Foreign funding of U.S. higher education relates to sanctioning of scholars and antisemitism

We examined relations between foreign funding of U.S. colleges and universities and campus political developments. Seven studies investigated associations between foreign funding and campus liberal democratic norms, specifically, deterioration of free speech and academic freedom, and presence of antisemitism. Study I found that 349 colleges and universities received a total of almost $18 billion from foreign sources between 2014 and 2019. Study II examined relationships of foreign funding to campus deplatforming of speakers and punitive actions for speech protected by academic freedom. Main results were: 1. overall foreign funding was not strongly related to campus speech outcomes; 2. higher levels of deplatforming and speech punishment occurred on campuses that received funding from member states of the Organization of Islamic Cooperation and from authoritarian countries. Study III found weak evidence that foreign funding was associated with college students' reported exposure to antisemitic and anti-Zionist tropes. After demonstrating substantial correlations among three national measures of antisemitic incidents (Study IV), Study V found that foreign funding provided by member countries of the Organization for Islamic Cooperation or by authoritarian countries was associated with elevated levels of campus antisemitism and anti-Zionist incidents. Studies VI and VII found that antisemitic incidents on campus were associated with antisemitic incidents across the country. This research highlighted troubling possibilities about the potential role of foreign funding in higher education that deserve further investigation.

1 Introduction: widespread failure to report donations from foreign sources

American institutions of higher education receive billions of dollars in foreign funding each year. Much of this funding has not, historically, been reported to the U.S. Department of Education as required by law. In this paper, we present seven studies addressing a range of issues related to this funding. Study I describes the methods and results of the investigative accounting used to uncover the extent of unreported foreign funding. Studies II through VI address the relationship of this funding to campus liberal democratic practices regarding free speech, academic freedom, and antisemitism. Study VII addresses relations between campus antisemitism and antisemitic incidents in the rest of the country.

In July 2019, Small and Bass (2019) presented to the U.S. Department of Justice (DOJ) the results of investigative research into the foreign funding of American colleges and universities. This presentation detailed extensive funding by foreign governments, foundations, and corporations, all of which adhere to and promote authoritarian and antisemitic ideologies. Specifically, Small and Bass (2019) reported uncovering billions of dollars coming from Qatar to U.S. colleges and universities that had not previously been reported to the U.S. Department of Education (DoEd) as required by law.

This reporting anomaly captured the attention of lawmakers. An investigation was conducted by the U.S. federal government, including numerous presentations and testimonies involving U.S. officials from the DoEd (Camera, 2020; Dennett, 2019). The DoEd investigation discovered $6.5 billion in previously unreported foreign funding (U.S. Department of Education, 2020). Updated DoEd reporting found that significant amounts of funding originated from Middle Eastern countries and authoritarian regimes hostile to fundamental principles of democracy and human rights (Small and Bass, 2020). The studies presented here examined the relationship between the foreign funding reported thus far and both democratic norms and antisemitism in U.S. institutions of higher education.

Given the historical lack of transparency in reporting the receipt of foreign funding on the part of institutions of higher education, it is possible that additional such funding will be disclosed in the future. But throughout this paper, we use the term “Section 117 funding” to refer to funds that were, as of September 2020, disclosed as having been received between 2014 and 2019 in accordance with this requirement:

Section 117 of the Higher Education Act of 1965 (HEA) requires institutions of higher education that receive federal financial assistance to disclose semiannually to the U.S. Department of Education any gifts received from and contracts with a foreign source that, alone or combined, are valued at $250,000 or more in a calendar year. The statute also requires institutions to report information when owned or controlled by a foreign source. (U.S. Department of Education, n.d.).

2 Funding, authoritarianism, liberal democratic norms, and antisemitism

American institutions of higher education have many goals, including the production of new knowledge through scholarship. Knowledge-production is built on a foundation of liberal democratic norms, including free speech, academic freedom, and free inquiry—sometimes referred to as the open society (Popper, 1945/2020). Many have argued that these norms comprise a critical foundation for both scientific discovery and addressing controversial social issues (e.g., Mill, 1859; Rauch, 1993; University of Chicago, 2014). These values are antithetical to authoritarianism whether of the political right (e.g., Altemeyer, 1996; Yourman, 1939) or left (e.g., Costello et al., 2022; Dikötter, 2016). Whether Section 117 funding, especially from authoritarian regimes, is involved in the erosion of support for the open society on U.S. college and university campuses is an open question. Accordingly, one of the central purposes of the present research is to address this question.

While prior generations of authoritarian governments relied more strictly on overt punishment and censorship, modern authoritarianism often relies on strategies that appear less obtrusive. “Informational autocracy” refers to the use of political power to control the flow of information in such a manner as to maintain false impressions of competence, honesty, and effectiveness of those in power, and to censor, demonize, or delegitimize elites or the public who oppose them (Guriev and Treisman, 2020). If successful, this form of soft authoritarianism maintains popular support, can remain in power for long periods, and, eventually, undermines democracy (Krekó, 2022). A facade of democratic elections can be maintained by enlisting observers of dubious credibility from supporting outside regimes, as has been done in Hungary (Krekó, 2022).

Another manifestation of soft authoritarianism that also involves information control and manipulation has been referred to as “networked authoritarianism.” Internationally, networked authoritarianism functions to advance goals analogous to information autocracy with one crucial difference: the goal is to advance regime interests abroad by strengthening its foreign supporters and weakening its foreign opponents. This can be done by providing rhetorical support through information networks (such as social media, including the use of bots programmed to disseminate disinformation and sow division among regime opponents) and/or by providing financial support to those in other countries who are aligned with regime interests (Kalathil, 2020; Maréchal, 2017).

Authoritarianism, both at the individual psychological level and among government actors, is often associated with antisemitism (Altemeyer, 1981). The most obvious recent historical cases are Nazi Germany, the Soviet Union, and Islamist regimes. A growing body of literature addresses a possible connection between funding from Islamic authoritarian regimes that hold anti-Israel views, and on-campus antisemitism. Elman and Romirowsky (2019, p. 230) wrote:

In the United States over the last decades large sums of money from the United Arab Emirates, Qatar, and Saudi Arabia have been pumped into the humanities and social sciences through chairs, grants, and fellowships, dictating what Middle East-related courses are taught and the kinds of extracurricular programming that is offered. Strapped for funds and eager to promote international and multicultural studies, many campuses have readily accepted this support despite the implicitly anti-American agendas that they bring.

Unfortunately, much of the work on this subject (e.g., Cravatts, 2011; Fishman, 2012) is a strange mix of empirical claims clouded by polemics and accusations. Criticism of universities for taking donations from Middle Eastern, Islamic, and authoritarian sources has become politicized and often lacks evidentiary support. Nonetheless, a question that can and should be addressed empirically is this: Is there a relationship between funding from authoritarian regimes and campus illiberalism and antisemitism?

2.1 Research questions

Although the present research was exploratory, there are good theoretical reasons to expect relationships between Section 117 contributions and illiberal trends in American institutions of higher education. We examined two potential aspects of campus life in which receipt of Section 117 contributions may be involved: 1. erosion of free speech and academic freedom, and 2. antisemitism.

