Attitudes Toward Hispanic Immigrants and Immigration Policies in the United States: Exploring the Roles of Age and Framing Through a Survey Experiment

Abstract

Hispanic immigrants are the largest immigrant group in the United States. However, conflicting immigration attitudes have stalemated efforts to develop more systematic and effective policies to better incorporate them. Guided by age stratification theory and framing theory, the present study examined the roles of age and framing in attitudes toward Hispanic immigrants and immigration policies. We used an experimental design to embed survey questions in the RAND American Life Panel (n = 694). Before answering the questions, respondents were randomly assigned to one of three brief priming statements that described Hispanic immigrants using a conservative, progressive, or no framing. We performed bivariate analyses and multivariate regressions to examine how age and framing are associated with attitudes toward Hispanic immigrants and immigration policies, and conducted post hoc comparisons to determine the interactions between age and framing. We found that at the bivariate level, compared to younger people, middle-aged and older people had less supportive attitudes toward Hispanic immigrants and immigration policies; there was no difference in immigration attitudes by framing. After controlling for covariates, we found that compared to younger people, middle-aged were less supportive of immigrants, and both middle-aged and older adults were less supportive of immigration policies; conservative framing was associated with a more negative attitude toward immigration policies. Framing moderated differences in immigration attitudes by age, with different age groups tending to be responsive to different framing statements. The study highlights age as a significant factor in affecting immigration attitudes, and demonstrates the potential of using framing to influence immigration attitudes for different age groups.

Keywords

immigration attitudes Hispanic immigrants age differences framing survey experiment

Introduction

The United States is home to nearly 20 million Hispanic immigrants, the largest immigrant group in the country (Krogstad et al., 2022). Based on the 2020 Census, Hispanics accounted for 18.7% of the total U.S. population (N. Jones et al., 2021). By the middle of this century, the U.S. is projected to become what has been termed a “majority-minority nation,” in which no single racial or ethnic group will comprise the majority (Alba, 2018; Torres-Gil & Demko, 2019). The steady and rapid growth of the Hispanic population is an important driving force for this demographic shift. It is projected that by 2060, Hispanics will comprise nearly 30% of the population (U.S. Census Bureau, 2018). Notably, two-thirds of Hispanics currently living in the United States are native-born (Batalova et al., 2021), a percentage that has been increasing over the last several decades (Zong, 2022).

Although the U.S. is recognized as a “nation of immigrants,” conflicting attitudes toward immigrants and immigration in general, fueled by partisan political controversy, have stalemated efforts to develop more systematic and effective policies (Galston, 2024; Lee, 2006; Lichter, 2013; Lopez et al., 2015; Reyna et al., 2013). Pulling the lens back to examine how immigration has been framed over the past 140 years, Card et al. (2022) used machine learning to identify trends in language toward immigrants. Their findings reveal a dual trend. Attitudes toward immigrants have become more positive in more recent history, but there has also been a growing divergence in views over the past few decades based on political affiliation, with Republicans showing increasing hostility toward immigration and a higher propensity to use dehumanizing language (Card et al., 2022). Shifts toward more negative attitudes are reflected in recent preferences among Americans, with a majority (55%) supporting reductions in immigration—the highest proportion since 2001 (J. M. Jones, 2024).

These changing preferences underscore the importance of understanding the extent to which current immigration attitudes are immutable or flexible enough to change. Toward that end, we aim to address this question by exploring the associations of age and framing with attitudes toward Hispanic immigrants and immigration policies.

Age Stratification of Immigration Attitudes

Immigration attitudes are associated with sociodemographic factors (Hainmueller & Hopkins, 2014; Reyna et al., 2013), such as age (Calahorrano, 2013; Gorodzeisky & Semyonov, 2018; McLaren & Paterson, 2020), gender (Berg, 2010; Valentova & Alieva, 2014), race/ethnicity (Ayers et al., 2009; Dustmann & Preston, 2007; Valentino et al., 2013), education (Cavaille & Marshall, 2019; Hainmueller & Hiscox, 2007; Mayda, 2006), income (Dancygier & Donnelly, 2013; Finseraas et al., 2017), and political affiliation (Druckman et al., 2013; Rustenbach, 2010; Vrânceanu, 2022). A recent meta-analysis of 114 studies on eight individual-level factors that potentially affect immigration attitudes (i.e., age, gender, education, minority background, employment status, income, high-skill occupation, and living area) indicated that age is a strong predictor (Dražanová et al., 2022).

Age stratification theory suggests that age is an important factor in shaping differences between people because of shared characteristics within each age group (Foner, 1974; Riley, 1971). The aging effect and cohort effect are two plausible explanations of the origins of shared characteristics. Indicative of the aging effect, it is widely believed that people become more conservative as they grow older. Glenn (1974) discussed the theoretical foundation of why conservatism might be associated with aging from biological (e.g., linkage between increased cautiousness and rigidity with functional decline), social (e.g., appreciation of social order and attempt to preserve continuity and stability), and psychological (value shift due to psychological development) dimensions. Empirical studies show that although political attitudes usually remain stable, when shifts happen with age, liberals are more likely to become conservatives than conservatives are to become liberals (Peterson et al., 2020). By contrast, cohort effects suggest that, due to common exposures to certain historical and social events across their life span, people in the same age group share similar opinions toward social issues, including immigration (Calahorrano, 2013; Cutler & Kaufman, 1975; Ryder, 1985).

Some recent studies from Europe found that older adults have more restrictive immigration attitudes compared to younger adults. Using the European Social Survey data for 25 countries from 2002 to 2014, Schotte and Winkler (2018) confirmed the existence of a positive association between older age and anti-immigration attitudes, and suggested that it is based on a cohort difference rather than an aging effect. McLaren and Paterson (2020) drew similar conclusions by analyzing the same dataset across 16 countries over 22 years to explore generational differences in immigration attitudes. They argued that better education and skills made younger generations better prepared to respond to and be more open to immigration. In a cross-sectional study, Heath and Richards (2020) observed that increased age is associated with increased anti-immigration attitudes in the 2014 European Social Survey, but they did not separate the aging effect and cohort difference. Analyzing data from the 2007 to 2019 Netherlands Longitudinal Internet Studies for the Social and the 2017 European Values Study, Lancaster (2022) found that older cohorts tended to be more opposed to immigration compared to younger cohorts. In the U.S., although a handful of earlier studies revealed that older age is associated with a less welcoming attitude toward immigrants (Cowan et al., 1997; Espenshade & Calhoun, 1993; Gil de Zúñiga et al., 2012), age was not the central focus of those studies. Few recent studies have examined the role of age in attitudes toward immigration, with hardly any academic study focused on age and attitudes toward Hispanic immigrants.

