  We present the results of Galaxy Nurseries project, which was designed to
enable crowdsourced analysis of slitless spectroscopic data by volunteer
citizen scientists using the Zooniverse online interface. The dataset was
obtained by the WFC3 Infrared Spectroscopic Parallel (WISP) Survey
collaboration and comprises NIR grism (G102 and G141) and direct imaging.
Volunteers were instructed to evaluate indicated spectral features and decide
whether it was a genuine emission line or more likely an artifact. Galaxy
Nurseries was completed in only 40 days, gathering 414,360 classifications from
3003 volunteers for 27,333 putative emission lines. The results of Galaxy
Nurseries demonstrate the feasibility of identifying genuine emission lines in
slitless spectra by citizen scientists. Volunteer responses for each subject
were aggregated to compute $f_{\mathrm{Real}}$, the fraction of volunteers who
classified the corresponding emission line as "Real". To evaluate the accuracy
of volunteer classifications, their aggregated responses were compared with
independent assessments provided by members of the WISP Survey Science Team
(WSST). Overall, there is a broad agreement between the WSST and volunteers'
classifications, although we recognize that robust scientific analyses
typically require samples with higher purity and completeness than raw
volunteer classifications provide. Nonetheless, choosing optimal threshold
values for $f_{\mathrm{Real}}$ allows a large fraction of spurious lines to be
vetoed, substantially reducing the timescale for subsequent professional
analysis of the remaining potential lines.