How might this work within universities? First, Section 117 money may be used to facilitate an intolerant intellectual environment on campus, one with higher levels of deplatforming, more calls for punishing speech and expression, and endorsement of censorship. Second, the money might be used to support and expand the work of faculty or students who are willing to violate others' speech rights. Third, the money might be used to support antisemitic extremist groups on campus and/or groups whose activities spill over into violation of others' speech rights. Fourth, it might buy a sort of soft influence—the institutional administration or whoever is receiving the funds might become more sympathetic to the interests and ideological agendas of the donor.

The above analysis is speculative and describes the types of processes that should be further investigated, pending empirical answers to the research questions driving the present set of studies. Nonetheless, there are some real-world reasons to believe such processes may already be occurring. For example, the Communist Party of China (CCP) funds Confucius Institutes throughout higher education, ostensibly to advance the study of Chinese languages, history and culture. In fact, however, these institutes constitute a major CCP propaganda effort, which includes suppressing speech and discourse around issues embarrassing to the CCP (e.g., Uyghurs, Tiananmen Square, Tibet and Taiwan; Human Rights Foundation, 2021). The research reported herein can be viewed as a preliminary attempt to determine whether this type of report constitutes anything more than a rare anecdote or something more pervasive and systematic.

The flood of Section 117 funding described herein coincides with both increased illiberal, anti-democratic sentiment on American college and university campuses (Rauch, 1993; Stevens, 2022, 2023) and antisemitic incidents (Beckwith and Rossman-Benjamin, 2022). The research reported herein provides the first effort to quantitatively examine the potential relationship between Section 117 funds, anti-democratic trends, and levels of antisemitism on American college and university campuses. Specifically, the present work investigates the following questions:

1. Is receipt of Section 117 funding per se, regardless of source, associated with increased illiberal, anti-democratic behaviors involving campus censorship and suppression of academic freedom?

2. Is receipt of Section 117 funding from member countries of the Organization for Islamic Cooperation and authoritarian regimes associated with more illiberal, anti-democratic behaviors involving campus censorship and suppression of academic freedom?

3. Is receipt of Section 117 funding per se, regardless of source, associated with higher levels of antisemitic activity on those campuses?

4. Is receipt of Section 117 funding from member countries of the Organization for Islamic Cooperation and authoritarian regimes associated with more campus antisemitic activity than contributions from other countries?

5. Is campus antisemitism associated with incidents of regional and national antisemitic activity?

3 Data and methods common across multiple studies

3.1 Data sources and aggregation

The data sources drawn upon include:

1. Investigative research from the DoEd by Michael Bass, CPA, for the Network Contagion Research Institute (NCRI) on Section 117 funding to campuses (see Supplementary Tables S1, S2). These data were based on funding uncovered as of September 23, 2020. However, because much such data went unreported and investigations are ongoing, it is possible that additional previously undisclosed foreign contributions may be uncovered.

2. Information on antisemitic hate crimes in the Federal Bureau of Investigation's (FBI, n.d.) Uniform Crime Reporting database.

3. The Anti-Defamation League (ADL, n.d.) Antisemitic Incident Tracker.

4. Antisemitic incident data from the AMCHA Initiative (n.d.-a).

5. Some analyses involve funding from other authoritarian sources. We operationalize this as the top 30 most authoritarian countries in the world, plus Russia (see Supplementary Table S4 for the list of authoritarian countries). This is based on The Economist Intelligence Unit's (2017) Democracy Index. Even though authoritarianism is a matter of degree, for simplicity of presentation, and because we dichotomized countries in this manner, we refer to these as “authoritarian” countries and the others as “non-authoritarian” countries.

6. Some analyses involve funding from member countries of the Organization of Islamic Cooperation (OIC, n.d.). The full list of countries appears in Supplementary Table S3, as well as which countries provided Section 117 funding. Most majority Muslim countries score poorly on both the Democracy Index and on measures of anti-Zionism and antisemitism (Tausch, 2014). The partial correlation (controlling for economic development) of membership in the OIC and antisemitism was over 0.7. Although this relationship disappeared in an analysis controlling for other indicators related to Islam (Muslim proportion of population, membership in the Arab League, both of which predicted antisemitism): a. The overall picture remains that of a heavily Islamic country scoring high in antisemitism; b. Tausch's research involved different outcome variables than the present research (Tausch studied antisemitism within those countries, whereas our research examines both erosion of norms around academic freedom and antisemitism in the U.S.); and c. most member countries in the OIC also score low in the Democracy Index. By using membership in the OIC, the present exploratory research intentionally casts a wide net.

3.2 Antisemitism and anti-Zionism

We employ simple, straightforward definitions of antisemitism and anti-Zionism in the present paper. Antisemitism refers to prejudice or discrimination against Jews, individually or collectively (for related definitions and perspectives, see Allington et al., 2023; Cohen et al., 2009; Kaufman et al., 2020). This may manifest in a myriad of ways, including but not restricted to open hostility, covert hostility, belief in conspiracy theories involving Jews, holding unjustified derogatory beliefs about Jews, hate crimes against Jews, harassing people because they are Jewish, etc.

Zionism refers to the movement to establish and maintain a Jewish state in Israel. As such, anti-Zionism refers to hostility toward and opposition to Israel as a Jewish state. Antisemitism and anti-Zionism, therefore, are, conceptually, clearly distinguishable. Empirically, however, they have been found to correlate at about r = 0.40 (Allington et al., 2023; Cohen et al., 2009) which means there is about a 70% chance that, people who score in the upper half of one measure, will also score in the upper half of the other (Rosenthal and Rubin, 1982).

For incidents of antisemitism on campus, in this report, we use the term “Expression” to refer to AMCHA's recording of expressions of antisemitism that do not target particular students or Jewish institutions, such as episodes of antisemitic graffiti, slogans, and chants. We use the term “Targeting” to refer to AMCHA's reporting of incidents of antisemitism on campus that target specific students (e.g., harassment) and institutions (e.g., defacing a Hillel). Some analyses also rely on AMCHA data on activities involving the anti-Zionist Boycott, Divestment, and Sanctions (BDS) movement on campus. The question of whether BDS activities are antisemitic is contentious. Resolving this question is beyond the scope of the present paper. Therefore, we present anything involving BDS as “antisemitic/anti-Zionist” to capture the idea that it is one, the other, or both. The empirical question relevant to the present research is whether foreign funding is associated with heightened BDS activity, and we leave it to others to decide for themselves whether such activity is antisemitic, anti-Zionist, or both. Determining correlations between support for BDS and hostility toward Jews was beyond the scope of the present studies, though it is an interesting and important question for future research.

4 Study I: Section 117 funding

The main purpose of Study I was to determine the Section 117 funding that U.S. institutions of higher learning received from foreign governments from 2014 to 2019. This timeframe is used because it is the timeframe covered by the prior U.S. Department of Education investigations (Camera, 2020; Dennett, 2019).

4.1 Methods

From 1981 to 2020, the DoEd hosted a portal for foreign funding of American institutions of higher education. This portal made publicly available the amount of foreign funding received by those institutions as they reported it to the DoEd. From 2014 to 2019, Michael Bass downloaded the information as it became available (twice per year) and consolidated the new reporting information with all previous information. Starting in 2020, the DoEd changed the portal mechanism, so that it now includes all information since 1981 (U.S. Department of Education, n.d.).