Shaping Attitudes Through Framing

Framing is a potentially powerful tool to change attitudes by influencing how people perceive and evaluate issues (Chong & Druckman, 2007; Goffman, 1974). People habitually use mental shortcuts to make sense of what is going on around them, making judgments and decisions through relatively stable frameworks based on knowledge, values, and predominant emotions (Nisbet, 2016). When an issue is congruent with a person’s primary framework, it can activate these mental shortcuts and pique their interest. In contrast, when an issue is presented in conflict with their primary framework, it may lead to dismissal or aversion (Chong & Druckman, 2007).

Some studies indicate that negative framing (e.g., immigrants are a threat to national security or a drain on the economy) is associated with increased perceptions of immigrants as threats fostering anti-immigration attitudes, while positive framing (e.g., immigrants are a source of economic opportunity or cultural enrichment), is associated with more welcoming attitudes (Brader et al., 2008; Fujioka, 2011). A study by Young et al. (2022) found that most newspaper coverage in the U.S. in the last decade negatively framed immigrants, which coincided with growing anti-immigration attitudes and support for exclusionary policies (e.g., travel bans, detention, and deportation, restricting access to refugee and asylum) among the public. Characterizing Hispanic immigrants as untrustworthy, impoverished, prone to criminal behavior, and job market competitors with native-born Americans are some commonly used negative framings for this population (Alamillo et al., 2019; Haynes et al., 2016). Such negative framings can translate into prejudice, stereotypes (Esses, 2021; Tirado-Espín et al., 2021), and hostile attitudes toward Hispanic immigrants (Casas & Cabrera, 2011; Lyons et al., 2013; Stephan et al., 1999) and increase support for immigration policies with fewer humanitarian values (e.g., family separation, detention of asylum seekers) (Cowan et al., 1997; Reny & Manzano, 2016; Rowatt et al., 2020).

Framing has been shown to affect original attitudes toward Hispanic immigrants. For example, in a framing experiment conducted with Iowa voters, labeling immigrants as “Mexicans” tended to increase support for punitive and restrictive approaches to immigration reform by Republicans, who viewed immigration as a significant problem (Knoll et al., 2011). In contrast, Merolla et al. (2013) found that mentioning that immigrants “came as young children” was associated with increased support for the DREAM (Development, Relief, and Education for Alien Minors) Act among individuals across different political affiliations, albeit with a modest effect size. This framing triggered sentiment related to the positive perception of children.

The purpose of this study is to examine the effects of age and framing on attitudes toward Hispanic immigrants and immigration policies. Although value-aligned framing has been shown to be an effective tool to shape attitudes (CDC, 2008; Chittamuru et al., 2020; Schmeltz, 2014), how different age groups respond to framing is understudied. To the best of our knowledge, this study is the first to examine how age and framing are related to immigration attitudes toward Hispanics in a national sample. Focusing on two dimensions, attitude toward Hispanic immigrants and attitude toward immigration policies, we hypothesize that:

(1) Age will be associated with attitudes toward immigrants and immigration policies such that: Younger adults will have more positive attitudes than middle-aged adults and older adults toward Hispanic immigrants and immigration policies.

(2) Framing will be associated with attitudes such that: Compared to respondents who did not receive a priming statement, those who receive a priming statement using conservative or progressive framing of Hispanic characteristics will show more positive attitudes toward Hispanic immigrants and immigration policies.

(3) Framing will moderate differences in attitudes such that:

a. Conservative framing will be associated with more positive attitudes toward Hispanic immigrants and immigration policies among middle-aged and older adults compared to younger adults.

b. Progressive framing will be associated with a more positive attitude toward Hispanic immigrants and immigration policies among younger people compared to middle-aged and older adults.

Methods

Sample

We collected data from the 2018 “Well Being 501 - Latino Economic Security Survey” through the RAND American Life Panel (ALP), a nationally representative and probability-based panel comprising more than 6,000 participants who are regularly interviewed over the internet. The survey was part of the Latinos and Economic Security Project led by this paper’s senior author to better understand public attitudes toward Hispanics. 739 participants completed the survey. To include political affiliation as a covariate in our analyses, we linked the “Well Being 501 Latino Economic Security Survey” dataset with the “Well Being 464 - 2016 RAND Presidential Election Panel Survey (PEPS) [W05]” dataset, which contains information on respondents’ political affiliation. After matching 702 respondents who took both surveys and excluding eight respondents with missing information on study variables, we included 694 respondents in the final analytic sample.

Measures

“Attitude toward Hispanic immigrants” was measured by a scale developed by the research team that included support for seven statements on feelings about Hispanic immigrants. Each statement was scored on a 5-point Likert scale (1 = strongly agree to 5 = strongly disagree): (1) U.S. policy should be guided by the Bible, which instructs us to “welcome/love the stranger.” (2) Hispanic/Latino immigrants who have permission to live in the U.S. are hard workers. (3) Hispanic/Latino immigrants who are undocumented are hard workers. (4) Undocumented Hispanic/Latino immigrants drain the economy. (5) Undocumented Hispanic/Latino immigrants are responsible for increases in crime, drugs, and other illegal behaviors. (6) Hispanic/Latino immigrants are trying to take over our country and impose their language, culture, and beliefs on the U.S. (7) Ethnic and racial diversity benefits all Americans. The internal consistency of the seven statements in the present sample was good (α = .82). After reverse coding, we added the scores for each statement, so a higher score reflects a more welcoming attitude toward Hispanic immigrants. Scores ranged from 7 to 35 following a normal distribution (skewness = −0.27, kurtosis = 2.37).

“Attitude toward immigration policies” was measured by support for five statements on actions that should be taken to immigrants on a 5-point Likert scale (1 = strongly agree to 5 = strongly disagree): (1) Children brought to the U.S. and raised here (sometimes called “dreamers”) deserve our help to become Americans with permission to live in the U.S. (2) English should be required as the official language. (3) All undocumented immigrants in the U.S. should be deported. (4) Undocumented immigrants willing to work should have access to legal employment. (5) Educational opportunities should be expanded for all immigrants. The internal consistency of the five statements in the present sample was good (α = .87). After reverse coding, we added the scores for each statement, with a higher score reflecting a more positive attitude toward immigration policies favorable to Hispanic immigrants. The total score ranged from 5 to 25, following a normal distribution (skewness = −0.19, kurtosis = 2.08). The two dependent variables, attitude toward Hispanic immigrants and attitude toward immigration policies, were highly correlated (r = .83, p < .001).

