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28-01-2016 | Original Paper

Rolling off the Tongue into the Top-of-the-Head: Explaining Language Effects on Public Opinion

Author: Efrén O. Pérez

Published in: Political Behavior | Issue 3/2016

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Abstract

Growing evidence shows that mass opinion varies by interview language, yet modest theory exists to explain this result. I propose a framework where language impacts survey response by making some political concepts more mentally accessible. I claim that concepts vary by how associated they are with certain languages, which means people are more likely to acquire a construct when it is tied to the tongue one speaks. Hence, recalling concepts from memory should be easier when the language a construct is linked to matches the tongue one interviews in, thereby intensifying people’s opinions. I test my theory by manipulating the interview language in two U.S. surveys of English/Spanish bilingual Latino adults. I generally find that language influences the accessibility of concepts. For example, subjects report higher opinion levels for concepts that are tied more to their interview language, such as American identity among English interviewees. Subjects who interview in English are also less likely to refuse completing items measuring knowledge about U.S. politics, and more likely to answer them quickly. Items reflecting constructs that are highly labile (e.g. anti-Obama affect) or very crystallized (e.g., partisanship) do not display these patterns. I then rule out that language effects are mostly mediated by a heightened sense of anxiety, anger, pride or efficacy that emerges when bilingual subjects interview in one of their languages.

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In turn, “hubristic” pride results from attributions to internal, stable, uncontrollable causes (e.g., I won because I’m always great). I focus on “authentic” pride because respondents do control the concepts they retrieve and use to form opinions.

Stereotype threat might also mediate the impact of language via depletion of people’ executive functioning (Steele et al. 2002), a possibility that future research should further explore.

37 % of subjects report usually completing GfK surveys in Spanish, while 63 % usually complete them in English.

31 % of subjects report usually completing GfK surveys in Spanish, while 69 % usually complete them in English.

Subjects completed these items when they first enrolled to GfK’s respondent panel. As might be expected (Abrajano and Alvarez 2010; Alba and Nee 2003), about half of bilinguals in both samples are foreign-born and Mexican origin, with the median education in both samples being “some college.” See table A in the supporting information (SI) for more characteristics and any nuances between them across samples.

Table B (SI) reports a non-linear regression predicting assignment to an experimental condition as a function of several covariates, suggesting my treatment was effectively randomized. Table C (SI) shows these covariates are balanced across my experimental cells. These results imply that my bilingual respondents are alike in all respects, save for the interview language treatment.

A full comparison of both treatments can be found in table D (SI).

The response times I analyze are indexed in seconds, rather than milliseconds, because GfK can only collect response times in seconds at this time. This will make it harder to uncover any accessibility effects by language.

For Study 1: Latino identity (α = .54); National origin identity (α = .86); American identity (α = .81). For Study 2: Latino identity (α = .54); National origin identity (α = .87); American identity (α = .74).

In both studies, most of the concepts that I measure are theorized to be linked to English. I did this by design, since U.S. polls typically ask about American constructs, which are tied to English. Still, as I describe in the text, I measure one Spanish-linked construct often asked about in U.S. academic surveys (i.e., national origin identity), and designed two items tapping knowledge about Latin American history in order to better test my hypotheses.

Since my knowledge items are dichotomous, I report average tetrachoric correlations (rho) rather than alphas (α). For Study 1: Traditional U.S. knowledge (average rho = .58); Latino knowledge (average rho = .54).

For Study 2: Traditional U.S. knowledge (average rho = .37); Latin American knowledge (average rho = .53).

One might expect these items to precede my opinion measures. But asking people about their efficacy and emotions right after my language manipulation risks an artificial increase in the correlation between interview language and emotions, which works against finding mediation effects (e.g., the more variance in anxiety that interview language explains, the less variance in anxiety to explain opinions). Also, gauging opinions should have a trivial effect on measuring efficacy and emotion, since any sense of these has already occurred by the time opinions are reported.