4.2 Results and discussion

Between 2014 and 2019, 349 U.S. colleges and universities received Section 117 funding from 158 foreign countries. The total sum across all universities and years was $17,961,986,172. Table 1A shows the top 10 countries contributing this type of funding to U.S. institutions of higher education during this time period. Table 1B shows the 10 universities that received the most Section 117 funding during this time period. Supplementary Tables provide full data on all countries and institutions. Supplementary Table S1 reports how much Section 117 funding had been donated by each of the 158 countries to U.S. institutions of higher education. Supplementary Table S2 lists the amounts of Section 117 funding received by each of the 349 institutions of higher education during this time period. The values obtained in Study I (see Supplementary Table S2) are used in all subsequent studies assessing the relationship of Section 117 funding to other outcomes.

Table 1A

Table 1A. (Study I) Countries providing the highest levels of Section 117 funding to U.S. institutions of higher education, 2014-2019.

Table 1B

Table 1B. (Study I) U.S. institutions of higher education receiving the highest levels of Section 117 funding, 2014–2019.

5 Study II: Section 117 funding and anti-democratic activity on American college campuses

The Foundation for Individual Rights and Expression (FIRE) empirically assesses failures of colleges and universities to support free speech and academic freedom in a variety of ways. One is by maintaining a database of Scholars Under Fire (FIRE, n.d.-a). This tracks outcomes of campaigns to sanction academics for speech that should be protected by either the First Amendment (for state colleges and universities) or contractual commitments to academic freedom. Another, the Campus Deplatforming database (FIRE, n.d.-b), tracks outcomes of deplatforming attempts to disinvite speakers from campus, cancel performances (e.g., concerts, plays, screenings of movies), or have controversial artwork removed from public display. These databases and their full methodologies are publicly available on FIRE's website.

Research by FIRE indicates that attempts to sanction scholars and disinvite speakers have increased sharply in recent years on college campuses (Lukianoff and Schlott, 2023). This suggests a decline in support for liberal democratic norms among students and faculty (Honeycutt and Jussim, 2023; see also Stevens and Haidt, 2018). Because attempts to sanction scholars or disinvite speakers can be considered types of anti-democratic behavior, the present study examined whether these attempts were associated with receipt of foreign funding. Accordingly, we merged FIRE's Scholars Under Fire and Campus Deplatforming databases with our own database on Section 117 funds.

We examined the question of whether simply having received foreign funding was associated with erosion of liberal democratic norms by comparing campuses that received foreign funding with those that did not. We also investigated whether erosion of liberal democratic norms on campus was associated specifically with having received funding from regimes hostile to democratic norms. We examined this by comparing campuses that received funding from OIC member countries with those that did not, and by comparing campuses that received foreign funding from authoritarian regimes with those that did not. Accordingly, Study II examined six research questions:

Research Question 1: Is Receipt of Section 117 Funding Related to Erosion of Campus Liberal Democratic Norms Around Speech?

1a. Do institutions that received foreign funding have more Scholars Under Fire than institutions that did not receive foreign funding?

1b. Do institutions that received foreign funding have more deplatforming attempts than institutions that did not receive foreign funding?

Research Question 2: Is Receipt of Section 117 Funding from OIC Member Countries Related to Campus Erosion of Liberal Democratic Norms Around Speech?

2a. Do institutions that received foreign funding from OIC member countries have more Scholars Under Fire than do institutions that received foreign funding from other countries?

2b. Do institutions that received foreign funding from OIC member countries have more deplatforming attempts than do institutions that received foreign funding from other countries?

Research Question 3: Is Receipt of Section 117 Funding from Authoritarian Regimes Related to Campus Erosion of Liberal Democratic Norms Around Speech?

3a. Do institutions that received foreign funding from the most authoritarian countries, compared to those that received funding from other countries, have more Scholars Under Fire than do institutions that received foreign funding from other countries?

3b. Do institutions that received foreign funding from the most authoritarian regimes, compared to those that received funding from other countries, have more deplatforming attempts than do institutions that received foreign funding from other countries?

5.1 Methods

This study assessed relations between receipt of Section 117 funds and FIRE data on Scholars Under Fire and campus deplatforming attempts (FIRE, n.d.-a,b) for 2014–2023.¹

The relevant information from FIRE databases that we included was as follows:

• The school at which the scholar came under fire or the deplatforming attempt occurred.

• The number of incidents reported at institutions listed by FIRE in both databases.

Supplementary Table S3 provides the list of OIC member countries that provided Section 117 funding. Supplementary Table S4 provides the list of authoritarian countries that provided Section 117 funding.

5.2 Results and discussion

There were 986 Scholars Under Fire and 771 deplatforming attempts between 2014 and 2023 (summarized by year in Table 2).

Table 2

Table 2. (Study II) FIRE data by year.

5.2.1 Main analysis overview

Our first research question involved comparing institutions that received Section 117 funding to those that did not. Our second and third research questions were restricted to institutions that received funding from OIC member countries and authoritarian regimes, respectively. However, some OIC member countries are also on the list of authoritarian countries. Because of these overlapping categories, we could not use ANOVA in our analyses.

Regression techniques were deemed inappropriate because the same dollar figure did not necessarily mean the same thing to different institutions. For example, a $500,000 grant to a major university with a $1 billion yearly budget does not necessarily mean the same thing as a $500,000 to a small liberal arts college.

Countries were categorized into three pairs of two groups for three separate comparisons. The first comparison assessed differences between institutions that did vs. did not receive Section 117 funding; the second assessed differences between institutions that received Section 117 funding from OIC vs. other countries; the third assessed differences between institutions that received Section 117 funding from authoritarian vs. other countries.

We did not compare dollar amounts. In several ways, grouping institutions as we did rendered our analyses more statistically conservative. First, our analyses ignored variability in the amount of funding received among those that received any funding at all. Second, the hypotheses were tested through a series of two group comparisons using Welch's t-tests. These are generally more conservative than conventional t-tests and permit comparisons even when some of the assumptions underlying the conventional t-test are not met (Delacre et al., 2017).

Because our outcomes are count variables, we considered using an alternative test statistic, such as the Mann Whitney U-test, which is a nonparametric analog to the t-test. However, with large samples such as ours, the Mann Whitney U produces far more false positives (statistically significant differences when there are none in the underlying population) than does the t-test, which has an error rate very close to alpha (e.g., 5% error rate at p ≤ 0.05; Fagerland, 2012). Therefore, rather than using the Mann Whitney U, we used the more conservative Welch's t-test, which adjusts for unequal variances by reducing the degrees of freedom.

We also considered using negative binomial regression, which is designed to handle distributions based on count variables. However, we rejected this as well, because negative binomial regression models are far more complex than t-tests (e.g., the coefficients they yield are exponents linking predictors to outcomes), and because a considerable body of statistical literature indicates that simple statistical techniques are generally more robust to specification errors, assumption violations, and are often more valid and replicable than more complex ones (e.g., Czerlinski et al., 1999; Dana and Dawes, 2004; Dawes, 1979). Dana and Dawes (2004), for example, found that when predicting future outcomes (winners of football games, weights of fish, political beliefs), simple correlation coefficients performed better than did regression coefficients. Writing in the Journal of Educational and Behavioral Statistics, their conclusion (abstract, p. 317) is worth quoting here: “It was concluded that regression is rarely useful for prediction in most social science contexts.” Furthermore, with large sample sizes (generally, N > 80), t-tests perform well even when variables are not normally distributed because the sampling distribution of means, which is all that is relevant, are normally distributed (Sainani, 2012).

