Brandeis University
Maurice and Marilyn Cohen Center for Modern Jewish Studies
Antisemitism and the College Campus:
Perceptions and Realities
Technical Appendices
Leonard Saxe
Theodore Sasson
Graham Wright
Shahar Hecht
July 2015
Table of Contents
Appendix A: Characteristics of Taglit-Birthright Israel Applicants .................................................. 2
Appendix B: Methodology .............................................................................................................. 5
Field Operations and Response Rates ......................................................................................... 5
Weighting .................................................................................................................................... 6
Analysis ........................................................................................................................................ 6
Appendix C: Regression Models ..................................................................................................... 7
Appendix D: Antisemitism and Anti-Israel Sentiment on Campus ............................................... 10
Appendix E: Comparison of Results to other Surveys of Antisemitism on Campus ..................... 21
Appendix F: Survey Instrument .................................................................................................... 23
2
Appendix A: Characteristics of Taglit-Birthright Israel Applicants
Of the applicant pool for summer 2015, 90 percent were from the United States and 10 percent
were from Canada. The majority of the applicant pool (58 percent) was female. Applicants
ranged in age from 18 to 26, with most (55 percent) being 22 years old or younger. Over half of
the applicant pool consisted of undergraduate students, and another third were college
graduates who were either attending graduate school or working (Figure 1). Two percent were
married. On all of these demographic measures Taglit’s summer 2015 applicants were not
substantially different from those who applied for trips in the previous summer.
Figure 1. Education status of Taglit applicants by country
100%
6%
8%
5%
3%
80%
60%
57%
60%
Not a student, no degree
High school student
Undergraduate student
40%
Has undergraduate degree
20%
33%
30%
United States
Canada
0%
Taglit applicants included individuals with a wide range of Jewish backgrounds and experiences.
Some applicants had no Jewish education, while others had extensive Jewish education (see
Figure 2). Although the size of the applicant pool was somewhat smaller than in 2014, summer
2015 applicants were very similar to the summer 2014 applicants in terms of their Jewish
backgrounds. Thus, for example, the proportion from households with two Jewish parents is
nearly identical, as are the proportions who have had exposure to a Jewish summer camp or a
day school.
3
Figure 2. Jewish background and experiences of Taglit applicants by country (summer 2014 and
2015 applicants)
100%
82%84%
80%
70%70%
60%
52%
47%
40%
55%
53%
55%
48%
35%35%
30%
27%
23%24%
20%
5% 6%
5% 6%
0%
Two Jewish Jewish day
parents
school
Jewish
camp
Orthodox
Been to Two Jewish Jewish day
Israel
parents
school
U.S. Taglit applicants
Jewish
camp
Orthodox
Been to
Israel
Canadian Taglit applicants
Summer 2014
Summer 2015
Applicants in the summers of 2014 and 2015 were also nearly identical in terms of their political
views (see Figure 3). Applicants who were undergraduate were more likely to have stronger
Jewish backgrounds than older applicants; 73 percent of current undergraduate applicants had
two Jewish parents, compared to only 68 percent of non-undergraduates, and 39 percent had
been to Jewish summer camp, compared to only 35 percent of non-undergraduates.
4
Figure 3: Political views of Taglit applicants summer 2014 (pre trip) and summer 2015
100%
1%
7%
1%
8%
8%
9%
26%
25%
80%
Extremely conservative
60%
Conservative
Slightly conservative
15%
16%
Moderate
Slightly liberal
40%
Liberal
Extremely liberal
35%
20%
35%
8%
6%
Summer 2014
Summer 2015
0%
5
Appendix B: Methodology
The sample for this study was drawn from all applicants to summer 2015 Taglit-Birthright Israel
trips. Although ineligible applications were ignored, incomplete applications were included in
the sampling frame to allow for an analysis of factors related to completion of the application
form. The analyses in the report is limited to the data collected from those with complete and
eligible applications. The sample was drawn on March 18, 2015 (a couple of weeks before
registration for the summer trips was officially closed). Overall there were 38,412 unique
applications to summer 2015 Taglit-Birthright Israel trips, of which 30,293 (79 percent) were
complete and eligible and 8,119 (21 percent) were incomplete (which in some cases meant that
there was insufficient information to determine eligibility status). The frame the sample was
drawn from accounts for 92 percent of all applications to this season’s trips. The simple random
sample of 15,000 applicants included 12,049 complete applications and 2,951 incomplete
applications.
Field Operations and Response Rates
The survey was conducted online, using a web instrument created in Lime Survey. Email
invitations and reminders were sent to individuals using email address information collected in
the Taglit registration process. All respondents were offered a chance to win one of three $100
Amazon.com gift certificates
The initial email invitation was sent to all 15,000 sample members on April 15, 2015. Three
separate reminders were sent on April 22, 2015, April 27, 2015, and May 4, 2015. The survey
was closed on May 7, 2015, before any summer Taglit trips had departed.
Table 1 shows final dispositions and AAPOR response rates for the entire population, as well as
separately for those with completed and incomplete Taglit applications.
Table 1: Pre Survey Final Disposition and Response Rate
Complete interview
Partial interview
Break-off
Refusal
Ineligible
Non-contact
Full Sample
Eligible Sample
AAPOR Response Rate 2
Incomplete
Applications
215
40
58
76
4
2,558
2,951
2,947
8.65%
Complete
Applications
2,833
366
668
322
6
7,854
12,049
12,043
26.6%
Total Sample
3,048
406
726
398
10
10,412
15,000
14,990
23.0%
6
Weighting
Because this survey utilized a simple random sample of the population, no design weights were
needed to account for unequal probabilities of selection. However, due to unit nonresponse,
there were a number of significant differences between the characteristics of survey
respondents and the characteristics of the full population. This could be determined empirically
because a significant amount of demographic data is available in the Taglit registration system
for the entire population, including survey nonrespondents. Respondents were weighted so
that their demographic characteristics matched those of the full population. This weighting
procedure (often known as “raking”) iteratively adjusts on each specified variable in turn, until
the difference between the weighted estimate and target value for each variable is below a
minimum specified level. Weights for this study were computed in Stata using the user written
“survwgt” command.
