Rationales for the creation of applied models
Theories and principles of applied models
Applied work-based models
Building applied models from data
Building applied models from projects and programs
Building applied models from observational research and fieldwork
Building applied models from multiple-sources
Abstracting applied models for heritability and generalizability
Avoiding overfit to local realities, local data, local dimensions, in applied models
Ensuring heritability of applied models
Testing applied models in vitro (in a lab, in an artificial setting)
Testing applied models in vivo (in the world)
Scenarios (contexts) for applied modeling
Operationalizing / actualizing applied models
Different types of applied models
Adoption of (inheriting) applied models
Retrofitting applied models
Adding new modules to applied models
Cultural adaptations to applied models
Fine-tuning applied models for heightened accuracy and sensitivity
Testing the (in)efficacy of applied models
Distribution and publishing of applied models
Inspirations for applied models