, BS remains a ubiquitous complement to HS that appears to legitimize HS and structural inequality, especially for people in relatively egalitarian nations. Results suggest women not only experience ideological influence from but also resist, men’s HS. By contrast, women most threatened by male HS, more strongly endorse BS, presumably in a bid to encourage male protection. Yet doing so only reinforces women’s vulnerability and dependence (BS correlated with justifying intimate violence, less participation in paid work and a larger gender gap in domestic labor). Although clearly worse for women, our results suggest sexism also harms men: HS and BS correlated with social dysfunctions affecting both sexes: antidemocratic practices, lower economic productivity, more collective violence, and poorer health. Thus, men may also have a direct stake in fostering a more gender-equal society.

Supplemental Material

sj-docx-1-spp-10.1177_19485506241302882 – Supplemental material for Worse for Women, Bad for All: A 62-Nation Study Confirms and Extends Ambivalent Sexism Principles to Reveal Greater Social Dysfunction in Sexist Nations

Supplemental material, sj-docx-1-spp-10.1177_19485506241302882 for Worse for Women, Bad for All: A 62-Nation Study Confirms and Extends Ambivalent Sexism Principles to Reveal Greater Social Dysfunction in Sexist Nations by Magdalena Zawisza, Natasza Kosakowska-Berezecka, Peter Glick, Michal Olech, Tomasz Besta, Paweł Jurek, Jurand Sobiecki, Deborah L. Best, Jennifer K. Bosson, Joseph A. Vandello, Saba Safdar, Anna Włodarczyk and Magdalena Żadkowska in Social Psychological and Personality Science

Footnotes

Acknowledgements

The results presented in this case are part of the wider project entitled: Towards Gender Harmony () where more wonderful people are involved. The authors thank the University of Gdańsk Research Assistants Team: Agata Bizewska, Mariya Amiroslanova, Aleksandra Głobińska, Andy Milewski, Piotr Piotrowski, Stanislav Romanov, Aleksandra Szulc, Olga Żychlińska, who have helped in coordinating data collections in all the countries. They also thank A. Timur Sevincer for his contribution with data collection from the University of Hamburg, Germany. Data collection has been supported by Angel Gomez, Universidad Nacional de Educación a Distancia, Spain (grant no. RTI2018-093550-B-I00) and Claudio V. Torres, University of Brasilia (grant no. DPI / DIRPE n. 04/2019).

Handling Editor: Shenel Husnu

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by a grant from the National Science Center in Poland (grant no. 2017/26/M/HS6/00360) awarded to N.K.B. N.K.B, P.G., M.O., P.J., and M.Z. contributed equally to the paper. M.Z. led the work on this paper, co-wrote with N.K.B the first draft of the introduction, methods, and replication part of the results. P.G. provided data from his 2000 and 2004 projects that formed the basis of this work, and revised and edited the first and consecutive versions of the paper. M.O. and P.J. conducted and reported advanced isomorphism and multilevel analyses for novel extension hypotheses. All others contributed to the final version of the paper.

Data Availability

All data, analysis code, and research materials are available at https://osf.io/trkyc/. Data were analyzed using R. The project, hypotheses, design, and analyses were preregistered here at https://osf.io/wyrb3 (with exceptions mapped in ).

ORCID iDs

Magdalena Zawisza

Michal Olech

Tomasz Besta

Deborah L. Best

Jennifer K. Bosson

Joseph Vandello

Saba Safdar

Supplemental Material

The supplemental material is available in the online version of the article.

Notes

Author Biographies

Magdalena Zawisza is an associate professor in Gender and Consumer Psychology at Anglia Ruskin University, Cambridge, UK. She publishes in leading peer-review journals, authored and co-edited three books, sits on the editorial board for Sex Roles, is a review editor for Frontiers Gender, Sex and Sexuality Studies section, and a holder of prestigious grants. She heads Applied Social Change Research Hub and Societies and Groups Research Center, and her research informed policy changes by British Advertising Standards Authority.

Natasza Kosakowska-Berezecka works as an associate professor and Head in the Division of Cross-Cultural Psychology and Psychology of Gender at the University of Gdańsk (Poland). Her main area of research interest focuses on cultural cues, fostering gender equality within societies worldwide. She also conducts research on the backlash against communal men and the universality of precarious manhood.

Peter Glick co-developed ambivalent sexism theory (with Susan Fiske) and the stereotype content model (with Susan Fiske, Amy Cuddy, and Jun Xu). The foundational articles for each theory have been recognized for innovation and influence on the field: ambivalent sexism with SPSSI’s Allport Award in 1995 and the stereotype content model with SESP’s Scientific Impact Award in 2022.

Michal Olech serves as an assistant professor at the Quality of Life Research Unit, Faculty of Health Sciences, Medical University of Gdańsk (Poland). His areas of expertise include statistics and data analysis, and he has a particular passion for working within the R computing environment.

Tomasz Besta works as an associate professor at the Institute of Psychology of the University of Gdańsk, and Head of Environmental Psychology and Intergroup Relations Lab. He studies intergroup relations, collective actions, radicalisation, and group dynamics.

Paweł Jurek is an associate professor at the University of Gdańsk and the Medical University of Gdańsk. He has developed numerous original measurement tools used in psychology and actively collaborated with renowned international scientific institutions, conducting joint research and workshops on methodology and statistical data analysis for young scientists. From 2020 to 2024, he served as the Director of the Institute of Psychology and the Chair of the Discipline Council for Psychology at the University of Gdańsk.

Jurand Sobiecki runs a cross-cultural project on religiosity and leads the student organization SciClub. As a psychologist and medical biologist, his interests span multiple disciplines and topics, including the gut microbiome, religiosity, nihilism, nutrition, statistics, coding, and cognitive flexibility.

Deborah L. Best is the William L. Poteat Professor of Psychology, Emerita, at Wake Forest University. A developmental psychologist by training, one line of her research focuses on children’s cognitive development and memory strategies. Also as a cross-cultural psychologist, she has explored the nature and development of gender, racial, and age stereotypes and attitudes of children and adults around the world.

Jennifer K. Bosson is a social psychologist and professor of psychology at the University of South Florida, where she has been on the faculty since 2006. Her primary research interests are in gender, masculinity, sexual prejudice, and the self. She has published more than 75 empirical articles and book chapters, and a textbook on the psychology of sex and gender.

Joesph A. Vandello is a professor in the Department of Psychology, University of South Florida, USA. He studies anxieties surrounding gender.

Saba Safdar is a professor in applied social psychology at University of Guelph, Canada. Her primary research focus is the examination of the psychological adaptation of immigrants in their adopted countries. She has investigated the diverse experiences of newcomers (e.g., sojourners, refugees, sexual minorities, Muslims) within Canada and abroad.

Anna Włodarczyk is a researcher at the School of Psychology at the Universidad Católica del Norte (Chile). She graduated in sociology at the University of Warsaw and received her PhD in psychology from the University of the Basque Country. Her main research interests cover coping and emotional regulation, posttraumatic growth, political psychology, social identity, intergroup relations, gender, and positive psychology.

Magdalena Żadkowska is an assistant professor at the Institute of Sociology, University of Gdańsk, Poland. She focuses on qualitative studies devoted to sociology of a couple, intimate relations, and women and men carriers in substituted with Science, Technology, Engineering, Maths and Medicine.

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(2015). Societies in transition: Are they more sexist? A comparison between Polish, South African and British samples. Journal of Gender Studies, 24(1), 38–55. https://doi.org/10.1080/09589236.2013.803952

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