Age

Respondents were classified into three ordinal age groups (1 = 39 or younger, 2 = 40 to 59, 3 = 60 or older) to represent young, middle-aged, and older people.

Framing

Before answering the survey questions, respondents were randomly assigned to read one of three brief priming statements that included a description about Hispanic immigrants (see the Supplemental Material for the framing statements): (1) “Conservative framing” that appealed to values that may be more prioritized by conservative individuals, establishing the U.S. as a nation of immigrants and framing Hispanic immigrants as being patriotic, religious, and family-oriented (n = 231); (2) “Progressive framing” that appealed to values that may be more prioritized by progressive individuals, focusing on the unjustified blaming of Hispanic immigrants for problems related to the economy and crime, and the fear and turmoil experienced by families who are in the U.S. without documentation (n = 229); (3) Reference group with no priming statement (n = 234). The three priming statements were coded as 0 = No framing, 1 = Conservative framing, and 2 = Progressive framing.

Covariates

Eight covariates were included: gender (0 = male, 1 = female); race/ethnicity (1 = non-Hispanic White, 2 = Hispanic, 3 = non-Hispanic Other); education attainment (0 = no college degree, 1 = college degree or more); whether born in the U.S. (0 = not born in the U.S., 1 = born in the U.S.); marital status (0 = unmarried/unpartnered; 1 = married/partnered), employment status (0 = unemployed, 1 = employed); household income (0 = less than 75,000 per year; 1 = 75,000 or more per year); and political affiliation (1 = Democrat, 2 = Republican, 3 = Other).

Analytic Strategy

We conducted χ² tests to examine whether the distribution of respondents by the study variables was independent of the three priming statements. We then conducted ANOVA tests to explore whether the score of attitudes toward Hispanic immigrants and the score of attitudes toward immigration policies varied by each independent variable. Given that patterns of responses to the attitude questions may be distinct for Hispanics, we also used ANOVA to test for age differences among the Hispanic respondents. To examine how age and framing are associated with each dependent variable when controlling for covariates, we performed two sets of multivariate linear regression models on the attitude toward Hispanic immigrants and the attitude toward immigration policies. In each set of multivariate linear regression models, we tested the interaction between age and framing after examining their main effects. Since group differences in interaction models rely on multiple parameters, we compared the predicted scores for respondents from each age group under each priming statement, and the predicted scores for respondents receiving each priming statement within each age group. The predicted scores in post hoc comparisons were calculated from the regression models that included the interaction term of age and framing. In all analyses, we applied the survey weights that ALP generated (Pollard & Baird, 2017) to make our sample approximate the general U.S. population. We used robust standard errors in regression models. All analyses used two-tailed tests to determine statistical significance. Analyses were performed in STATA 18.0 (Stata Corp, College Station, TX).

Results

Descriptive Characteristics of the Sample

Table 1 presents the distribution of the respondents (N = 694) among the independent variables across the three priming statements. Respondents aged from 22 to 90 years with a mean of 51 years. About 37.0% were older adults born from 1928 to 1958, 32.0% were middle-aged adults born from 1959 to 1978, and 31.0% were young adults born from 1979 to 1996. The majority of respondents were non-Hispanic Whites, accounting for 70.7% of the sample. Hispanics and non-Hispanic Others consisted of 15.2% and 14.1% of the sample. About 53.7% were female, 90.3% were born in the U.S., 61.1% were married or partnered, 40.8% had a college degree, 55.1% were employed, and 41.0% had a household income of $75,000 or more per year. Democrats, Republicans, and Others constituted 43.7%, 34.8%, and 21.5% of the sample, respectively. Each of the three priming statements was assigned to about a third of the respondents. None of the χ² tests’ p-values were statistically significant, indicating that there were no significant differences in the characteristics of the respondents across the priming statements.

Table 1.

Distribution of Respondents by Variables Across Three Statements.^a

	Full sample	No framing	Conservative framing	Progressive framing	χ² (p)
	N = 694 (%)	n = 234 (%)	n = 231 (%)	n = 229 (%)	χ² (p)
Age (mean = 51, range: 22–90)					2.82 (0.59)
Young	31.0	24.1	34.1	35.0
Middle-aged	32.0	36.6	30.7	28.6
Older	37.0	39.3	35.2	36.4
Race/Ethnicity					2.74 (0.60)
Non-Hispanic White	70.7	71.3	74.7	65.8
Hispanic	15.2	12.6	11.8	21.5
Non-Hispanic Other	14.1	16.1	13.5	12.7
Gender					0.64 (0.73)
Female	53.7	50.4	54.9	56.0
Male	46.3	49.6	45.1	44.0
Born in the U.S.					2.52 (0.28)
Yes	90.3	93.1	92.6	84.9
No	9.7	6.9	7.4	15.1
Marital status					5.49 (0.06)
Married/Partnered	61.1	52.8	61.4	69.6
Unmarried/Unpartnered	38.9	47.2	38.6	30.4
Education					2.24 (0.33)
College degree or more	40.8	38.2	37.6	47.2
No college degree	59.2	61.8	62.4	52.8
Employment					0.92 (0.63)
Yes	55.1	51.2	57.2	56.9
No	44.9	48.8	42.8	43.1
Household income					5.83 (0.06)
≥75,000	41.0	44.2	31.7	47.9
<75,000	59.0	55.8	62.3	52.1
Political affiliation					2.91 (0.58)
Democrat	43.7	43.6	48.4	38.6
Republican	34.8	38.1	31.9	34.5
Other	21.5	18.3	19.7	26.9

The percentages in each cell are weighted proportions.

Bivariate Analyses of Study Variables

Table 2 presents the mean scores of the two dependent variables by each independent variable. The results of one-way ANOVA tests revealed that attitudes toward Hispanic immigrants and immigration policies were associated with age, race/ethnicity, whether born in the U.S., education, employment status, and political affiliation at the bivariate level. Several of these bivariate relationships were significant, including by age. Compared to young adults, middle-aged and older adults had significantly lower scores (less positive) for attitude toward Hispanic immigrants (F = 4.03, p < .05) and significantly lower scores (less positive) for attitude toward immigration policies (F = 5.28, p < .01). Neither attitudes toward Hispanic immigrants nor immigration policies were associated with framing at the bivariate level. Additionally, we found no statistically significant differences in immigration attitudes among Hispanics by age (see Supplemental Material).