To calculate weights, a logistic regression model was run that attempted to predict survey
response as a function of a number of demographic variables which were known for the entire
population. Variables investigated included: age, gender, parental inmarriage, Jewish
denomination, and number of previous applications to Taglit. After examining these variables,
the final weighting variable was calculated using the following variables: gender, age, and
number of previous applications to Taglit. For weighting purposes, age was recoded to be a
binary variable based on the respondent being 22 years old or older.
Analysis
Analyses were conducted using Stata 13.1 and the “svy” suite of commands for weighted data.
Data were drawn from the Taglit registration system, the pre-trip survey and pre-trip data from
the CMJS’ survey of summer 2014 Taglit applicants (see Shain et. al, 2015 for methodological
details1), and appropriate weights were applied to each analysis based on the source or sources
of the data. Throughout the report, only descriptive statistics—usually two-way tables of
frequencies—are presented. However, the substantive relationships between variables
presented in this report have been confirmed by a number of more sophisticated analytic
paradigms, including regression analysis and multi-level modeling to account for the clustering
of individuals in college campuses. The results of these additional analyses can be found in
Technical Appendix C and D.
1
Shain, M., Saxe, L., Hecht, S., Wright, G., & Sasson, T. (2015). Discovering Israel at war: The impact of TaglitBirthright Israel in summer 2014. Waltham, MA: Cohen Center for Modern Jewish Studies, Brandeis University.
7
Appendix C: Regression Models
This appendix reports the results of the logistic regression models which are referenced in the
report when discussing the individual level predictors of perceiving hostility to Israel or Jews,
being blamed for Israel’s actions or being verbally harassed. All of these models control for five
different individual level predictors





“binparinmar” – a binary variable denoting that the respondent was raised by two Jews
(as opposed to being raised by a Jew and a non-Jew)
“Jewed” – a categorical variable measuring the most intense form of Jewish education
received by the respondent, entered in to the model as two dummy variables denoting
Sunday school and day school, with “no-Jewish education” as the suppressed reference
category
“prpolviewsscale” – an ordinal variable measuring political ideology, with higher values
denoting more conservative respondents
“female” – a binary variable for gender
“prconisr” – an ordinal variable measuring connection to Israel, with higher values
denoting more connected respondents
Table 2: Logistic regression of perceiving hostility to Israel by students as a "fairly big" or "very big" problem (current
undergraduates only)
Logistic regression
Log likelihood = -690.93957
Number of obs
LR chi2(6)
Prob > chi2
Pseudo R2
=
=
=
=
1,268
78.29
0.0000
0.0536
-----------------------------------------------------------------------------------prcolasisrlstudbin |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------------+---------------------------------------------------------------binparinmar |
.2685063
.169628
1.58
0.113
-.0639585
.600971
|
jewed |
sunday school |
.0198574
.1599475
0.12
0.901
-.293634
.3333487
day school |
.0519986
.1829487
0.28
0.776
-.3065742
.4105715
|
prpolviewscale |
.0298351
.0488994
0.61
0.542
-.066006
.1256763
female |
.308811
.1396328
2.21
0.027
.0351358
.5824862
prconisrl |
.6087026
.0899954
6.76
0.000
.4323149
.7850903
_cons | -3.449435
.3299567
-10.45
0.000
-4.096138
-2.802732
------------------------------------------------------------------------------------
8
Table 3: Logistic regression of ever being blamed for Israel's actions (current undergraduates only)
Logistic regression
Log likelihood = -675.21171
Number of obs
LR chi2(6)
Prob > chi2
Pseudo R2
=
=
=
=
1,267
72.88
0.0000
0.0512
-------------------------------------------------------------------------------prisrblamerec |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
---------------+---------------------------------------------------------------binparinmar |
.099493
.1705795
0.58
0.560
-.2348367
.4338226
|
jewed |
sunday school |
.1628177
.1637764
0.99
0.320
-.158178
.4838135
day school |
.2919239
.1857592
1.57
0.116
-.0721574
.6560053
|
prpolviewscale |
.0204879
.0497513
0.41
0.680
-.0770228
.1179987
female |
.3592836
.142548
2.52
0.012
.0798946
.6386726
prconisrl |
.5717302
.091233
6.27
0.000
.3929168
.7505437
_cons | -3.395519
.3331424
-10.19
0.000
-4.048466
-2.742572
--------------------------------------------------------------------------------
Table 4: Logistic regression of perceiving hostility to Jews by students as a "fairly big" or "very big" problem (current
undergraduates only)
Logistic regression
Log likelihood = -485.65105
Number of obs
LR chi2(6)
Prob > chi2
Pseudo R2
=
=
=
=
1,271
43.71
0.0000
0.0431
----------------------------------------------------------------------------------prcolasjewstudbin |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
------------------+---------------------------------------------------------------binparinmar |
.17006
.2187033
0.78
0.437
-.2585907
.5987106
|
jewed |
sunday school | -.0775233
.204759
-0.38
0.705
-.4788435
.3237969
day school | -.0529186
.2279715
-0.23
0.816
-.4997345
.3938973
|
prpolviewscale |
.1432611
.06049
2.37
0.018
.0247029
.2618192
female |
.3048486
.1772507
1.72
0.085
-.0425564
.6522537
prconisrl |
.5299129
.1156618
4.58
0.000
.3032199
.7566058
_cons | -4.285132
.4289441
-9.99
0.000
-5.125847
-3.444417
-----------------------------------------------------------------------------------
9
Table 5: Logistic regression of being verbally harassed for being Jewish (current undergraduates only)
Logistic regression
Log likelihood =
-786.5806
Number of obs
LR chi2(6)
Prob > chi2
Pseudo R2
=
=
=
=
1,274
24.58
0.0004
0.0154
-------------------------------------------------------------------------------prexpasverb |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
---------------+---------------------------------------------------------------binparinmar |
.3487569
.1514373
2.30
0.021
.0519452
.6455685
|
jewed |
sunday school |
.1875747
.1430233
1.31
0.190
-.0927457