The third way we were conservative in analyzing the data was by using p-values of < 0.01 rather than 0.05 as the threshold for considering differences as statistically credible. This is consistent with research (Open Science Collaboration, 2015) finding that results with p-values below 0.01 were much more likely to be replicable than those between 0.05 and 0.01.

5.2.2 Main analyses

Research Question 1: Is Receipt of Section 117 Funding Related to Erosion of Campus Liberal Democratic Norms Around Speech?

Our first set of analyses compared speech norms among campuses that received Section 117 funding with those that did not. These analyses provided weak and inconsistent evidence that institutions that received foreign funding had experienced an erosion in liberal democratic norms around speech (Table 3). There were more attempts to sanction scholars at institutions that received foreign funding (mean = 1.82) than those that did not [mean = 1.37; Welch's t_(420.8) = 2.44, p = 0.015], but this falls short of our 0.01 threshold for statistical significance and the effect size was small (d = 0.15). Similarly, deplatforming attempts at institutions that did not receive foreign funding (mean = 1.90) were nearly identical to those that did [mean = 1.82; Welch's t_(520.09) = 0.40, p = 0.69]. The best conclusion is that there is minimal evidence here that foreign funding, per se, is associated with erosion of liberal democratic norms around campus speech.

Table 3

Table 3. (Study II) Foreign funding: received vs. did not.

Research Question 2: Is Receipt of Section 117 Funding from OIC Member Countries Related to Campus Erosion of Liberal Democratic Norms Around Speech?

The next analysis examined whether norms around speech were different, depending on whether the source of Section 117 funding was from a source in an OIC member country or not. Therefore, we compared attempts to sanction scholars and deplatforming attempts at institutions that received funding from a source in an OIC member country to those that received funding from sources in any other foreign country (Table 4). There were, on average, more attempts to sanction scholars at institutions that received funding from OIC member countries (mean = 2.56) than at institutions that received funding from other foreign sources [mean = 0.80; Table 4; Welch's t_(263.39) = 6.42, p < 0.001, d = 0.52]. Similarly, there were more deplatforming attempts at institutions that received funding from OIC member countries (mean = 2.35) than at institutions that received funding from other foreign sources [mean = 1.23, Welch's t_(330.47) = 3.02, p < 0.003, d = 0.31]. Thus, the answer to Research Question 2 was “yes”: receipt of funding from OIC member countries was related to campus erosion of liberal democratic norms around speech.

Table 4

Table 4. (Study II) Funding source: OIC member countries vs. other countries.

Research Question 3: Is Receipt of Section 117 Funding from Authoritarian Regimes Related to Campus Erosion of Liberal Democratic Norms Around Speech?

The final Study II analyses examined whether norms around speech were different, depending on whether the source of Section 117 funding was an authoritarian country or not. Therefore, we compared attempts to sanction scholars and deplatforming attempts at institutions that received funding from a source in an authoritarian country to those that received funding from sources in any other foreign country (Table 5). There were, on average, more attempts to sanction scholars at institutions that received funding from authoritarian regimes (mean = 2.23) than at institutions that received funding from other foreign sources [mean = 0.80, Welch's t_(343.04) = 5.22, p < 0.001, d = 0.45]. Similarly, there were more deplatforming attempts at institutions that received funding from authoritarian regimes (mean = 2.16) than at institutions that received funding from other foreign sources [mean = 1.26, Welch's t_(262.25) = 2.51, p = 0.0125, d = 0.22]. Thus, the answer to Research Question 3 was “yes”: receipt of funding from the most authoritarian sources was related to campus erosion of liberal democratic norms around speech.

Table 5

Table 5. (Study II) Funding source: authoritarian countries vs. other countries.

Receipt of foreign funding, overall, was largely unrelated to erosion of liberal democratic norms around speech and academic freedom, as measured by FIRE's Scholars Under Fire and Campus Deplatforming databases. However, receipt of funding from either OIC member countries or authoritarian countries was related to such erosion.

There are, however, several important limitations and qualifications to this study. First, we have no evidence on why these relationships exist. Put differently, we have no information about the social, organizational, economic, or political processes by which these relationships come about. The main contribution of Study II is discovering that these relationships exist; but understanding how and why they come about is a question for future research.

6 Study III: survey on relation of Section 117 funding to student perceptions of antisemitism

Because of the well-established relationships between authoritarianism and antisemitism, and because of the ongoing conflict between Israel and many of its Islamic neighbors, one purpose of the present project was to examine whether receipt of Section 117 funding from foreign countries correlates with antisemitism. Because so much Section 117 funding was provided by OIC member countries and other authoritarian countries (see Table 1; Supplementary Tables S1, S3, and S4), we performed a series of studies examining this issue using a variety of methodologies. Study III was a preliminary examination into whether such funding was associated with campus antisemitism. We conducted a survey of college students at institutions that did and did not receive Section 117 funding. In the survey, we assessed student experiences with antisemitism on campus, and then analyzed whether Section 117 funding was associated with students' reported experiences with antisemitism.

6.1 Methods

6.1.1 Sample

A national survey of college students was conducted via Prolific in March and April of 2022. One thousand nine hundred twenty-eight students nationwide were asked about their experience with antisemitism at their institutions. Demographic data was collected by self-report. One thousand four hundred twenty-five indicated they are women, 490 men, and 13 preferred not to respond. One thousand two hundred ninety-eight reported that they are White, 244 Asian, 121 Black, 173 mixed, and 92 Other. After removal of all respondents who did not complete the survey, did not provide the name of their institutions, or took over 30 min to complete the survey, the final sample was based on 1,760 respondents.

6.1.2 Measures

After answering filler questions (such as participants' views of the campus climate), respondents were prompted to answer five questions about their experiences with antisemitism and anti-Zionism on campus. Specifically, participants were asked:

How frequently is the following sentiment expressed at your university campus or in your classes? (1 = never; 2 = rarely; 3 = sometimes; 4 = often)

1. Saying Israel has no right to exist as a Jewish country.

2. Saying that the U.S. government only supports Israel because of Jewish money.

3. Drawing comparisons between contemporary Israeli policy and that of the Nazis.

4. Saying American Jews care more about Israel than the U.S.

5. Boycotting Jewish organizations because they have a connection to Israel.

These specific questions were utilized because they tap into well-documented antisemitic (questions 2 and 4) and anti-Zionist (questions 1, 3, and 5) tropes (e.g., ADL, 2023; Burley, 2019; Jussim et al., 2023; Kaufman et al., 2021; Sunshine, 2019; Tabarovsky, 2022).

6.2 Results and discussion

Table 6 summarizes results of Welch's t-tests comparing experiences of campus antisemitism reported by students attending universities that received Section 117 funds between 2014 and 2019 (n = 473) with such experiences reported by students from universities that did not receive Section 117 funds (n = 1,287). First, the overall mean levels of reported exposure to antisemitic and anti-Zionist tropes were low; all means were below 1.4 on a scale of 1–4, where 1 was “never.” Consistent with this, the effect sizes are uniformly small. Second, even though overall reported exposure was low, students at colleges/universities that received Section 117 funding reported experiencing all five types of antisemitism more often, in terms of mean differences, than did students at institutions that did not receive Section 117 funding. However, only two had p-values below 0.01 (Israel has no right to exist; boycott), and a third (American Jews care more about Israel) had a p-value of 0.013. The remaining items did not approach statistical significance (see Table 6).