Table 2.

Mean Scores of Immigration Attitudes by Independent Variables.

	Toward Hispanic immigrants		Toward immigration policies
	M ± SD	F	M ± SD	F
Overall	24.84 ± 5.45		16.40 ± 5.17
Framing		1.64		0.91
No framing	24.16 ± 5.65		16.42 ± 5.00
Conservative framing	24.84 ± 5.35		15.94 ± 5.23
Progressive framing	25.55 ± 5.29		16.89 ± 5.25
Age		4.03*		5.28**
Young	26.08 ± 4.04		17.94 ± 4.81
Middle-aged	24.49 ± 5.98		15.94 ± 5.16
Older	24.10 ± 5.84		15.51 ± 5.21
Race/Ethnicity		10.95***		16.62***
Non-Hispanic White	24.31 ± 5.55		15.77 ± 5.34
Hispanic	27.80 ± 4.09		19.55 ± 3.55
Non-Hispanic other	24.29 ± 5.27		16.18 ± 4.48
Gender		0.32		0.25
Female	24.67 ± 5.13		16.54 ± 4.99
Male	25.03 ± 5.81		16.25 ± 5.37
Born in the U.S.		13.29***		4.34*
Yes	24.47 ± 5.39		16.19 ± 5.19
No	28.24 ± 4.85		18.34 ± 4.55
Marital status		0.29		0.01
Married/partnered	24.97 ± 5.63		16.38 ± 5.37
Unmarried/unpartnered	24.62 ± 5.16		16.43 ± 4.84
Education		14.53**		9.26**
College degree or more	26.12 ± 4.80		17.44 ± 5.20
No college degree	23.95 ± 5.70		15.69 ± 5.03
Employment		2.92		5.31*
Yes	25.31 ± 5.34		16.97 ± 5.05
No	24.26 ± 5.54		15.70 ± 5.22
Household income		0.42		0.53
≥75,000	25.08 ± 5.12		16.65 ± 5.12
<75,000	24.67 ± 5.67		16.23 ± 5.19
Political affiliation		61.93***		79.88***
Democrat	27.99 ± 4.42		19.46 ± 4.17
Republican	21.43 ± 4.34		12.79 ± 3.75
Other	23.95 ± 5.35		16.02 ± 5.11

p < .05. **p < .01. ***p < .001.

Multivariate Regression Models

Table 3 shows the results of multivariate linear regression models on attitudes toward Hispanic immigrants and immigration policies. Across all regression models, none of the variance inflation factors were above 4, and none of the tolerance values were below 0.25, confirming that multicollinearity was not a concern.

Table 3.

Multivariate Regression Models.

	Toward Hispanic immigrants				Toward immigration policies
	Model 1		Model 2		Model 3		Model 4
	β	t	β	t	β	t	β	t
Framing (Ref = No framing)
Conservative framing	.16	0.26	−1.43	−1.23	−1.05	−1.97*	−3.11	−2.57*
Progressive framing	.78	1.28	−0.24	−0.21	−0.11	−0.20	−2.00	−1.71
Age (Ref = Young)
Middle-aged	−1.28	−1.96*	−3.24	−3.06**	−1.89	−2.86**	−3.88	−3.70***
Older	−1.06	−1.72	−1.89	−1.75	−1.53	−2.26*	−3.56	−3.30**
Race/Ethnicity (Ref = non-Hispanic White)
Hispanic	2.08	2.60**	1.92	2.52*	2.36	2.88**	2.23	2.85**
non-Hispanic other	−1.47	−1.92	−1.51	−2.05*	−1.13	−1.60	−1.25	−1.88
Gender (Female)	−0.39	−0.78	−0.38	−0.77	.11	0.23	.16	0.35
Born in the U.S. (Yes)	−2.03	−1.67	−2.04	−1.82	−0.37	−0.31	−0.39	−0.34
Marital status (Married/Partnered)	.59	1.07	.52	0.98	.41	0.77	.34	0.64
Education (College degree or more)	.93	1.79	.75	1.53	.53	1.14	.35	0.74
Employment (Yes)	.30	0.63	.31	0.64	.57	1.16	.54	1.13
Household income (≥75,000)	.23	0.34	.40	0.66	.53	0.96	.72	1.43
Political affiliation (Ref = Other)
Democrat	4.06	5.37***	4.12	5.47***	3.78	5.47***	3.78	5.66***
Republican	−2.51	−3.18**	2.50	−3.36**	−2.97	−4.25***	−3.04	−4.56***
Age × Framing (Ref = Young, No framing)
Middle-aged × Conservative framing			2.68	1.81			2.40	1.62
Middle-aged × Progressive framing			2.92	2.02*			3.13	2.13*
Older × Conservative framing			1.80	1.24			3.25	2.24*
Older × Progressive framing			.10	0.07			2.20	1.67
Summary statistics
Overall R²	.3892***		.4024***		.4285***		.4436***

p < .05, **p < .01, ***p < .001.

As shown in model 1, controlling for all other variables, compared to young adults, middle-aged adults (β = −1.28, p < .05) were likely to have a lower score, reflecting a less positive attitude toward Hispanic immigrants. In model 3, controlling for all other variables, compared to younger adults, middle-aged adults (β = −1.89, p < .01) and older adults (β = −1.53, p < .05) were likely to have a less supportive attitude toward immigration policies. Conservative framing was also associated with a less supportive attitude toward immigration policies (β = −1.05, p < .05).

Examination of the Interaction Between Age and Framing

We included interaction terms between age and framing in both multivariate regression models to test whether framing can moderate the relationship between age and immigration attitudes. Among middle-aged adults, those who received the progressive priming statement tended to have a more supportive attitude toward Hispanic immigrants (β = 2.92, p < .05) and immigration policies (β = 3.13, p < .05) in models 2 and 4, respectively. Among older adults, those who received the conservative priming statement tended to have a more supportive attitude toward immigration policies (β = 3.25, p < .05) in model 4.