.4678952
day school | -.2067326
.1750489
-1.18
0.238
-.5498222
.136357
|
prpolviewscale |
.0164834
.0456563
0.36
0.718
-.0730013
.1059681
female |
.2616169
.1280249
2.04
0.041
.0106926
.5125412
prconisrl |
.1941927
.0781494
2.48
0.013
.0410227
.3473628
_cons | -1.837275
.2787423
-6.59
0.000
-2.3836
-1.29095
--------------------------------------------------------------------------------
10
Appendix D: Antisemitism and Anti-Israel Sentiment on Campus
The discussion of campus-level variation with respect to antisemitism in the report is based on
the results of Hierarchical Linear Modeling (HLM) which treats undergraduate respondents as
being “clustered” within universities, and aims to determine the extent to which variation in
reported levels of antisemitism or hostility to Israel are due to variations across campuses, as
opposed to variations across individuals. These analyses use linear, random effects models,
estimated using maximum likelihood, to estimate the portion of the total variance on the
dependent variable is at the campus level.2
A random effects model is a weighted average of a “within school” model (which explores
variation in antisemitism among students at the same school) and a “between school” model
(which explores variation in the average levels of antisemitism on different campuses). Using
such a model makes it possible to calculate an “interclass correlation coefficient” (ICC) which
shows the percentage of the total variance which is explained by variations across schools (as
opposed to by variation across individuals in the same school), once the individual level
predictors have been accounted for.3
One potential complication to this effort is the fact that, as noted in the regression models
discussed in Appendix C, certain types of respondents (e.g., females and those with higher
levels of connection to Israel) were more likely to report certain types of antisemitism or
hostility to Israel. Different schools have different proportions of respondents with these
characteristics. If antisemitism is particularly high on certain campuses precisely because the
types of Jews on that campus serve as a target for hostility, then controlling for individual-level
characteristics might obscure the extent to which antisemitism and anti-Israel hostility is
particularly prevalent on specific campuses. Consequently, HLM models for the three
dependent variables are each run twice: once as a “constant only” model with no individuallevel predictors, and once controlling for the five variables included in the regression models in
Appendix C: parental inmarriage, most intense form of Jewish education, political views,
gender, and connection to Israel.
With respect to experiencing verbal harassment, both the constant only model (Table 6) and the
model with individual-level controls (Table 7) suggest that there is virtually no systematic
variation in verbal harassment across campus, whether or not the demographics of the campus
are controlled for. The ICC for the constant only model is .008, and the ICC for the model with
2
To ease interpretation, results reported here come from linear models, even though the dependent variables in
question are either binary (experiencing verbal harassment) or ordinal (hostility towards Jews/Israel is a problem).
Binary and ordinal logistic random effects models were also run for these variables which generally confirmed the
results of the linear models.
3
The ICC in these models is calculated by dividing the cluster level variance (denoted as “var(_cons)” in the output
tables) by the total cluster + individual level variance remaining after the predictor variables are controlled for
(“var(_cons)” + “var(Residual)”)
11
controls is almost exactly zero. The likelihood ratio tests presented at the bottom of both tables
are also both insignificant, suggesting that insufficient campus-level variance exists to justify
using a multi-level model to analyze this variable.
Table 6: Linear random effects model of being verbally harassed for being Jewish –constant only
Mixed-effects ML regression
Group variable: rguniversity
Log likelihood = -867.91478
Number of obs
Number of groups
=
=
1,315
350
Obs per group:
min =
avg =
max =
1
3.8
55
Wald chi2(0)
Prob > chi2
=
=
.
.
-----------------------------------------------------------------------------prexpasverb |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------+---------------------------------------------------------------_cons |
.3243465
.0134235
24.16
0.000
.2980369
.3506561
----------------------------------------------------------------------------------------------------------------------------------------------------------Random-effects Parameters |
Estimate
Std. Err.
[95% Conf. Interval]
-----------------------------+-----------------------------------------------rguniversity: Identity
|
var(_cons) |
.0019617
.0029884
.0000991
.0388457
-----------------------------+-----------------------------------------------var(Residual) |
.2172978
.0089133
.2005118
.2354889
-----------------------------------------------------------------------------LR test vs. linear model: chibar2(01) = 0.56
Prob >= chibar2 = 0.2270
12
Table 7: Linear random effects model of being verbally harassed for being Jewish –with individual level controls
Mixed-effects ML regression
Group variable: rguniversity
Log likelihood = -820.43814
Number of obs
Number of groups
=
=
1,269
341
Obs per group:
min =
avg =
max =
1
3.7
50
Wald chi2(6)
Prob > chi2
=
=
25.16
0.0003
-------------------------------------------------------------------------------prexpasverb |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
---------------+---------------------------------------------------------------binparinmar |
.0718089
.0314156
2.29
0.022
.0102355
.1333823
|
jewed |
sunday school |
.041377
.0307117
1.35
0.178
-.0188168
.1015709
day school | -.0471968
.0371184
-1.27
0.204
-.1199475
.025554
|
prpolviewscale |
.0033803
.0097815
0.35
0.730
-.0157911
.0225518
female |
.055463
.0270727
2.05
0.040
.0024015
.1085245
prconisrl |
.0426873
.0165346
2.58
0.010
.0102801
.0750946
_cons |
.0912101
.0573103
1.59
0.111
-.021116
.2035362
------------------------------------------------------------------------------------------------------------------------------------------------------------Random-effects Parameters |
Estimate
Std. Err.
