Chapter 14 Code of conduct
Contributors: Jade Benjamin-Chung, Ben Arnold
14.1 Group culture
We strive to work in an environment that is collaborative, supportive, open, and free from discrimination and harassment, per University policies.
We encourage students / staff of all experience levels to respectfully share their honest opinions and ideas on any topic. Our group has thrived upon such respectful honest input from team members over the years, and this document is a product of years of student and staff input (and even debate) that has gradually improved our productivity and overall quality of our work.
If Ben is your PI, be forewarned that he tends to batch his email communication (~30 mins in the morning and afternoon, 15 mins mid-day), and doesn’t tend to answer Slack or email during evenings or weekends. If you need to reach him urgently then give him a call or text on his mobile.
14.2 Protecting human subjects
All lab members must complete CITI Human Subjects Training and share their certificate with Ben. We will will add team members to relevant Institutional Review Board protocols to ensure they have permission to work with identifiable datasets.
One of the most relevant aspects of protecting human subjects in our work in the Data Coordinating Center is maintaining confidentiality and data privacy. For students supporting our data science efforts, in practice this means:
- If you are using a virtual computer (e.g., Google Cloud, AWS, Optum), never save the data in that system to your personal computer or any other computer without prior permission.
- Do not share data with anyone without first obtaining permission, including to other members of the Proctor Foundation, who might not be on the same IRB protocol as you (check with Ben or the relevant PI first).
- NEVER push a dataset into the public domain (e.g., GitHub, OSF) without first checking with Ben to ensure that it is appropriately de-identified and we have approval from the sponsor and/or human subjects review board to do so.
Remember, data that looks like it does not contain identifiers to you might still be classified as data that requires special protection by our IRB or under HIPAA, so always proceed with caution and ask for help if you have any concerns about how to maintain study participant confidentiality. For example, the combination of age, sex, and geographic location of the individual’s town or neighborhood is typically considered identifiable.