We further examined the effects of framing on age by looking at whether the predicted scores of attitudes for each age group differ from each other under the three framing conditions. As shown in Table 4, for respondents who did not receive a framing statement, those who were middle-aged had a lower predicted score than the younger age group (difference = −3.24, p < .01) in attitudes toward Hispanic immigrants. Both the middle-aged (difference = −3.88, p < .001) and older adult groups (difference = −3.56, p < .01) had a lower predicted score than the younger adults in their attitude toward immigration policies. There was no difference between the three age groups of respondents who received either the conservative or the progressive framing, which suggests that framing moderated the difference in immigration attitudes by age group.

Table 4.

Comparison of Predicted Scores of Immigration Attitudes.

	Toward Hispanic immigrants		Toward immigration policies
	Difference	z	Difference	z
Difference of scores for age group, by framing
No framing
Middle-aged versus young	−3.24	−3.06**	−3.88	−3.70***
Older versus young	−1.89	−1.76	−3.56	−3.30**
Older versus middle-aged	1.35	1.46	0.32	0.42
Conservative framing
Middle-aged versus young	−0.56	−0.53	−1.48	−1.48
Older versus young	−0.09	−0.08	−0.31	−0.30
Older versus middle-aged	0.47	0.48	1.17	1.37
Progressive framing
Middle-aged versus young	−0.32	−0.31	−0.76	−0.69
Older versus young	−1.79	−1.93	−1.36	−1.44
Older versus middle-aged	−1.47	−1.58	−0.60	−0.66
Difference of scores for framing, by age group
Young
Conservative framing versus no framing	−1.43	1.23	−3.11	−2.57*
Progressive framing versus no framing	−0.24	−0.21	−2.00	−1.71
Progressive framing versus conservative framing	1.19	1.17	1.11	1.01
Middle-aged
Conservative framing versus no framing	1.25	1.30	−0.71	−0.88
Progressive framing versus no framing	2.68	2.82**	1.13	1.20
Progressive framing versus conservative framing	1.43	1.44	1.84	2.01*
Older
Conservative framing versus no framing	0.37	0.41	0.14	0.18
Progressive framing versus no framing	−0.14	−0.17	0.20	0.31
Progressive framing versus conservative framing	−0.52	−0.61	0.06	0.09

p < .05. **p < .01. ***p < .001.

To determine which framing each age group was more responsive to, we compared the predicted scores for respondents under the three priming statements within each age group. Among young adults, those who received a conservative frame had a lower score in attitude toward immigration policies than those who did not receive a framing statement (difference = −3.11, p < .05). Among middle-aged adults, those who received a progressive framing had a higher score in attitude toward Hispanic immigrants than those who did not receive a frame (difference = 2.68, p < .01), and had a higher score in attitude toward immigration policies than those who received a conservative framing (difference = –1.84, p < .05). The predicted scores are provided in the Supplemental Material.

Discussion

The present study examined attitudes toward Hispanic immigrants and immigration policies among adults living in the U.S. We compared attitudes by age (young, middle-aged, and older adults), random assignment to a priming statement before starting the survey questions (conservative, progressive, or none), and the extent to which priming statements about immigrants and immigration policies modified attitudes by age.

Our first hypothesis, focused on age, was partially supported. Compared to younger people, middle-aged were less supportive of immigrants, and both middle-aged and older adults were less supportive of immigration policies. This finding was consistent with previous findings that young adults tend to have the most positive attitudes toward immigrants (Debrael et al., 2021; Doherty et al., 2018), and older people are likely to become more conservative toward policy issues (Cornelis et al., 2009; Franssen et al., 2013; Glenn, 1974; Tilley & Evans, 2014).

Our second hypothesis, focused on framing, was not supported. At bivariate level, neither the conservative framing nor the progressive framing was associated with more positive attitudes toward Hispanic immigrants or immigration policies. At multivariate level, the conservative framing was associated with a more negative attitude toward immigration policies.

Regarding the third hypothesis, the present study suggests that framing (i.e., positive messaging) could reduce differences in immigration attitudes by age. As shown in Table 4, among respondents who did not receive a priming statement, compared to younger respondents, the middle-aged had a less welcoming attitude toward Hispanic immigrants and a more negative attitude toward immigration policies; the older had a more negative attitude toward immigration policies. Among respondents who received a priming statement, regardless of conservative or progressive framing, there was no difference in attitudes toward immigrants or immigration policies by age.

Findings also suggested that those in different age groups tended to be responsive to different framing statements. The post hoc analysis (Table 4) confirmed that among young respondents, conservative framing is associated with a more negative attitude toward immigration policies than no framing; among the middle-aged respondents, progressive framing is associated with a more positive attitude toward Hispanic immigrants than no framing, and progressive framing is associated with a more positive attitude toward immigration policies than conservative framing. Although the post hoc analysis did not confirm the effect of framing on older people, the significant interaction term between old age and conservative framing in regression model 4 indicated that conservative framing might boost older respondents to have a more positive attitude toward immigration policies. Such findings highlighted the importance of customizing framings for different demographic groups.

Despite the relatively small effect, it is noteworthy that the frames were associated with changes in attitudes toward immigrants and immigration policies. In the last several years, there has been a drumbeat of antiimmigrant sentiment among leaders. Although this is in keeping with divergent trends over many decades, descriptions of immigrants and the characteristics of those coming to the U.S. have become increasingly hostile (Card et al., 2022). Stronger efforts are needed to educate the U.S. population and correct inaccuracies, such as portrayals that immigrants perpetrate more crime (e.g., crime rates are lower among immigrants), are less patriotic, and are a drain on public funds (e.g., undocumented immigrants are not eligible for many public programs such as Social Security and Medicare). Considering the influence of framing, consistent and ongoing information may have an impact on attitudes, although how and where to convey this information is an unresolved question, given how siloed Americans are in their information-seeking.

Some limitations to the study should be noted. First, because the study used cross-sectional data, we could not draw causal inferences. For instance, we could not answer exactly why the difference in immigration attitudes toward Hispanics was due to aging effect or cohort effect. Second, we were not able to determine whether the moderating effect of framing was temporal or more enduring because respondents answered the survey questions right after they read the priming statements. Although different framing had a modest impact on attitudes among different age groups, it is not clear how long the more supportive attitudes would remain, and what the impact would be on increases in the dose of accurate information as well as for a longer timeframe of repeat messaging. Third, the data were collected before the COVID-19 pandemic; given the profound impact of the pandemic on the social narrative of immigrants and immigration, attitudes may have changed. The data were also collected before the border, and U.S. immigration policies moved more strongly to center stage as an election issue (J. M. Jones, 2024). Fourth, it is possible that respondents were unable to distinctly consider Hispanic immigrants while taking the survey, and that their responses also reflect their sentiments about U.S.-born Hispanics. However, any inability to separate these two groups would have resulted in an artificial reduction in the size of the effects, therefore not taking away from our findings on how immigration attitudes were shaped by age and framing. Fifth, we did not have a large enough sample to conduct a robust sub-analysis of the Hispanic respondents, to see if the relationship between framing statements and age was different among these individuals; this topic would be appropriate for exploration in a separate survey experiment.