[95% Conf. Interval]
-----------------------------+-----------------------------------------------rguniversity: Identity
|
var(_cons) |
1.84e-09
3.93e-09
2.79e-11
1.21e-07
-----------------------------+-----------------------------------------------var(Residual) |
.2133481
.0084698
.197377
.2306115
-----------------------------------------------------------------------------LR test vs. linear model: chibar2(01) = 0.00
Prob >= chibar2 = 1.0000
The lack of variation across schools with respect to verbal harassment is also presented
graphically, by plotting the campus-level intercepts generated by the random effects models
(figures 4 and 5). The error bars in this chart show the total within-school variation (for the
constant-only model) or the residual variation on the dependent variable within each school
that remains after controlling for the demographic variables included in the model (for the
model with controls). In both figures it can be clearly seen that there are essentially no
differences in campus-level intercepts, regardless of whether or not individual-level
characteristics are controlled for.
13
-1
-.5
0
.5
1
Figure 4: Campus intercepts and within campus variation for experiencing verbal harassment - constant only model
0
100
200
rank1a
300
400
-1
-.5
0
.5
1
Figure 5: Campus intercepts and within campus variation for experiencing verbal harassment - model with individual-level
controls
0
100
200
rank1b
300
400
14
With respect to hostility to Israel, however, there does appear to be a systematic variation in
the average level of hostility across different campuses. Tables 8 and 9 show that there is
significant campus-level variation in hostility to Israel, even after controlling for individual-level
factors. The ICC for the constant only model is .273 and the ICC for the model with controls is
.287, implying that, in both cases almost 30 percent of the total variance in hostility to Israel is
due to variations across campuses, as opposed to across individuals within campuses. The
likelihood ratio test for both models are also highly significant, suggesting that a significant
amount of campus-level variation exists. This can be seen in Figures 6 and 7, as well.
Table 8: Linear random effects model of seeing hostility to Israel as a problem on campus –constant only
Mixed-effects ML regression
Group variable: rguniversity
Log likelihood = -1756.8114
Number of obs
Number of groups
=
=
1,308
350
Obs per group:
min =
avg =
max =
1
3.7
53
Wald chi2(0)
Prob > chi2
=
=
.
.
--------------------------------------------------------------------------------prcolasisrlstud |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
----------------+---------------------------------------------------------------_cons |
1.862974
.0408813
45.57
0.000
1.782848
1.9431
-------------------------------------------------------------------------------------------------------------------------------------------------------------Random-effects Parameters |
Estimate
Std. Err.
[95% Conf. Interval]
-----------------------------+-----------------------------------------------rguniversity: Identity
|
var(_cons) |
.2671031
.0422337
.1959246
.3641403
-----------------------------+-----------------------------------------------var(Residual) |
.7103234
.0316379
.6509438
.7751195
-----------------------------------------------------------------------------LR test vs. linear model: chibar2(01) = 148.83
Prob >= chibar2 = 0.0000
15
Table 9: Linear random effects model of seeing hostility to Israel as a problem on campus –with individual level controls
Mixed-effects ML regression
Group variable: rguniversity
Log likelihood = -1656.3411
Number of obs
Number of groups
=
=
1,263
341
Obs per group:
min =
avg =
max =
1
3.7
49
Wald chi2(6)
Prob > chi2
=
=
89.08
0.0000
--------------------------------------------------------------------------------prcolasisrlstud |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
----------------+---------------------------------------------------------------binparinmar |
.0298887
.060887
0.49
0.624
-.0894476
.149225
|
jewed |
sunday school |
.0612105
.0592352
1.03
0.301
-.0548883
.1773093
day school |
.1592839
.0716222
2.22
0.026
.0189071
.2996608
|
prpolviewscale |
.0294289
.0183751
1.60
0.109
-.0065857
.0654435
female |
.087428
.0510196
1.71
0.087
-.0125686
.1874246
prconisrl |
.2153241
.0311914
6.90
0.000
.1541901
.276458
_cons |
.9962321
.1127906
8.83
0.000
.7751665
1.217298
-------------------------------------------------------------------------------------------------------------------------------------------------------------Random-effects Parameters |
Estimate
Std. Err.
[95% Conf. Interval]
-----------------------------+-----------------------------------------------rguniversity: Identity
|
var(_cons) |
.2661859
.0419391
.195467
.3624906
-----------------------------+-----------------------------------------------var(Residual) |
.6598793
.0300897
.6034631
.7215698
-----------------------------------------------------------------------------LR test vs. linear model: chibar2(01) = 149.95
Prob >= chibar2 = 0.0000
16
-2
-1
0
1
2
Figure 6: Campus intercepts and within campus variation for perceiving hostility to Israel on campus - constant only model
0
100
200
rank3a
300
400
-2
-1
0
1
2
3
Figure 7: Campus intercepts and within campus variation for perceiving hostility to Israel on campus - model with individual level
controls
0
100
200
rank3b
300
400
17
With respect to perceiving hostility to Jews as a problem on campus, the story appears to be
more complicated. When a constant-only model is run, without controlling for campus-level
demographics there appears to be very little in the way of campus-level variation in hostility
toward Jews, as shown in Table 10. The ICC for this model is only .017, and the likelihood ratio
test reported by the model suggests that this value is not significantly different from zero.
