| Ontological challenge: Different data and units of analysis (seeming distinct phenomena) |
Broaden the phenomenon: areas of inquiry by unit; collect shared data with standard protocol. Form groups that develop data sets for multiple disciplines |
Local boundaries: defense of local silos and territories is common (labs, departments) |
Integrate local networks: meet often, use central desktops, span labs and departments; seed grants that encourage shared students/trainees |
Imbalance challenge: intellectual representation is uneven and unequal (same for attributions of authorship) |
Form a confederacy of representatives: make sure multiple disciplines are represented; include broad demographics; form subcommittee to evaluate progress toward solutions and integration |
| Methodological challenge: different methods (distinct modes of inference) |
Use more expansive methods: methods for new data and spanning different units of analysis |
Disciplinary boundaries: jurisdictional disputes across professional and disciplinary boundaries are common (disciplines) |
Integrate inter-university networks: expand collaborations, build partnerships, run special sessions and conferences |
Alignment challenge: rule misalignments arise across administrative units (for example, funding rules) |
Write the rules: create new positions; write new rules; develop metrics that facilitate transdisciplinary promotion (new standards) |
| Epistemological challenge: different concepts/understandings make cross-disciplinary discourse problematic (threatened naiveté) |
Develop systemic thinking: frequent meetings; manage the meetings; create general, shared baseline understanding through discussions and shared bibliographies and glossaries from multiple disciplines |
Reproduction challenge: boundaries reproduce themselves and favors traditional silos and disciplines |
Sustain mixing: develop mixed training; identify receptive publication outlets; identify sister centers and career opportunities |
Ambiguous goals: different goals exist in heterogeneous coalitions |
Negotiate: horse-trade/log roll on issues; actively align goals among departments and organizations (for example: March of Dimes (MOD)—sees Stanford as an intellectual risk-taking partner and a fundraising opportunity; Stanford Research Institute (SRI International)—sees it as a subcontract, State Public Health sees it as a partner) |