Table 6

Table 6. (Study III) Students' reported experiences with antisemitic claims at institutions that received Section 117 funding compared to those that did not (2014–2019).

Additional analyses assessed whether experiences with antisemitism differed depending on whether funding was from OIC vs. non-OIC countries, and whether funding was from authoritarian vs. non-authoritarian countries. However, all of these differences were trivial in magnitude, and none had p-values below 0.05 (all Welch's t's < 1.0, all p's ≥ 0.30). Overall, therefore, Study III provided modest evidence of students reporting more exposure to antisemitic and anti-Zionist tropes if they attended an institution that received Section 117 funding than if they attended one that did not.

A limitation of Study III was that it assessed students' self-reported exposure to antisemitic and anti-Zionist rhetoric. Exposure to rhetoric and being a victim of an actual hate crime or some form of harassment or vandalism are very different types of phenomena. Study V examined these issues. However, before studying whether receipt of Section 117 funding was related to actual antisemitic incidents, Study IV assessed whether different national measures of antisemitic incidents assessed similar or fundamentally different underlying phenomena.

7 Study IV: validation of national measures of antisemitism

To study the relationship between Section 117 funding and antisemitic and anti-Zionist incidents, we needed to first identify credible assessments of such incidents. Several organizations provide assessments of antisemitic incidents, each using different definitions for what classifies as antisemitism. The Federal Bureau of Investigation (FBI) provides a national assessment of hate crimes, including those against Jews. The Anti-Defamation League (ADL) provides a national assessment of antisemitic incidents, which includes propaganda campaigns and attacks. AMCHA is an American non-profit that describes itself as “dedicated to investigating, documenting, educating about, and combating antisemitism at institutions of higher education in America” (AMCHA Initiative, n.d.-b). Its activities include monitoring antisemitic and anti-Zionist activities on college and university campuses. The main purpose of Study IV was to assess the concurrent validity of these three sources with each other (Supplementary Table S5 reports summary statistics regarding reports of antisemitism from ADL, FBI, and AMCHA).

Each of these sources of data on antisemitism has limitations. AMCHA, for instance, has faced criticism for cataloging BDS activity as antisemitic, because some interpret it as human rights activity. But AMCHA data also includes overt expressions of antisemitism on campus such as swastikas and anti-Jewish slurs, and incidents of students targeted in the classroom for being Jewish. Thus, we describe AMCHA variables as measuring antisemitism/anti-Zionism. The ADL's antisemitic incident reports include a variety of incidents including slurs, the display of hate symbols, and violent attacks, but it may lack the same reach as law enforcement-reported incidents, particularly in lower-population areas. And even the FBI may underreport hate crimes. Nonetheless, if all three sources produce similar estimates, it is likely that they are capturing bona fide variation in antisemitism over time and place.

Thus, Study IV examined two alternative hypotheses:

Hypothesis 1: The FBI, ADL, and AMCHA data capture underlying, similar, and systematic variability in acts of antisemitism/anti-Zionism. As such, there should be considerable similarity among these three measures. Therefore, the three reports should substantially correlate with one another.

Hypothesis 2: The FBI, ADL, and AMCHA reports of antisemitism are so different from one another that they do not capture fundamentally similar phenomena. Therefore, there will be little or no correlation among them.

7.1 Methods

We obtained data on antisemitic acts and incidents from the websites of the FBI, ADL, and AMCHA for 2015–2020. Our first objective was to assess the consistency among their reports. Data on antisemitic activity in 3,108 U.S. counties in the lower 48 states was obtained from the FBI's Uniform Crime Reporting database for the years 2015–2020. We linked the AMCHA data on campus antisemitism to county by using Google map data for campuses. The ADL Tracker™ dataset contains data on antisemitic incidents for all 50 states. The ADL, AMCHA and FBI spreadsheets were converted from city form to county FIPS code using INDEX and MATCH functions in Excel with an extensive dataset of 108,797 cities and towns downloaded from SimpleMaps.com. Cities not included in that dataset were manually matched to county FIPS code. Incidents reported on university campuses were referenced to their respective counties. A small number of townships, villages, and towns could not be located, likely due to reporting errors, and were thus excluded.

7.2 Results and discussion

The main analyses tested our hypotheses suggesting that the three measures of antisemitism either will (Hypothesis 1) or will not (Hypothesis 2) substantially correlate with one another. We did this by assessing the Spearman correlation between the three measures by county. For this analysis, the three AMCHA variables were summed to create an overall index of AMCHA incidents.

We used Spearman correlations because the data were not normally distributed; most counties had no antisemitic incidents. Consistent with Hypothesis 1, the three measures correlated substantially [Spearman correlations: r_{(3, 106)} = 0.56 (FBI with ADL); r_{(3, 106)} = 0.53 (ADL with AMCHA); and r_{(3, 106)} = 0.48 (FBI with AMCHA); all p's < 0.001].

Figure 1 shows three maps of the United States, each colored by the percentile of the count of antisemitic incidents occurring in each county per the titled dataset. The maps reflect: 1. The different overall levels of antisemitism reported by the three sources; and 2. The geographic similarity in the patterns of antisemitism each source reports. The first map shows the percentile rankings of counties based on the Targeting variable reported by the AMCHA Initiative (because it is most similar to the ADL and FBI data), while the second map displays the FBI's reported antisemitic hate crimes, and the third map represents the Anti-Defamation League (ADL) reports of antisemitic incidents. Each county's color intensity corresponds to its relative percentile ranking, with darker shades indicating higher frequencies or reports of antisemitic incidents.

Figure 1

Figure 1. (Study IV) Comparative Choropleth maps of antisemitic targeting and incidents in U.S. counties, 2015–2020. This set of three maps visualizes the distribution of antisemitic activities across U.S. counties, as indicated by different data sources. Darker reds indicate a county with more antisemitic incidents.

The maps provide a geographical perspective on the prevalence and distribution of antisemitism at the county level, aiding in understanding regional patterns and differences. They are also a way to visualize the overlap or similarity among the three measures of antisemitism and are, therefore, another way to examine our alternative hypotheses. Taken together, the visual perspective of the maps and the correlations among the three data sources all support Hypothesis 1 and indicate that there exists substantial alignment on county-level antisemitism measures. Therefore, Studies V, VI, and VII use the data from the FBI, ADL, and AMCHA on antisemitism.

8 Study V: association of Section 117 funding with antisemitic and anti-Zionist activity

Study V assessed the relationship between receipt of Section 117 funding and antisemitism/anti-Zionism. Some of the largest contributors of Section 117 funding of institutions of higher education were from OIC member countries. There is a long history of hostility to Jews within violent Islamic extremism and Islamism more broadly (see Schroeter, 2018; Tausch, 2014 for reviews). Similarly, authoritarian regimes on the right (e.g., Nazi Germany) and left (e.g., Soviet Union) promulgated antisemitic rhetoric and enacted antisemitic policies. Therefore, the purpose of this study was to explore whether funding from OIC member countries and/or authoritarian countries was associated with antisemitism on campuses. Three research questions were assessed:

Were there higher levels of antisemitism at:

1. institutions that received Section 117 funding than at institutions that did not receive Section 117 funding?

2. institutions that received Section 117 funding from OIC member countries than at institutions that received Section 117 funding from non-OIC member countries?