Consequently, when the campus-level intercepts from this model are plotted in Figure 8, the
average level of perceived hostility to Jews appears to be virtually identical on all campuses.
Table 10: Linear random effects model of seeing hostility to Jews as a problem on campus –constant only
Mixed-effects ML regression
Group variable: rguniversity
Log likelihood = -2797.3753
Number of obs
Number of groups
=
=
1,606
381
Obs per group:
min =
avg =
max =
1
4.2
72
Wald chi2(0)
Prob > chi2
=
=
.
.
-------------------------------------------------------------------------------prpolviewscale |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
---------------+---------------------------------------------------------------_cons |
3.238844
.0374999
86.37
0.000
3.165345
3.312342
------------------------------------------------------------------------------------------------------------------------------------------------------------Random-effects Parameters |
Estimate
Std. Err.
[95% Conf. Interval]
-----------------------------+-----------------------------------------------rguniversity: Identity
|
var(_cons) |
.0338892
.0339423
.0047591
.2413221
-----------------------------+-----------------------------------------------var(Residual) |
1.876526
.072139
1.740332
2.023379
-----------------------------------------------------------------------------LR test vs. linear model: chibar2(01) = 1.29
Prob >= chibar2 = 0.1282
18
-4
-2
0
2
4
Figure 8: Campus intercepts and within campus variation for perceiving hostility to Jews on campus - constant only model
0
100
200
rank2a
300
400
However, when individual-level predictors are included in the model, the story changes. The
model shown in Table 11, has an ICC of .137, suggesting that around 14% percent of the total
variance in hostility to Jews is at the campus level, and the likelihood ratio test is highly
significant, implying that the ICC is significantly different from zero. When the campus-level
intercepts generated by this model are plotted (Figure 9) it can be seen that, although there is
little variation in intercepts for the majority of schools there are a few schools at either end
where students appear to be systematically more likely to report hostility toward Jews as a
problem.
19
Table 11: Linear random effects model of seeing hostility to Jews as a problem on campus –with individual-level controls
Mixed-effects ML regression
Group variable: rguniversity
Log likelihood = -1456.8138
Number of obs
Number of groups
=
=
1,266
341
Obs per group:
min =
avg =
max =
1
3.7
49
Wald chi2(6)
Prob > chi2
=
=
61.96
0.0000
-------------------------------------------------------------------------------prcolasjewstud |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
---------------+---------------------------------------------------------------binparinmar |
.0746402
.052414
1.42
0.154
-.0280893
.1773697
|
jewed |
sunday school |
.0305224
.050989
0.60
0.549
-.0694141
.1304589
day school |
.0708745
.0617639
1.15
0.251
-.0501806
.1919296
|
prpolviewscale |
.0381955
.0159952
2.39
0.017
.0068455
.0695455
female |
.0983406
.0443099
2.22
0.026
.0114948
.1851864
prconisrl |
.1364584
.027055
5.04
0.000
.0834316
.1894852
_cons |
.9447788
.0959233
9.85
0.000
.7567725
1.132785
------------------------------------------------------------------------------------------------------------------------------------------------------------Random-effects Parameters |
Estimate
Std. Err.
[95% Conf. Interval]
-----------------------------+-----------------------------------------------rguniversity: Identity
|
var(_cons) |
.0833306
.0191167
.0531535
.1306401
-----------------------------+-----------------------------------------------var(Residual) |
.5265091
.0232315
.4828895
.5740689
-----------------------------------------------------------------------------LR test vs. linear model: chibar2(01) = 48.30
Prob >= chibar2 = 0.0000
20
-2
-1
0
1
2
3
Figure 9: Campus intercepts and within campus variation for perceiving hostility to Israel on campus - model with individuallevel controls
0
100
200
rank2b
300
400
One interpretation of the different results obtained by the two models of hostility toward Jews
is that there are some schools where reported hostility to Jews is not particularly high in
absolute terms, but where it is substantially higher than other schools with similar Jewish
populations. However, since this study was not designed to explicitly investigate campus-level
differences, there is insufficient statistical power available to further investigate this result.
21
Appendix E: Comparison of Results to other Surveys of Antisemitism on
Campus
Kosmin and Keysar (2015) conducted a study of more than a 1000 Jewish students, sampled
from college students with Jewish ethnic names.4 They reported that more than half of their
respondents had experienced or witnessed antisemitism in the previous year (see chart below,
reproduced from original report).
In this study of Taglit applicants in 2015 the questions used in the Kosmin and Keysar study
regarding encountering antisemitism were repeated. While the overall rate of encountering
antisemitism reported by respondents to this survey was somewhat lower from that reported
by Kosmin and Keysar, the results are very similar (Figure 10). In both surveys the findings
indicate that the source of the incidents were individuals rather than classrooms, lectures, or
the university administrative system.
4
Kosmin, B., & Keysar, A. (2015). National demographic survey of American Jewish college students 2014: AntiSemitism report. Hartford: The Louis D. Brandeis Center, Trinity College.
22
Figure 10: Witnessed or experienced antisemitism in past academic year (undergraduates only)
Combined (in any context)
46%
In another context
11%
By the University administration system
4%
In the student union
9%
In a lecture/class
9%
In clubs/societies
17%
From Individual students
32%
0%
20%
40%
60%
80%
100%
23
Appendix F: Survey Instrument
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BRI 32 Pre-Trip
Thank you for participating in Brandeis University's study of Jewish young adults' views about Israel and Antisemitism. The survey will take less than 10 minutes to complete and when you are done you will be entered in a
lottery to win ONE OF THREE $100 Amazon.com gift cards.Your input is very important.
