146 research outputs found
Can Terrorism Abroad Influence Migration Attitudes at Home?
This article demonstrates that public opinion on migration âat homeâ is systematically driven by terrorism in other countries. Although there is little substantive evidence linking refugees or migrants to most recent terror attacks in Europe, news about terrorist attacks can trigger more negative views of immigrants. However, the spatial dynamics of this process are neglected in existing research. We argue that feelings of imminent danger and a more salient perception of migration threats do not stop at national borders. The empirical results based on spatial econometrics and data on all terrorist attacks in Europe for the post-9/11 period support these claims. The effect of terrorism on migration concern is strongly present within a country, but also diffuses across states in Europe. This finding improves our understanding of public opinion on migration, spill-over effects of terrorism, and it highlights crucial lessons for scholars interested in the security implications of population movements
Are Tall People Less Risk Averse than Others?
This paper examines the question of whether risk aversion of prime-age workers is negatively correlated with human height to a statistically significant degree. A variety of estimation methods, tests and specifications yield robust results that permit one to answer this question in the affirmative. Hausman-Taylor panel estimates, however, reveal that height effects disappear if personality traits and skills, parents' behaviour, and interactions between environment and individual abilities appear simultaneously. Height is a good proxy for these influences if they are not observable. Not only one factor but a combination of several traits and interaction effects can describe the time-invariant individual effect in a panel model of risk attitude
Simplicity in Visual Representation: A Semiotic Approach
Simplicity, as an ideal in the design of visual representations, has not received systematic attention. High-level guidelines are too general, and low-level guidelines too ad hoc, too numerous, and too often incompatible, to serve in a particular design situation. This paper reviews notions of visual simplicity in the literature within the analytical framework provided by Charles Morris' communication model, specifically, his trichotomy of communication levelsâthe syntactic, the semantic, and the pragmatic. Simplicity is ultimate ly shown to entail the adjudication of incompatibilities both within, and between, levels.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68281/2/10.1177_105065198700100103.pd
'It's Reducing a Human Being to a Percentage'; Perceptions of Justice in Algorithmic Decisions
Data-driven decision-making consequential to individuals raises important
questions of accountability and justice. Indeed, European law provides
individuals limited rights to 'meaningful information about the logic' behind
significant, autonomous decisions such as loan approvals, insurance quotes, and
CV filtering. We undertake three experimental studies examining people's
perceptions of justice in algorithmic decision-making under different scenarios
and explanation styles. Dimensions of justice previously observed in response
to human decision-making appear similarly engaged in response to algorithmic
decisions. Qualitative analysis identified several concerns and heuristics
involved in justice perceptions including arbitrariness, generalisation, and
(in)dignity. Quantitative analysis indicates that explanation styles primarily
matter to justice perceptions only when subjects are exposed to multiple
different styles---under repeated exposure of one style, scenario effects
obscure any explanation effects. Our results suggests there may be no 'best'
approach to explaining algorithmic decisions, and that reflection on their
automated nature both implicates and mitigates justice dimensions.Comment: 14 pages, 3 figures, ACM Conference on Human Factors in Computing
Systems (CHI'18), April 21--26, Montreal, Canad
Efficiently Learning Structured Distributions from Untrusted Batches
We study the problem, introduced by Qiao and Valiant, of learning from
untrusted batches. Here, we assume users, all of whom have samples from
some underlying distribution over . Each user sends a batch
of i.i.d. samples from this distribution; however an -fraction of
users are untrustworthy and can send adversarially chosen responses. The goal
is then to learn in total variation distance. When this is the
standard robust univariate density estimation setting and it is well-understood
that error is unavoidable. Suprisingly, Qiao and Valiant
gave an estimator which improves upon this rate when is large.
Unfortunately, their algorithms run in time exponential in either or .
We first give a sequence of polynomial time algorithms whose estimation error
approaches the information-theoretically optimal bound for this problem. Our
approach is based on recent algorithms derived from the sum-of-squares
hierarchy, in the context of high-dimensional robust estimation. We show that
algorithms for learning from untrusted batches can also be cast in this
framework, but by working with a more complicated set of test functions.
It turns out this abstraction is quite powerful and can be generalized to
incorporate additional problem specific constraints. Our second and main result
is to show that this technology can be leveraged to build in prior knowledge
about the shape of the distribution. Crucially, this allows us to reduce the
sample complexity of learning from untrusted batches to polylogarithmic in
for most natural classes of distributions, which is important in many
applications. To do so, we demonstrate that these sum-of-squares algorithms for
robust mean estimation can be made to handle complex combinatorial constraints
(e.g. those arising from VC theory), which may be of independent technical
interest.Comment: 46 page
Genetic influences on spatial ability: Transmission in an extended kindred
Transmission of six spatial tests, Card Rotations, Cube Comparisons, Group Embedded Figures, Hidden Patterns, Mental Rotations, and portable Rod and Frame, is examined among 73 members in four generations of an extended kindred. Nonadditive genetic variance is substantial for one of the six tests, Card Rotations. Whether this nonadditive genetic variance is due to a major autosomal gene is equivocal based on results from segregation and linkage analysis. There is no evidence for genetic variance for Mental Rotations or Hidden Patterns, in contrast to previous findings suggesting major gene involvement (Ashton et al. , 1979). If spatial ability is due, in part, to an autosomal major gene, the gene has variable expression (reflected in different tests) or genetic heterogeneity is pronounced.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44106/1/10519_2005_Article_BF01065907.pd
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