We focused on two closely related but distinct aspects of immigration attitudes: attitude toward Hispanic immigrants and attitude toward immigration policies. Our findings underscored age as a significant factor in affecting immigration attitudes. Using a survey experiment approach, we investigated how exposure to different framings was associated with attitudes toward immigrants and immigration policies in three age groups. This study demonstrated the potential of using framing to impact immigration attitudes. It also provided a road map for additional research to explore this area, including how to tailor framing strategies for individuals with diverse backgrounds, with the goal of promoting diversity, equity, and inclusion in society.

Supplemental Material

sj-docx-1-hjb-10.1177_07399863241302228 – Supplemental material for Attitudes Toward Hispanic Immigrants and Immigration Policies in the United States: Exploring the Roles of Age and Framing Through a Survey Experiment

Supplemental material, sj-docx-1-hjb-10.1177_07399863241302228 for Attitudes Toward Hispanic Immigrants and Immigration Policies in the United States: Exploring the Roles of Age and Framing Through a Survey Experiment by Mengzhao Yan, Zachary Gassoumis, Kathleen Wilber, Sheila Salinas Navarro and Fernando Torres-Gil in Hispanic Journal of Behavioral Sciences

Footnotes

Data Availability

The data are available on the RAND American Life Panel at .

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 work was supported by the Ford Foundation.

ORCID iDs

Mengzhao Yan

Zachary Gassoumis

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Mengzhao Yan is a PhD Candidate at the Leonard Davis School of Gerontology of the University of Southern California. He is dedicated to studying how to optimize services, programs, and products to improve older people’s quality of life. He is interested in the sociology of aging and aging in place.

Zachary Gassoumis is an Assistant Professor of Research Family Medicine and Gerontology at the University of Southern California. His research focuses on improving the well-being of vulnerable populations, including minoritized groups, through improving our understanding of population characteristics, intervention efficacy, innovative programs, and policy impacts.

Kathleen Wilber is the Mary Pickford Foundation Chair in Gerontology and a Professor of Health Services Administration at the University of Southern California. Her research focuses on improving outcomes and quality of life for vulnerable older adults, including those with chronic illness, disability, cognitive impairment, and economic insecurity.

Sheila Salinas Navarro is a PhD Candidate at the Leonard Davis School of Gerontology of the University of Southern California. Her research interest is in economic security for the Latino/Hispanic immigrant communities living in the United States.

Fernando Torres-Gil is a Professor Emeritus of Social Welfare and Public Policy at UCLA, an Adjunct Professor of Gerontology at USC, and Director of the UCLA Center for Policy Research on Aging. He was appointed as the first-ever Assistant Secretary on Aging in the U.S. Department of Health and Human Services.

References

Alamillo

Haynes

Madrid

(2019). Framing and immigration through the trump era. Sociology Compass, 13(5), e12676. https://doi.org/10.1111/soc4.12676

Alba

(2018). What majority-minority society? A critical analysis of the census bureau’s projections of America’s demographic future. Socius, 4, 4. https://doi.org/10.1177/2378023118796932

Ayers

J. W.

Hofstetter

C. R.

Schnakenberg

Kolody

(2009). Is immigration a racial issue? Anglo attitudes on immigration policies in a border county. Social Science Quarterly, 90(3), 593–610. https://doi.org/10.1111/j.1540-6237.2009.00633.x

Batalova

Hanna

Levesque

(2021). Frequently requested statistics on immigrants and immigration in the United States. Migration Policy Institute. https://www.migrationpolicy.org/article/frequently-requested-statistics-immigrants-and-immigration-united-states-2020

Berg

J. A.

(2010). Race, class, gender, and social space: Using an intersectional approach to study immigration attitudes. Sociological Quarterly, 51(2), 278–302. https://doi.org/10.1111/j.1533-8525.2010.01172.x

Brader

Valentino

N. A.

Suhay

(2008). What triggers public opposition to immigration? Anxiety, group cues, and immigration threat. American Journal of Political Science, 52(4), 959–978. https://doi.org/10.1111/j.1540-5907.2008.00353.x

Calahorrano

(2013). Population aging and individual attitudes toward immigration: Disentangling age, cohort and time effects. Review of International Economics, 21(2), 342–353. https://doi.org/10.1111/roie.12040

Card

Chang

Becker

Mendelsohn

Voigt

Boustan

Abramitzky

Jurafsky

(2022). Computational analysis of 140 years of US political speeches reveals more positive but increasingly polarized framing of immigration. Proceedings of the National Academy of Sciences, 119(31), e2120510119. https://doi.org/10.1073/pnas.2120510119

Casas

J. M.

Cabrera

A. P.

(2011). Latino/a immigration: Actions and outcomes based on perceptions and emotions or facts? Hispanic Journal of Behavioral Sciences, 33(3), 283–303. https://doi.org/10.1177/0739986311416342

10.

Cavaille

Marshall

(2019). Education and anti-immigration attitudes: Evidence from compulsory schooling reforms across western europe. American Political Science Review, 113(1), 254–263. https://doi.org/10.1017/s0003055418000588

11.

CDC. (2008). Adding power to our voices: A framing guide for communicating about injury. https://stacks.cdc.gov/view/cdc/5487

12.

Chittamuru

Daniels

Sarkar

Schillinger

(2020). Evaluating values-based message frames for type 2 diabetes prevention among Facebook audiences: Divergent values or common ground? Patient Education and Counseling, 103(12), 2420–2429. https://doi.org/10.1016/j.pec.2020.08.042

13.

Chong

Druckman

J. N.

(2007). Framing theory. Annual Review of Political Science, 10(1), 103–126. https://doi.org/10.1146/annurev.polisci.10.072805.103054

14.

Cornelis

Van Hiel

Roets

Kossowska

(2009). Age differences in conservatism: Evidence on the mediating effects of personality and cognitive style. Journal of Personality, 77(1), 51–87. https://doi.org/10.1111/j.1467-6494.2008.00538.x

15.