This survey is conducted by the Cohen Center for Modern Jewish Studies at Brandeis University. Your responses will remain strictly confidential and only aggregate responses will be reported. Participation in this study is
completely voluntary. We hope that you will participate fully and honestly but you are also free to skip any questions that you choose not to answer.
To start the survey click on the "Next" button below.
There are 63 questions in this survey
About You
We'll start by asking you a few questions about yourself.
Do you currently live in...?
Please choose only one of the following:
United States
Canada
Another country (please specify):
{if((country=="1"), 'the United States', if((country=="2"),'Canada', 'the country where you live'))}
{if((country=="1"), 'American', if((country=="2"),'Canadian', 'citizens'))}
{if((country=="1"), 'American', if((country=="2"),'Canadian', ''))}
In what month and year were you born?
Answer must be between 01/1978 and 12/1996
Please enter a date:
Are you...?
Please choose only one of the following:
Male
Female
Other
Are you currently a student in a degree-granting program at a college or university?
Please choose only one of the following:
No
Yes
What level of schooling are you currently enrolled in?
Only answer this question if the following conditions are met:
((student.NAOK == "1"))
Please choose only one of the following:
Associate's degree (AA, ADN, etc.)
Bachelor's degree (BA, BS, etc.)
Master's degree (MA, MBA, MSW, etc.)
Professional degree (JD, MD, etc.)
Doctoral degree (PhD, etc.)
Other:
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Are you currently a...?
Only answer this question if the following conditions are met:
(schooltype.NAOK == "1" or schooltype.NAOK == "2")
Please choose only one of the following:
First year (Freshman)
Second year (Sophomore)
Third year (Junior)
Fourth year (Senior)
In which college or university are you enrolled?
Only answer this question if the following conditions are met:
(student.NAOK == "1")
Please write your answer here:
Are you currently...?
Please choose only one of the following:
Not employed
Employed full-time
Employed part-time
In terms of political views, people often classify themselves as "liberal" or "conservative." Where would you place yourself on this scale?
Please choose only one of the following:
Extremely liberal
Liberal
Slightly liberal
Moderate
Slightly conservative
Conservative
Extremely conservative
In politics today, do you consider yourself...?
Only answer this question if the following conditions are met:
(country.NAOK == "1")
Please choose only one of the following:
Republican
Democrat
Independent
As of today, do you lean more to the...?
Only answer this question if the following conditions are met:
((poliparty.NAOK == "3"))
Please choose only one of the following:
Republican Party
Democratic Party
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Israel
We'll now ask you a few questions about your thoughts on Israel.
To what extent do you feel a connection to Israel?
Please choose only one of the following:
Not at all
A little
Somewhat
Very much
How much do you agree or disagree with the following statements?
Please choose the appropriate response for each item:
Strongly
disagree
Disagree
Somewhat
disagree
Somewhat
agree
Agree
Strongly agree
Israel is a world center of high tech innovation
Israel is part of God's plan for the Jewish people
Israel is under constant threat from hostile neighbors who seek its
destruction
Israel is guilty of violating the human rights of the Palestinian people
Israel was established as a refuge for persecuted Jews
Israel upholds the social and political equality of all its citizens
In the PAST MONTH, how often have you actively sought news about Israel?
Please choose only one of the following:
Never
Once
Once a week
Every few days
Once a day
Several times a day
In the PAST MONTH, did you seek news about Israel from any of the following sources?
Only answer this question if the following conditions are met:
((news.NAOK == "2" or news.NAOK == "3" or news.NAOK == "4" or news.NAOK == "5"))
Please choose the appropriate response for each item:
No
Yes
American news media (e.g., CNN, Wall Street Journal, etc.)
Israeli news media (e.g., Ha'aretz, Ynet, etc.)
Arabic news media (e.g., Al Jazeera, Asharq al-Awsat, etc.)
European news media (e.g., BBC, Sky Network, etc.)
Social media (e.g., Facebook, Twitter, etc.)
How closely did you follow the 2015 election in Israel?
Please choose only one of the following:
Not at all
A little
Somewhat
Very much
Which bloc did you want to form the Israeli government after the recent elections?
Please choose only one of the following:
The center-right bloc (led by Benjamin Netanyahu and the Likud party)
The center-left bloc (led by Isaac Herzog and Tzipi Livni and the Zionist Union party)
Don't know
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How would you rate your feelings toward...?
Only answer this question if the following conditions are met:
country.NAOK == "1" or country.NAOK == "-oth-"
Please choose the appropriate response for each item:
Very positive
Somewhat
positive
Neutral
Somewhat
negative
Very negative
Don't know
Very positive
Somewhat
positive
Neutral
Somewhat
negative
Very negative
Don't know
Barack Obama
John Boehner
Benjamin Netanyahu
Hillary Clinton
Jeb Bush
Tzipi Livni
Scott Walker
Rubi Rivlin
How would you rate your feelings toward...?
Only answer this question if the following conditions are met:
country.NAOK == "2"
Please choose the appropriate response for each item:
Barack Obama
Stephen Harper
Benjamin Netanyahu
Thomas Malcair
Tzipi Livni
Justin Trudeau
Rubi Rivlin
How much have you heard about the Boycotts, Divestment, and Sanctions (BDS) campaign?
Please choose only one of the following:
No information at all
Not much information
Some information
A great deal of information
Thinking about products make in the following locations, do you personally...?
