  The Galaxy Zoo has provided morphological data on many galaxies. Several
biases have been identified in the Galaxy Zoo data. Here we report on a newly
discovered selection effect: astronomers interested in studying spiral galaxies
may select a set of spiral galaxies based upon a threshold in spirality (the
fraction of Galaxy Zoo humans who report seeing spiral structure). SpArcFiRe is
an automated tool that decomposes a spiral galaxy into its constituent spiral
arms, providing objective, quantitative data on their structure. SpArcFiRe
measures the pitch angle of spiral arms. We have observed that when selecting a
set of spiral galaxies based on a threshold on spirality, the pitch angle of
spiral arms appear increase with redshift. We hypothesize that this is a
selection effect: tightly-wound spiral arms become less visible as images
degrade with increasing redshift, leading to fewer such galaxies being included
in the sample at higher redshifts. We corroborate this hypothesis by
artificially degrading images of nearby galaxies, then using a machine learning
algorithm trained on Galaxy Zoo data to provide a spirality for each
artificially degraded image. It correctly predicts that spirality decreases as
image quality degrades. Thus, the mean pitch angle of those galaxies remaining
above the spirality threshold is higher than those eliminated by the selection
effect. This demonstrates that users who select samples of galaxies using a
threshold of Galaxy Zoo votes must carefully consider the possibility of
selection effects on morphological measures, even if the measure itself is
believed to be objective and unbiased. Finally, we also perform an empirical
sensitivity analysis to demonstrate that SpArcFiRe's output changes in a smooth
and predictable fashion to changes in its internal algorithmic parameters.