Cowan

Martinez

Mendiola

(1997). Predictors of attitudes toward illegal Latino immigrants. Hispanic Journal of Behavioral Sciences, 19(4), 403–415. https://doi.org/10.1177/07399863970194001

16.

Cutler

S. J.

Kaufman

R. L.

(1975). Cohort changes in political attitudes: Tolerance of ideological nonconformity. Public Opinion Quarterly, 39(1), 69–81. https://doi.org/10.1086/268200

17.

Dancygier

R. M.

Donnelly

M. J.

(2013). Sectoral economies, economic contexts, and attitudes toward immigration. Journal of Politics, 75(1), 17–35. https://doi.org/10.1017/S0022381612000849

18.

Debrael

D’Haenens

De Cock

De Coninck

(2021). Media use, fear of terrorism, and attitudes towards immigrants and refugees: Young people and adults compared. International Communication Gazette, 83(2), 148–168. https://doi.org/10.1177/1748048519869476

19.

Doherty

Kiley

Johnson

(2018). Shifting public views on legal immigration into the U.S. Pew Research Center. https://www.pewresearch.org/politics/2018/06/28/shifting-public-views-on-legal-immigration-into-the-u-s/

20.

Dražanová

Gonnot

Heidland

Krüger

(2022). Understanding differences in attitudes to immigration: A meta-analysis of individual-level factors (No. 2235, Kiel Working Paper). http://hdl.handle.net/10419/265507

21.

Druckman

J. N.

Peterson

Slothuus

(2013). How elite partisan polarization affects public opinion formation. American Political Science Review, 107(1), 57–79. https://doi.org/10.1017/S0003055412000500

22.

Dustmann

Preston

I. P.

(2007). Racial and economic factors in attitudes to immigration. B E Journal of Economic Analysis & Policy, 7(1), 1–39. https://doi.org/10.2202/1935-1682.1655

23.

Espenshade

T. J.

Calhoun

C. A.

(1993). An analysis of public opinion toward undocumented immigration. Population Research and Policy Review, 12(3), 189–224. https://doi.org/10.1007/bf01074385

24.

Esses

V. M.

(2021). Prejudice and discrimination toward immigrants. Annual Review of Psychology, 72, 503–531. https://doi.org/10.1146/annurev-psych-080520-102803

25.

Finseraas

Røed

Schøne

(2017). Labor market competition with immigrants and political polarization. Quarterly Journal of Political Science, 12(3), 347–373. https://doi.org/10.1561/100.00016109

26.

Foner

(1974). Age stratification and age conflict in political life. American Sociological Review, 39(2), 187–196. https://doi.org/10.2307/2094231

27.

Franssen

Dhont

Hiel

A. V.

(2013). Age-related differences in ethnic prejudice: Evidence of the mediating effect of right-wing attitudes. Journal of Community & Applied Social Psychology, 23(3), 252–257. https://doi.org/10.1002/casp.2109

28.

Fujioka

(2011). Perceived threats and Latino immigrant attitudes: How White and African American college students respond to news coverage of Latino immigrants. Howard Journal of Communications, 22(1), 43–63. https://doi.org/10.1080/10646175.2011.546743

29.

Galston

W. A.

(2024, February 8). The collapse of bipartisan immigration reform: A guide for the perplexed. Brookings. https://www.brookings.edu/articles/the-collapse-of-bipartisan-immigration-reform-a-guide-for-the-perplexed/

30.

Gil de Zúñiga

Correa

Valenzuela

(2012). Selective exposure to cable news and immigration in the US: The relationship between FOX News, CNN, and attitudes toward Mexican immigrants. Journal of Broadcasting & Electronic Media, 56(4), 597–615. https://doi.org/10.1080/08838151.2012.732138

31.

Glenn

N. D.

(1974). Aging and conservatism. Annals of the American Academy of Political and Social Science, 415(1), 176–186. https://doi.org/10.1177/000271627441500113

32.

Goffman

(1974). Frame analysis: An essay on the organization of experience. Harvard University Press.

33.

Gorodzeisky

Semyonov

(2018). Competitive threat and temporal change in anti-immigrant sentiment: Insights from a hierarchical age-period-cohort model. Social Science Research, 73, 31–44. https://doi.org/10.1016/j.ssresearch.2018.03.013

34.

Hainmueller

Hiscox

M. J.

(2007). Educated preferences: Explaining attitudes toward immigration in Europe. International Organization, 61(02), 399–442. https://doi.org/10.1017/s0020818307070142

35.

Hainmueller

Hopkins

D. J.

(2014). Public attitudes toward immigration. Annual Review of Political Science, 17(1), 225–249. https://doi.org/10.1146/annurev-polisci-102512-194818

36.

Haynes

Merolla

Ramakrishnan

S. K.

(2016). Framing immigrants: News coverage, public opinion, and policy. Russell Sage Foundation.

37.

Heath

A. F.

Richards

(2020). Contested boundaries: Consensus and dissensus in European attitudes to immigration. Journal of Ethnic and Migration Studies, 46(3), 489–511. https://doi.org/10.1080/1369183x.2018.1550146

38.

Jones

J. M.

(2024, July 12). Sharply more Americans want to curb immigration to U.S. Gallup News. https://news.gallup.com/poll/647123/sharply-americans-curb-immigration.aspx

39.

Jones

Marks

Ramirez

Rios-Vargas

(2021, August 12). 2020 Census illuminates racial and ethnic composition of the country. Unities States Census Bureau. https://www.census.gov/library/stories/2021/08/improved-race-ethnicity-measures-reveal-united-states-population-much-more-multiracial.html

40.

Knoll

B. R.

Redlawsk

D. P.

Sanborn

(2011). Framing labels and immigration policy attitudes in the Iowa caucuses: “Trying to out-Tancredo Tancredo”. Political Behavior, 33(3), 433–454. https://doi.org/10.1007/s11109-010-9141-x

41.

Krogstad

J. M.

Passel

J. S.

Noe-Bustamante

(2022, September 23). Key facts about U.S. Latinos for National Hispanic Heritage Month. Pew Research Center. https://www.pewresearch.org/short-reads/2022/09/23/key-facts-about-u-s-latinos-for-national-hispanic-heritage-month/

42.

Lancaster

C. M.

(2022). Value shift: Immigration attitudes and the sociocultural divide. British Journal of Political Science, 52(1), 1–20. https://doi.org/10.1017/s0007123420000526

43.