3. institutions that received Section 117 funding from authoritarian countries than at institutions that received Section 117 funding from non-authoritarian countries?

8.1 Methods

8.1.1 Institutions

We used the U.S. News and World Report (2022; Reiter, n.d.) list of top 100 universities and top 100 colleges in the U.S. as our sample (plus ties, total N = 203). See Supplementary Table S6 for the list of colleges and universities included in our analysis. This list includes some of the most important and influential institutions in the country, and it was created independent of the present research, thereby minimizing the potential for selection bias. Of this set of 203 institutions, 107 received Section 117 funding.

8.1.2 Linking institutions to antisemitism

Analyses were based on antisemitic/anti-Zionist incidents (total N = 2,040) as reported by AMCHA (AMCHA Initiative, n.d.-a) at 107 institutions over 6 years, from 2015 to 2020. We used these with a 1-year lag in order to permit diffusion of effects for receipt of Section 117 funding from 2014 to 2019. The three types of AMCHA incidents analyzed were BDS, Antisemitic Expression, and Targeting (as previously described in Section 3.1) as well as the summed Total of all three. AMCHA reports antisemitic/anti-Zionist incidents on campus, something done by neither the FBI nor ADL. Therefore, these analyses only involved AMCHA data.

8.2 Results and discussion

We examined whether levels of each of the three AMCHA types of incidents varied depending on the receipt or source of Section 117 funding received from 2014 to 2019 (see Supplementary Tables S2–S4).

Research Question 1: Are there higher levels of antisemitism/anti-Zionism at institutions that received Section 117 funding than at institutions that did not?

Four Welch's t-tests compared levels of BDS, Expression, Targeting and their summed total among institutions that either received or did not receive Section 117 funding. Table 7 reports the results. All three measures and the total were higher among institutions that received Section 117 funding (all p's < 0.001). Furthermore, the effect sizes were strong (0.52 ≤ Cohen's d's ≤ 0.74).

Table 7

Table 7. (Study V) Welch's t-tests comparing antisemitism variables among institutions that received Section 117 foreign funding to those that did not.

Research Question 2: Are there higher levels of antisemitism/anti-Zionism at institutions that received Section 117 funding from OIC member countries than at institutions that received Section 117 funding from other countries?

Four Welch's t-tests compared levels of BDS, Expression, Targeting and their summed Total, but this time, among institutions that received Section 117 funding from either OIC or other countries. Table 8 reports the results. These results were also strong and consistent. All three measures of antisemitism/anti-Zionism, and the total, were much higher among institutions that received OIC funding (all p's < 0.001, all d's ≥ 0.59; see Table 8).

Table 8

Table 8. (Study V) Welch's t-tests comparing antisemitism variables among institutions that received funding from OIC member countries to those that received funding from other countries.

Research Question 3: Are there higher levels of antisemitism/anti-Zionism at institutions that received Section 117 funding from authoritarian countries than institutions that received Section 117 funding from non-authoritarian countries?

Four Welch's t-tests compared levels of BDS, Expression, Targeting and their summed total, but this time, among institutions that received Section 117 funding from either authoritarian countries or other countries. Table 9 reports the results, which were also strong and consistent. All three measures of antisemitism/anti-Zionism, and the total, were much higher among institutions that received funding from authoritarian countries than from other countries (all p's < 0.001, all d's ≥ 0.55; see Table 9).

Table 9

Table 9. (Study V) Welch's t-tests comparing antisemitism variables among institutions that received funding from authoritarian countries to those that did not.

Overall, therefore, Study V produced strong evidence that receipt of Section 117 funding per se is associated with heightened antisemitic/anti-Zionist activity. It also produced consistently strong evidence that institutions that received Section 117 funding from OIC member countries or authoritarian countries had much higher levels of antisemitic/anti-Zionist activity.

9 Study VI: does what happens on campus stay on campus?

Having demonstrated a robust association between receipt of Section 117 funds with antisemitic activity on campus, we next examined whether and how antisemitic activity on campus correlated with broader area trends in antisemitic activity. College and university campuses are often leading indicators of cultural trends (Altbach, 2007), though they are also not necessarily immune to being influenced by those trends. Therefore, it is possible that antisemitic political activity, protests, and even violence on college campuses could be related to such events in the wider society. Study VI, therefore, examined whether campus antisemitism is associated with county-level incidents.

9.1 Methods

This study examined whether there were relationships between AMCHA data on campus antisemitism/anti-Zionism and ADL and FBI data on county antisemitism, using a county-level dataset (Study VI used the same data from 2015 to 2020 that was used in Studies IV and V). The dataset included 3,108 counties within the contiguous United States. For this analysis, we used AMCHA Targeting (rather than AMCHA BDS or Expression) due to its similarity in kind to ADL-recorded incidents of antisemitism and FBI-reported hate crimes. County demographic data was obtained from the U.S. Census Bureau's (2017) American Community Survey. These data were then merged with a TigerLine county shapefile after removing states and territories outside of the lower-48 states using FIPS codes.

9.2 Results and discussion

9.2.1 Analysis overview

Analyses assessed the relationship between the AMCHA data on campus antisemitism (summarized in Supplementary Table S5, and which occurred on 402 campuses in the U.S.) and antisemitism (as indicated by ADL and FBI data) in both the county in which those campuses were located and in adjacent counties. Geospatial regression models, an adaptation of OLS regression, were used to examine those associations. Whereas, OLS regression is typically used to assess relationships among different variables, one common use of geospatial regression is to assess patterns of association between one or more variables in different locations. For example, geospatial regression might be used to assess the relationship of unemployment levels in one area to home foreclosures in surrounding areas (see, e.g., Berry et al., 2008 for an overview).

The first step to spatial analysis is to assess the presence of spatial autocorrelation, or clustering. A preferred method for assessing the existence of clustering is the Moran's I-test:

$\begin{array}{l}I=\frac{n}{S_0}\frac{{\displaystyle \sum _{i=1}^n}{\displaystyle \sum _{j=1}^n}{w}_{i,j}{z}_i{z}_j}{{\displaystyle \sum _{i=1}^n}{z}_i^2}\end{array}$

i and j are features, n is the total number of features, w is the spatial weight for features i and j, and z is the deviation of a given attribute from the mean for i or j. S₀ indicates the combination of all spatial weights (Gimond, 2023).

We performed our Moran's I-test using Monte Carlo simulations (n = 999) of randomly distributed spatial arrangements in order to test whether our variables were randomly distributed, evenly dispersed, or clustered, and found that they were clustered (p < 0.001; Bivand, 2022). Given the spatial autocorrelation in our dataset, we ran Lagrange Multiplier tests on linear models to address appropriate spatial techniques.

$\begin{array}{l}y=X\beta +\rho W(1)y+u\\ u=\lambda W(2)u+e\end{array}$

W is a spatial weights matrix, e is an uncorrelated error term, λ is a spatial error, and ρ is a spatial lag. The dual tests examine the presence of a missing spatial error (λ= 0) or spatial lag term (ρ= 0; Anselin et al., 1996). Lagrange Multiplier tests indicated that our data would most support spatial lag models, while spatial error models proved less significant.