Please choose the appropriate response for each item:
Avoid purchasing/
Boycott
Purchase/
Promote
Neither
Never thought about
this
Jewish settlements in the West Bank
Israel
To what extent do you support...?
Please choose the appropriate response for each item:
Not at all
A little
Somewhat
Very
much
The expansion of existing Jewish settlements in the West Bank
The construction of new Jewish settlements in the West Bank
Israel is defined as both a Jewish and a democratic state. Which part of this definition is more important to you personally?
Please choose only one of the following:
Jewish
Democratic
Both are equally important
If it were possible, how interested would you be in visiting the West Bank?
Please choose only one of the following:
Not at all
A little
Somewhat
Very much
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Antisemitism
We'll now ask you a few questions about your views and experiences.
In your opinion, would you consider a non-Jewish person to be antisemitic if he or she...?
Please choose the appropriate response for each item:
No, definitely not
No, probably not
Yes, probably
Yes,
definitely
Criticizes Israel
Does not consider Jews living in {cntrytxt.shown} to be {nationality.shown}
Would not marry a Jew
Thinks that Jews are good with money
Opposes Israel's existence as a Jewish state
In the PAST 12 MONTHS, have you personally EXPERIENCED any of the following in {if((country=="1"), 'the United States',
if((country=="2"),'Canada', 'the country where you live'))} BECAUSE you are Jewish?
Please choose the appropriate response for each item:
No
Yes
Verbally insulted or harassed
Physically attacked
In the PAST 12 MONTHS, have you personally WITNESSED any of the following happen to Jew(s) in {if((country=="1"), 'the United States',
if((country=="2"),'Canada', 'the country where you live'))} BECAUSE they were Jewish?
Please choose the appropriate response for each item:
No
Yes
Verbally insulted or harassed
Physically attacked
In the PAST 12 MONTHS, how often, if at all, have you PERSONALLY heard or seen non-Jewish people in {if((country=="1"), 'the United States',
if((country=="2"),'Canada', 'the country where you live'))} suggest that:
Please choose the appropriate response for each item:
Never
Occasionally
Frequently
All the time
Jews have too much power in {cntrytxt.shown} (economy, politics, media)
Jews exploit Holocaust victimhood for their own purposes
The Holocaust is a myth or has been exaggerated
Israelis behave "like Nazis" towards the Palestinians
Jews are not capable of integrating into {nationality2.shown} society
The interests of Jews in {cntrytxt.shown} are very different from the interests of everyone else
In your opinion, how big a problem, if at all, is each of the following on your COLLEGE CAMPUS?
Only answer this question if the following conditions are met:
((student.NAOK == "1"))
Please choose the appropriate response for each item:
Not a problem at all
Not a very big
problem
A fairly big problem
A very big
problem
Not a very big
problem
A fairly big problem
A very big
problem
Expressions of hostility toward Jews by students
Expressions of hostility toward Jews by professors
Expressions of hostility toward Israel by students
Expressions of hostility toward Israel by professors
In your opinion, how big a problem, if at all, is each of the following at your WORKPLACE?
Only answer this question if the following conditions are met:
(employ.NAOK == "1" or employ.NAOK == "2")
Please choose the appropriate response for each item:
Not a problem at all
Expressions of hostility toward Jews
Expressions of hostility toward Israel
How often, if at all, do you feel that people in {if((country=="1"), 'the United States', if((country=="2"),'Canada', 'the country where you
live'))} accuse or blame you for anything done by the Israeli government BECAUSE you are Jewish?
Please choose only one of the following:
Never
Occasionally
Frequently
All the time
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To what extent, if at all, does the Israeli-Arab conflict impact how SAFE you feel as a Jewish person in {if((country=="1"), 'the United States',
if((country=="2"),'Canada', 'the country where you live'))}?
Please choose only one of the following:
Not at all
A little
A fair amount
A great deal
Although different people have different views as to what constitutes antisemitism, would you say that you have witnessed or personally been
subjected to antisemitism in any of the following contexts, since the beginning of this academic year (since September 2014)?
Please choose the appropriate response for each item:
No
Yes
From an individual student
In clubs/societies
In a lecture/class
In the student union
By my university administrative system
In another context
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BRI Application
We'll now ask you a few questions about Taglit-Birthright Israel.
Did you apply to go on a 2015 summer Taglit-Birthright Israel trip?
Please choose only one of the following:
No
Started but did not complete
Yes, completed
How important was each of the following in your decision to begin a Taglit-Birthright Israel application?
Only answer this question if the following conditions are met:
((round32.NAOK == "1" or round32.NAOK == "2"))
Please choose the appropriate response for each item:
Not at all
A little
Somewhat
Very
much
I always wanted to visit Israel
I wanted to learn more about Judaism
Friends told me it's a great experience
The trip is free
I wanted to meet other young Jews
I wanted to get to know Israelis
My parents wanted me to go
The trip is an important Jewish experience
My friends were applying
I thought it would be fun
I wanted to learn about the political situation in Israel
Other. Please describe below.
Describe what else influenced your decision to begin a Taglit-Birthright Israel application.
Only answer this question if the following conditions are met:
((whyapply_13.NAOK == "2" or whyapply_13.NAOK == "3" or whyapply_13.NAOK == "4"))
Please write your answer here:
Before your application to the 2015 summer Taglit-Birthright Israel trip, had you applied in the past?
Only answer this question if the following conditions are met:
((round32.NAOK == "1" or round32.NAOK == "2"))
Please choose only one of the following:
No, this was my first application
Yes, I've applied more than once
What is the MAIN reason you hadn't applied to go on a Taglit-Birthright Israel trip in the past?
