The Journal of College and University Student Housing - Volume 45, No. 2 - 59

James C. Stoner

Additionally, while this study mitigated
structural and mechanical bias within the RA
hiring process scoring metrics, the study gave
no consideration to applicant demographics
and thus did not address potential existing
structural bias based on demographics. Recognizing existing concerns with the application
of "big data" (O'Neil, 2017) in hiring processes,
some practitioners may express concern about
replicating existing employee attributes year
after year. Specifically, using performance data
to inform hiring algorithms from a year with a
non-diverse staff may insert mathematical bias,
thus skewing data for those privileged with
similar demographics (e.g., race, ethnicity, international status, and gender identity) in the
originally studied applicant pool. Fortunately
in this study the institution's candidate pool
and staff each year was highly diverse and overrepresentative of the residential population in
some demographic categories such as race and
ethnicity. At institutions with low existing diversity in their candidate pools and staff teams,
employing such an analysis may trade one bias
(built-in scoring bias, most notably against
introversion or extroversion) for another (replication of diversity-or lack thereof-in successful candidates year to year). This concern
may be addressed by not employing a full analysis with performance evaluations, but rather
simply applying weights based on job description and associated responsibilities.
It should also be noted that there are many
factors contributing to job performance beyond
the candidate's potential evaluated within application and interview processes. The study
design did not consider the capacity to receive
training, supervisory style and relationship,
personal motivation, career aspirations, and

The contextual application of
statistics in a nontraditional
manner (i.e., using results to
inform variables instead of
allowing variables to inform
results) demonstrates the value in
attempting to reverse-engineer RA
hiring practice as one method to
strengthen the hiring process.

other such factors. Similarly, the study design
also limited the ability to explore the potential
success of candidates who were not hired due
to the fact that no performance evaluations
existed for them.
Finally, the conclusions drawn are limited
by the stacking of data analyses year after year.
Given that each applicant pool was reasonably
unique in terms of candidates, using results
from a previous candidate pool to inform hiring
decisions on a different applicant pool may cause
some practitioners to pause. Although performance evaluation scores would not be available,
comparing hiring process scores for candidates
who apply in subsequent years may illuminate
any year-to-year discrepancies between scoring
weights. Additionally, this concern is mitigated
somewhat by the logistics of the two hiring processes not changing between years. Departments
providing a training program before hiring (Carrenti & Tuttle, 1972) may be able to alleviate this
concern by conducting performance evaluations
prior to making job offers.

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The Journal of College and University Student Housing - Volume 45, No. 2

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