Hence, we used spatial simultaneous autocorrelation linear lag models, which analyze the correlations between the independent variables in neighboring areas, to assess the relationship of campus antisemitism to antisemitism in surrounding counties based on the following model:

$\begin{array}{l}y=\rho Wy+\beta X+\epsilon \end{array}$

y is the dependent variable (FBI or ADL data), x is the independent variable (AMCHA and population in county), ρ is the scalar parameter (which describes the magnitude of spatial dependence between the observed variables), and W is the spatial weights matrix (which quantifies the spatial relationship between geographically contiguous observations; LeSage and Pace, 2009).

9.2.2 Main findings

Table 10 presents the main results from two geospatial models, one for each outcome (county level antisemitism as reported by the FBI and ADL). Each model has two predictors (AMCHA Targeting, county population) of county level incidents of antisemitism. All coefficients are unstandardized and reported as β.

Table 10

Table 10. (Study VI) Spatial simultaneous autocorrelation lag model depicting the relationships between campus antisemitic targeting (AMCHA), ADL incidents, and FBI hate crimes by county.

The critical result in Table 10 is the row for antisemitic targeting (AMCHA) on campus, which was associated with all four antisemitism outcomes. The higher the antisemitism on campus, the higher the levels of antisemitism in the county in which that campus was located (ADL: β = 2.9522, p < 0.0001; FBI: β = 4.3483, p < 0.0001). Campus antisemitism also was associated with antisemitism in the immediately adjacent counties (ADL: β = 1.59, p < 0.0001; FBI: β = 5.7319, p < 0.0001).

These results clearly show that, as campus antisemitism goes up or down, so does antisemitism in the surrounding communities. Although Study VI has established the existence of this relationship, it raises more questions than it answers. Why and how does this connection between campus and community antisemitism occur? Are the antisemitic events near campus perpetrated by students? Does hostility to Jews spread from campus to surrounding communities? Alternatively, do communities that harbor more antisemitism provide more support and encouragement for campus antisemitism than communities that are less antisemitic? Do certain types of major local, national or international controversies trigger simultaneous spikes in antisemitism on campus and in the surrounding communities? Or is something else entirely going on? These are all questions for future research.

10 Study VII: antisemitism from campus to the rest of the country

Study VI found that antisemitic incidents on campus are associated with incidents in surrounding counties. However, those analyses did not examine the relationship between antisemitism on campus and antisemitic incidents in the rest of the country. Doing so was the purpose of Study VII.

10.1 Method

Study VII examined the relationship between campus antisemitism (AMCHA data, 2015–2020) and antisemitic hate crimes in the U.S. as reported by the FBI from 2015 to 2020. Because Study VII focuses on antisemitism per se, it did not include analyses with AMCHA's BDS data. Supplementary Table S5 summarizes the data on antisemitism and hate crimes against Jews. The FBI and AMCHA data were integrated into a daily time series table using INDEX and MATCH functions in Excel. ADL data were not used in these analyses because they are not available by year for 2015 to 2020.

10.2 Results and discussion

Analyses examined whether variability in campus antisemitism forecasts variability in antisemitism in the U.S. Figure 2 visually displays the variability and covariability among FBI antisemitic hate crimes and antisemitic incidents on campus. Spikes in green or blue (AMCHA campus antisemitism) often precede spikes in FBI reported antisemitic hate crimes (red).

Figure 2

Figure 2. (Study VII) ggplot chart (Wickham, 2016) showing campus antisemitic incidents (both expression and targeting) between 2015 and 2020 (AMCHA data), and FBI antisemitic hate crimes by week. Green reflects expressions of antisemitism on campus. Blue reflects antisemitic targeting on campus. Red reflects FBI reported hate crimes.

To test this pattern more rigorously, we employed Granger causality analysis. Granger causality is a statistical time-series correlation analysis which includes lagged variables to determine whether one is useful in forecasting the other. This assesses whether lagged values of the explanatory variable better predict the dependent variable than the latter's lagged values alone (Stern, 2019).

Granger causality has some important limitations. The term “Granger causality” is something of a misnomer because forecasting is not equivalent to causality and the results of a Granger causality analysis rarely prove causality (Shojaie and Fox, 2022). In addition, effects sizes are not produced by Granger causality analyses. Despite its limitations, Shojaie and Fox (2022, p. 314) conclude that: “At minimum, …continued developments in this area can help researchers take the first step toward causal inference by restricting the set of possible causal hypotheses.” See Supplementary Table S7 for fit measures.

The key Granger causality results are shown in Table 11. Both Campus Targeting Incidents (p < 0.0001) and Campus Antisemitic Expression (p = 0.0257) forecasted FBI-reported hate crimes. However, the p-value above 0.01 should be viewed as an invitation to future research rather than as definitive. The Granger causality results also found that national FBI hate crimes forecast Campus Antisemitic Targeting incidents (p = 0.0039), but a statistically significant forecast was not found for Campus Antisemitic Expression (p = 0.159).

Table 11

Table 11. (Study VII) Granger causality analysis assessing how campus antisemitism and FBI hate crimes against Jews forecast one another (January 2015–December 2020).

These findings are exploratory and correlational, meaning that causal conclusions are not justified, and further research is necessary. Nonetheless, the Granger causality analyses indicated that both campus antisemitic targeting and FBI hate crimes nationwide forecast one another. Speculation regarding hypotheses worthy of further testing are, therefore, warranted. For example, one possible explanation for these relationships is that institutional antisemitism could spill out to national incidents and hate crimes. Another is that heightened antisemitism around the country could manifest on campus.

The strongest and clearest results indicate bidirectional predictive power between Campus Antisemitic Targeting Incidents and FBI hate crimes, whereas relationships with Campus Antisemitic Expression were weaker. We speculate that this pattern occurs because, like targeted antisemitic harassment, hate crimes (other than property-related crimes) target a specific person or people. Also, antisemitism directed at specific targets is more severe than is un-targeted expression. Harassment, bullying, or hate crimes (targeting) are clearly more severe transgressions than antisemitic or anti-Zionist posters or chants (expression), which is why targeting is potentially punishable either by legal or campus authorities whereas expression rarely is (a notable exception is when it constitutes vandalism or other property-related crimes). As such, targeting may be more likely to make campus, local, or even national news stories. If so, this might be more likely to inspire similar such actions in other places. Regardless of the explanation, however, our findings indicate that campus institutional antisemitism does not remain isolated to the university but is related to broader regional activity.

11 General discussion

In this report, we explored ways in which Section 117 funding received by colleges and universities predicted both the erosion of liberal democratic norms around speech and antisemitism. Key findings include:

1. Major institutions of higher learning in the U.S. received billions of dollars of Section 117 funding from foreign sources between 2014 and 2019 (Study I).

2. Receipt of Section 117 funding:

a. was weakly related to an illiberal environment on campus in which scholars and campus speakers were likely to be targeted for disinvitation or punishment by activist campaigns (Study II).

b. was weakly associated with student reports of campus exposure to both antisemitic and anti-Zionist rhetoric (Study III).

c. was strongly associated with higher levels of antisemitic acts than on campuses that did not receive such funding (Study V).

3. Receipt of funding from member countries of the Organization for Islamic Cooperation (OIC) and from authoritarian countries was:

a. strongly associated with scholars and campus speakers being targeted for disinvitation or punishment by activist campaigns (Study II).

b. weakly related to student reports of their experiences with antisemitic and anti-Zionist rhetoric (Study III).

c. strongly associated with higher levels of antisemitic activity on campus than on campuses that did not receive funding from such countries (Study V).