The point of these efforts, then, is not to create translations that are exact in length, word for word. Such a strategy is likely to yield translations of similar length, but with different and often grammatically incorrect meanings (Jacobson et al. 1960). Instead, the aim is to develop translated items that mean the same thing to different people (Pérez 2009).

Indeed, scholars regularly find that Latino identity is more widespread among individuals who have deeper roots in the U.S. and are more conversant in English (Portes and Rumbaut 2006; Abrajano and Alvarez 2010), suggesting a relatively stronger tie between it and the English language.

Although I use a regression approach to estimate my treatment effects, t-tests yield comparable results.

I use one-tailed tests given the explicitly directional nature of my main hypothesis (H1), as well as accumulated lab work showing accessibility effects in specific directions on cognitive outcomes, such as answering questions.

Reflecting prior research (Ross et al. 2002, p. 1041), these findings are largely inconsistent with a social desirability explanation. For example, if social desirability was responsible for these opinion gaps, we should have observed English interviewees express weaker (not stronger) Latino identity than Spanish interviewees.

I used a 30 s threshold for answering knowledge items in Study 1 in order to keep this analysis consistent with an identical one using knowledge items from Study 2, where subjects were explicitly given 30 s to answer each knowledge item. As my analysis will show, knowledge item RTs in Study 1 are largely unaffected by slow responders.

I study refusal rates rather than “don’t know” (DK) rates because people offer DKs for many reasons, including (a) not fully knowing an answer (b) incompletely knowing an answer (Gibson and Caldeira 2009); (c) refraining from guessing an answer (Mondak 2001); and (d) being unmotivated to try answering correctly (Prior and Lupia 2008). Refusal rates are less affected by these problems, so I use them to test my accessibility hypothesis.

Indeed, in Study 1, the two items measuring American identity were positively worded. Not surprisingly in hindsight, the estimated intercept for American identity in Study 1 was about .75, which suggests a high degree of this attachment among Spanish interviewees, making it harder for English interviewees to report an even higher level of this attachment.

This estimate is from an ordered probit model. The three knowledge scale items were: “Whose responsibility is it to determine if a law is constitutional or not?”; “How much of a majority is required for the US Senate and House to override a presidential veto?”; and “How long is the term of office for a United States Senator?”.

Specifically, I estimated an ordered probit model with the following coefficients: Latin American knowledge = −.144 English + .110 > 30 s + .613 English x > 30 s + .464 Education + .015 Age.

Indeed, in both Study 1 and 2 the intercept for this construct is above .80 on a 0–1 range.

Although limited in number, the two reliable RT differences by interview language in Table 2 weakly impact people’s survey responses, further hinting at the role of accessibility in producing these results (see Table E, SI).

Since my RR variables have much more limited variation than my RT scores, I do not further examine whether RR differences subsequently impact knowledge reports.

One might reasonably wonder whether an emotion like pride is conceptually and empirically synonymous with group consciousness, linked fate, or solidarity, since all of these reflect positive feelings to a degree (Dawson 1994; McClain et al. 2009; Sanchez 2006; Leach et al. 2008). True, group attachments can induce pride and other emotions in group members (Mackie et al. 2008). But my conceptualization and measure of pride focus on this feeling among individuals and what each person accomplishes during an interview. Still, I would expect, but cannot test here, that language impacts people’s sense of group consciousness, linked fate, and/or solidarity insofar as these flow from a specific group identity.

A better strategy here is to design a sufficiently powered experiment that blocks subjects’ assigned interview language on their PL or IG, thus retaining the experiment’s causal leverage. I leave this possibility open for future research.

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Title: Rolling off the Tongue into the Top-of-the-Head: Explaining Language Effects on Public Opinion
Author: Efrén O. Pérez
Publication date: 28-01-2016
Publisher: Springer US
Published in: Political Behavior / Issue 3/2016
Print ISSN: 0190-9320
Electronic ISSN: 1573-6687
DOI: https://doi.org/10.1007/s11109-015-9329-1

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