IEEE Technology and Society Magazine - March 2018 - 88

one-half of one percent of the variance. Even when perceptions of actor trustworthiness, issue attitude, and ideology are included in the model in Step 2, UAV purposes
continue to predict the most variance in public support,
followed by perceptions of end-user trustworthiness.
Taken together, our results support H3 that UAV purpose is among the most important predictors of UAV
support. The B statistics in Table 4 indicate, for example,
controlling for all other variables (Step 2), use of UAVs
for security purposes reduces support by 1.15 points on
the 7-point scale, compared to environmental purposes.
Using UAVs for economic (rather than environmental)
purposes reduces support by 0.58 points. Additionally,
our analyses find that our sample supported use by government more than by businesses (Table  4). Further,
issue attitude, trustworthiness perceptions, and ideology
do not completely explain the effects of purpose and
end user. We know this because purpose and end user
remain significant predictors of support even when
those other variables are included in the model.

Response to RQ4: Political Polarization can be
Evoked, but is Small and the Pattern
Changes over Time
To examine whether certain conditions appeared to elicit
politically polarized responses, and whether those conditions changed from 2014 to 2015, we tested for differences in the effect of ideology dependent on UAV purpose,
actor, and year. Specifically, we examined the four-way
interaction in a multiple regression while including all subsumed interactions and main effects also in the model.
Due to space constraints, the full model results are not
presented but are available from the first author. However,
the four-way interaction was statistically significant. This

indicates that political polarization of support (i.e., the
relationship between ideology and support) changed
dependent upon UAV purpose, end user, and year.
To clarify how political polarization varied, Table 5
shows the strength of the ideology-support relationship
under different conditions and Figure 4 illustrates the
predicted mean support for UAVs dependent on the different factors. In Figure 4, the conditions under which
significant ideology-support relationships were apparent are highlighted by the labeled bars. As shown in
Table 5, our hypothesis (H4) was partially supported:
polarization of support depended both on UAV purpose
and end user. Specifically, ideology correlated with use
of UAVs for environmental purposes by government in
both 2014 and 2015 (Table 5 respective rs = -0.27,
-0.32, ps < 0.05), with the negative correlations indicating that conservatives were less supportive of UAVs
than liberals under those conditions. In addition, Table
5 and Figure 4 show that use of UAVs for security resulted in polarization such that conservatives were more
supportive of that use in both 2014 and 2015 - but the
polarization was associated with different end users in
2014 (business) and 2015 (government).
Finally, although the results are partially supportive of
our hypothesis, we note that the effect of ideology (and
thus political polarization) is generally small, only accounting for a fraction of a percent of the variance in public support for UAVs. This amount is not always statistically
significant (see Table 5). In addition, the four-way and all
three-way interactions became non-significant when issue
attitudes and trustworthiness variables were included in
the model. This suggests that changes in polarization over
time are due to the differences in issue attitudes and trustworthiness ratings between our 2014 and 2015 samples.

Economic
Liberal-Govt

Environment
Liberal-Business

5.00 (a)

3.87

2.90

4.76

3.86

3.06
Security

5.70 (a)

2015

5.46

2014

Security
Conservative-Govt

Economic

Environment

Conservative-Business

Notes: Bars representing the conditions under which there occurred significant relationships between ideology
and support are labeled. (a) Ideology-support correlation but not the ideology regression coefficient was significant in 2015.
Figure 4. Predicted UAV support by year, UAV purpose, UAV end-user, and ideology (computed at -1 and +1 standard deviation
from the sample mean ideology).

88

IEEE Technology and Society Magazine

∕

march 2018



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