4. Increased antisemitic activity on college campuses was associated with heightened antisemitic activity in nearby communities (Study VI).

5. Campus antisemitism directed at specific targets was associated with the level of national antisemitic hate crimes (Study VII).

11.1 Limitations and directions for future research

As the first large-scale and data-driven report that links foreign funding, democratic norms and antisemitism, this work has notable limitations. Because our analyses were correlational, we did not reach causal conclusions. This leaves unanswered many important questions. For example, does receipt of foreign funding, especially from member countries of the Organization for Islamic Cooperation or from authoritarian countries, increase antisemitism, illiberalism or the erosion of specific liberal democratic norms on campus such as those regarding free speech? Or perhaps the independent development of illiberalism and antisemitism attracted such funding. Does some third variable (such as university status, number of state-sponsored students from anti-democratic countries, number of antisemitic faculty, whether the university president is an antisemite, etc.) cause illiberalism and attract foreign funding from illiberal sources? Do spikes in campus antisemitism cause spikes in surrounding communities and the country? Do spikes in local or national antisemitism cause spikes in campus antisemitism? Or does some combination of causes combine in complex ways?

This research provided no insight into how any of the potential directions of causality might occur. Perhaps Section 117 money funds illiberal or antisemitic groups on campus. Perhaps it supports hiring illiberal or antisemitic professors. Perhaps this sort of support provides tacit endorsement of antisemitic incidents. Alternatively, campus sociopolitical trends conducive to illiberalism and antisemitism may have developed independently of Section 117 funding, and Section 117 funding may have no causal relationship whatsoever with campus illiberalism or antisemitism.

Another limitation stems from the exploratory nature of all studies reported herein. Our analyses cast a broad net, operationalizing “authoritarian sources” as the 30 most authoritarian countries plus Russia. Separately, for OIC countries, most were ranked as authoritarian or “hybrid” (a mix of democratic and authoritarian) by the Democracy Index, and many have populations with high levels of antizionist and antisemitic beliefs and attitudes. One could test these hypotheses using different operationalizations of authoritarianism and antisemitic/antizionist attitudes. We did not do this because it could have muddied the findings, due to overlap between various alternative operationalizations. Additionally, different operationalizations would have created a massive multiple comparisons problem requiring a dramatic reduction of our already-reduced threshold for statistical significance. Although, the consistent differences found between these and other countries validates how we grouped them, it is nonetheless possible that those differences derive primarily from specific subsets of those countries we grouped. Addressing these sorts of issues is an important issue for future research.

Future research should test potential causal explanations. Whereas experimental research, which would permit strong causal conclusions, is probably not possible in this area, identifying causal directions is an important area for future research. Causal hypotheses could be tested in future non-experimental research that might justify causal conclusions, as long as certain strong standards are met (Rohrer, 2018). Although the present research does not meet those standards, it does raise important causal questions.

Additionally, the present research did not assess why some of this funding went unreported for years, until the U.S. Department of Education conducted an investigation in 2019. Therefore, the present research did not examine whether this occurred because of innocent mistakes, managerial incompetence, overly complex bureaucratic reporting requirements, political agendas, corruption, or some combination of reasons. It is also possible that foreign funding went unreported for different reasons at different institutions. The purpose of the present research was to investigate social and political phenomena related to receipt of Section 117 funding; its purpose was not to investigate how or why the money went unreported, though future research doing so would be valuable.

Last, this was the first quantitative investigation (of which we are aware) on how receipt of Section 117 funds relates to campus liberal democratic norms. As such, it was exploratory, rather than confirmatory. Therefore, all findings should be viewed as preliminary, pending replication in future research.

11.2 No conspiracies needed

It is important not to misunderstand or misrepresent the findings in the present paper. Many elements of the findings may appear ripe for conspiratorial thinking—secrecy (undisclosed funding), wealthy and powerful foreign actors, and harmful outcomes (e.g., spreading antisemitism and undermining liberal democratic norms). Nothing presented here suggests that mustachio-twirling villains from authoritarian or majority Muslim countries are conspiring in dark basements with deans and provosts to corrode democracy or harm Jews. We caution against misconstruing these findings to blame and target students or faculty who simply have ties to these donor countries. Indeed, we have no evidence that any of the relationships we uncovered reflect causal effects of foreign funding. Causal effects are one possible explanation for our findings, but, as we have pointed out throughout the manuscript, causality may flow in very different directions. Furthermore, the main outcomes in the present study—liberal democratic norms around speech and academic freedom, and antisemitism, are surely influenced by many factors not addressed in any of our studies. Moreover, even if the influence of foreign funding is ultimately found to be causal in subsequent research, it would likely happen through very conventional processes (e.g., attracting or supporting scholars or organizations with particular views or political agendas) rather than through conspiracies concocted in dark corners.

12 Conclusion

Despite the preliminary and correlational nature of this report, it raises some sobering possibilities that deserve attention in future research. Are international actors funneling large amounts of money, sometimes undisclosed, into higher education (including elite institutions that often have outsized influence on American culture and politics) for purposes harmful to the democratic norms of pluralism, tolerance, and freedom of speech? There clearly has been an erosion of democratic norms regarding freedom of speech in academia (Clark et al., 2023; Lukianoff and Schlott, 2023; Maranto et al., in press). These developments are surely complex and multiply determined.

The present research highlights two troubling possibilities that deserve further investigation. The first is that receipt of Section 117 funding from foreign sources, especially authoritarian ones, has contributed to these developments. The second is that providing massive financial support to campuses with ascendant illiberalism serves the interests of foreign actors hostile to the U.S. in particular or liberal democracy in general.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.

Ethics statement

The studies involving humans were approved by Institutional Review Board for Human Subjects Research, Washington State University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

MB: Conceptualization, Data curation, Investigation, Methodology, Writing – review & editing. AR: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. BW: Data curation, Formal analysis, Methodology, Software, Validation, Visualization, Writing – review & editing. JF: Conceptualization, Formal analysis, Visualization, Writing – review & editing. SY: Data curation, Writing – review & editing. DF: Data curation, Writing – review & editing. SS: Data curation, Investigation, Methodology, Writing – review & editing. NH: Data curation, Investigation, Methodology, Writing – review & editing. PP: Writing – review & editing. AF: Conceptualization, Data curation, Investigation, Methodology, Writing – review & editing. CS: Conceptualization, Investigation, Writing – review & editing. LJ: Conceptualization, Project administration, Supervision, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Acknowledgments

A preliminary, unpublished report on relationships between foreign funding, speech, and antisemitism, using partially overlapping data, appeared in Small et al. (2023).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Footnotes

1. ^In subsequent studies on campus antisemitism, we only used data with a one year lag from receipt of funding (i.e., funding data is from 2014 to 2019, so antisemitism is based on data collected with a one year lag, from 2105 to 2020). There are, however, thousands of incidents of antisemitism in the databases we used, whereas there are far fewer cases of deplatforming or scholars under fire (several hundred total). This meant that sometimes there were as few as a 100 instances per cell when we compared institutions based on whether they received funding and from which type of countries they received it. Therefore, when conducting the study using FIRE data on deplatforming and scholars under fire, to increase the statistical power of our tests, we extended the timeframe from the first year of funding (2014) to 2023, which was the last year of data available when we conducted the analyses.

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