Do’s and Don’ts of starting new academics disciplines
2. Do study existing disciplines that overlap the new discipline, and how they began and took hold
3. Do build a social network of all the faculty currently teaching aspects of the discipline
4. Do have a very good answer to the “Why now?” question
5. Do align with existing conferences (only start new ones later)
6. Do align with special issues of existing journals (only start new ones later)
7. Do align with existing professional associations (only start new ones later)
8. Do encourage new sections in popular textbooks (only start whole new ones later)
9. Do generate a list of grand challenge problems to solve, and practical next steps on each
10. Do create and post freely available introductory lectures, including case studies.
1. Don’t expect the “discipline’s brand” to become big over night (this work takes decades)
2. Don’t forget to co-create a new profession in business and government at the same time
3. Don’t forget that professions need tools – what are the new tools the discipline builds?
4. Don’t become too rigorous too fast (early mathematization can create a narrow niche discipline)
5. Don’t forget to ask if others have tried and failed (or only partly succeeded)
6. Don’t forget the discipline needs a pipeline of doctoral students who want to be faculty
7. Don’t forget the profession needs practitioners willing to give themselves new job titles
8. Don’t forget someone has to hire the undergraduate, master, and doctoral students
9. Don’t forget new disciplines require accreditation for programs and certification for practitioners
10. Don’t forget to be persistent – there will be many up’s and down’s along the way
Most important of all – relate the new discipline to something in the world that is evolving rapidly (entities), and strive to deeply understand the evolution of the ecology of those entities. Disciplinarians should be creating case studies, and sharing data sets about the entities, even as the theoretical foundations are put in place. Ultimately, the quality of the discipline is tied to the quality of data about the entities being studied.