Only answer this question if the following conditions are met:
((prevappl.NAOK == "0"))
Please choose only one of the following:
I was not yet 18
I had other commitments
I was or thought I was ineligible
I didn't want to travel to Israel then
I felt Israel was not safe
I wanted to be older when I went on a Taglit-Birthright Israel trip
I didn't feel time pressure
Other
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What is the MAIN reason you did not go on a Taglit-Birthright Israel trip in previous seasons?
Only answer this question if the following conditions are met:
((prevappl.NAOK == "1"))
Please choose only one of the following:
I was not offered a trip
There was no trip available on the dates I wanted to travel
I couldn't go on the same trip as family/friends
I had work/school obligations
I had personal/family obligations
I couldn't afford other trip expenses and/or the deposit
I had safety concerns
My parents thought it wasn't safe to go
Other
Which of the following statements describes the reasons you did not complete your summer 2015 Taglit-Birthright Israel application?
Only answer this question if the following conditions are met:
((round32.NAOK == "1"))
Please choose all that apply:
The application was too long
I realized I was not eligible for the trip
Choosing a trip was too complicated
I couldn't figure out what dates were available
I didn't really want to go
It's unsafe to travel to Israel
Other:
Were you ever contacted and encouraged by Taglit-Birthright Israel to complete your application?
Only answer this question if the following conditions are met:
((round32.NAOK == "1"))
Please choose only one of the following:
No
Yes
Did you tell your parents that you applied to go on a summer 2015 Taglit-Birthright Israel trip?
Only answer this question if the following conditions are met:
((round32.NAOK == "1" or round32.NAOK == "2"))
Please choose only one of the following:
No
Yes, before I applied
Yes, after I applied
Have you...?
Only answer this question if the following conditions are met:
((parentstold.NAOK == "1" or parentstold.NAOK == "2"))
Please choose the appropriate response for each item:
Yes
No
Consulted your parents about trip dates and options
Asked your parents for assistance with the application process
Asked your parents for financial assistance with the deposit
Updated your parents on whether you are going on a trip
Forwarded emails about the trip to your parents
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In the PAST SIX MONTHS, how often have you heard your JEWISH FRIENDS and ACQUAINTANCES your age say that...?
Please choose the appropriate response for each item:
Never
Rarely
Occasionally
Often
Israel is an unsafe travel destination
Taglit-Birthright Israel offers a fun opportunity to explore Israel
Their parents discourage traveling to Israel now
Their parents encourage participating in Taglit-Birthright Israel
Taglit-Birthright Israel trips are politically one-sided
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Never
Rarely
Occasionally
Often
They don't have an interest in visiting Israel
Taglit-Birthright Israel is appropriate only for college students
They don't want to travel to Israel because the policies of the current Israeli government are
objectionable
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Upbringing
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We'll now ask you a few questions about your upbringing.
What is your present religion, if any?
Please choose only one of the following:
Jewish
Christian
Atheist or agnostic
Nothing in particular
Something else. Please specify:
Where was your father born?
Only answer this question if the following conditions are met:
(( { TOKEN:ATTRIBUTE_3 } .NAOK == "1"))
Please choose only one of the following:
The United States
Canada
Israel
The Former Soviet Union
Other. Please specify:
Was your father born Jewish?
Only answer this question if the following conditions are met:
(( { TOKEN:ATTRIBUTE_3 } .NAOK == "1"))
Please choose only one of the following:
No
Yes
Is your father Jewish now?
Only answer this question if the following conditions are met:
(( { TOKEN:ATTRIBUTE_3 } .NAOK == "1"))
Please choose only one of the following:
No
Yes
Where was your mother born?
Only answer this question if the following conditions are met:
(( { TOKEN:ATTRIBUTE_3 } .NAOK == "1"))
Please choose only one of the following:
The United States
Canada
Israel
The Former Soviet Union
Other. Please specify:
Was your mother born Jewish?
Only answer this question if the following conditions are met:
(( { TOKEN:ATTRIBUTE_3 } .NAOK == "1"))
Please choose only one of the following:
No
Yes
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Is your mother Jewish now?
Only answer this question if the following conditions are met:
(( { TOKEN:ATTRIBUTE_3 } .NAOK == "1"))
Please choose only one of the following:
No
Yes
Were you raised...?
Only answer this question if the following conditions are met:
(mjew.NAOK == "1" or mjewnow.NAOK == "1" or fjew.NAOK == "1" or fjewnow.NAOK == "1")
Please choose only one of the following:
Reform
Conservative
Orthodox
Reconstructionist
Just Jewish
Sephardic
Other. Please specify:
During grades 1-12, how many years did you attend each of the following?
(Please select 0 if you didn't attend).
Please choose the appropriate response for each item:
0
1
2
3
4
5
6
7
8
9
10
11
12
Full time Jewish day school
Jewish supplementary school that met
several times a week (like Hebrew
school)
Jewish supplementary school that met
once a week (like Sunday school)
Overnight camp that had Shabbat
services and/or a Jewish education
program
If you were asked to read a text in Hebrew how much would you understand?
Please choose only one of the following:
Don't know Hebrew alphabet at all
Can read the letters, but not understand the words
Some of what I read
Most of what I read
Everything I read
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Final Thoughts
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Is there anything else you would like to add?
Please write your answer here:
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Submit your survey.
Thank you for completing this survey.
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The Cohen Center for Modern Jewish Studies at Brandeis University is a multi-disciplinary
research institute dedicated to the study of American Jewry and issues related to contemporary
Jewish life.
The Steinhardt Social Research Institute (SSRI), hosted at CMJS, uses innovative research
methods to collect and analyze socio-demographic data on the Jewish community.
Brandeis University