Lee

(2006). A nation of immigrants and a gatekeeping nation: American immigration law and policy. A Companion to American Immigration, 5–35. https://doi.org/10.1002/9780470997116.ch2

44.

Lichter

D. T.

(2013). Integration or fragmentation? Racial diversity and the American future. Demography, 50(2), 359–391. https://doi.org/10.1007/s13524-013-0197-1

45.

Lopez

M. H.

Passel

Roha

(2015, September 28). Modern immigration wave brings 59 million to U.S., driving population growth and change through 2065. Pew Research Center. https://www.pewresearch.org/hispanic/2015/09/28/modern-immigration-wave-brings-59-million-to-u-s-driving-population-growth-and-change-through-2065/

46.

Lyons

P. A.

Coursey

L. E.

Kenworthy

J. B.

(2013). National identity and group narcissism as predictors of intergroup attitudes toward undocumented Latino immigrants in the United States. Hispanic Journal of Behavioral Sciences, 35(3), 323–335. https://doi.org/10.1177/0739986313488090

47.

Mayda

A. M.

(2006). Who is against immigration? A cross-country investigation of individual attitudes toward immigrants. Review of Economics and Statistics, 88(3), 510–530. https://doi.org/10.1162/rest.88.3.510

48.

McLaren

Paterson

(2020). Generational change and attitudes to immigration. Journal of Ethnic and Migration Studies, 46(3), 665–682. https://doi.org/10.1080/1369183x.2018.1550170

49.

Merolla

Ramakrishnan

S. K.

Haynes

(2013). “Illegal,” “undocumented,” or “unauthorized”: Equivalency frames, issue frames, and public opinion on immigration. Perspectives on Politics, 11(3), 789–807. https://doi.org/10.1017/s1537592713002077

50.

Nisbet

M. C.

(2016). The ethics of framing science. In Nerlich

Elliott

Larson

(Eds.), Communicating biological sciences (pp. 51–74). Routledge.

51.

Peterson

J. C.

Smith

K. B.

Hibbing

J. R.

(2020). Do people really become more conservative as they age? Journal of Politics, 82(2), 600–611. https://doi.org/10.1086/706889

52.

Pollard

M. S.

Baird

(2017). The RAND American life panel: Technical description. RAND. https://www.rand.org/pubs/research_reports/RR1651.html

53.

Reny

Manzano

(2016). The negative effects of mass media stereotypes of Latinos and immigrants. Media and minorities, 4(2), 195–212. https://doi.org/10.13109/9783666300882.195

54.

Reyna

Dobria

Wetherell

(2013). The complexity and ambivalence of immigration attitudes: Ambivalent stereotypes predict conflicting attitudes toward immigration policies. Cultural Diversity & Ethnic Minority Psychology, 19(3), 342–356. https://doi.org/10.1037/a0032942

55.

Riley

M. W.

(1971). Social gerontology and the age stratification of society. Gerontologist, 11(1 Part 1), 79–87. https://doi.org/10.1093/geront/11.1_part_1.79

56.

Rowatt

W. C.

Al-Kire

R. L.

Dunn

Leman

(2020). Attitudes toward separating immigrant families at the United States–Mexico border. Analyses of Social Issues and Public Policy, 20(1), 118–142. https://doi.org/10.1111/asap.12198

57.

Rustenbach

(2010). Sources of negative attitudes toward immigrants in Europe: A multi-level analysis. International Migration Review, 44(1), 53–77. https://doi.org/10.1111/j.1747-7379.2009.00798.x

58.

Ryder

N. B.

(1985). The cohort as a concept in the study of social change. In Mason

W. M.

Fienberg

S. E.

(Eds.), Cohort analysis in social research (pp. 9–44). Springer.

59.

Schmeltz

(2014). Introducing value-based framing as a strategy for communicating CSR. Social Responsibility Journal, 10(1), 184–206. https://doi.org/10.1108/srj-06-2012-0065

60.

Schotte

Winkler

(2018). Why are the elderly more averse to immigration when they are more likely to benefit? Evidence across countries. International Migration Review, 52(4), 1250–1282. https://doi.org/10.1177/0197918318767927

61.

Stephan

W. G.

Ybarra

Bachman

(1999). Prejudice toward Immigrants1. Journal of Applied Social Psychology, 29(11), 2221–2237. https://doi.org/10.1111/j.1559-1816.1999.tb00107.x

62.

Tilley

Evans

(2014). Ageing and generational effects on vote choice: Combining cross-sectional and panel data to estimate APC effects. Electoral Studies, 33, 19–27. https://doi.org/10.1016/j.electstud.2013.06.007

63.

Tirado-Espín

Cuesta

Martínez-Martínez

Almeida-Galárraga

(2021). Framing and immigration: New frames in media and social networks [Conference session]. International Conference on Communication and Applied Technologies. https://doi.org/10.1007/978-981-16-5792-4_15

64.

Torres-Gil

J. F.

Demko

(2019). The politics of aging and diversity: Moving toward a majority-minority nation. Generations, 42(4), 57–64. https://www-jstor-org-443.web.bisu.edu.cn/stable/26608430

65.

U.S. Census Bureau. (2018, October 9). Hispanic population to reach 111 million by 2060. Author. https://www.census.gov/library/visualizations/2018/comm/hispanic-projected-pop.html

66.

Valentino

N. A.

Brader

Jardina

A. E.

(2013). Immigration opposition among US whites: General ethnocentrism or media priming of attitudes about Latinos? Political Psychology, 34(2), 149–166. https://doi.org/10.1111/j.1467-9221.2012.00928.x

67.

Valentova

Alieva

(2014). Gender differences in the perception of immigration-related threats. International Journal of Intercultural Relations, 39, 175–182. https://doi.org/10.1016/j.ijintrel.2013.08.010

68.

Vrânceanu

(2022). How do cross-pressures affect immigration attitudes? Party and educational influences. West European Politics, 45(7), 1433–1461. https://doi.org/10.1080/01402382.2021.1975447

69.

Young

M. T.

Sarnoff

Lang

Ramírez

A. S.

(2022). Coverage and framing of immigration policy in US newspapers. Milbank Quarterly, 100(1), 78–101. https://doi.org/10.1111/1468-0009.12547

70.

Zong

(2022). A mosaic, not a monolith: A profile of the U.S. Latino population, 2000-2020. UCLA Latino Policy Institute. https://latino.ucla.edu/research/latino-population-2000-2020/

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