Implement initialisation strategies for new attributes.

[pausz]

If a location/context is not specified (ie, country) in a simulation, what would be the defaults for:

• paid_employment Implement intialisation strategy for paid_employment #185
• partnered Implement intialisation strategy for attribute partnered #186
• control_over_wages Implement initialisation strategy for control_over_wages #187
• sexual_autonomy Implement intialisation strategy for sexual_autonomy #188
• urban Implement intialisation strategy for urban #189
• education_attainment Implement intialisation strategy for education_attainment #190

For instance, for age and sex ratio fpsim uses a default age pyramid from a specific location and a specific year. What would be the equivalent default source data for the other attributes?

[mzimmermann-IDM]

We will use country specific data for the new inputs from Kenya DHS. I'll make an issue to list all of the data points we need and I can pull them.

[mzimmermann-IDM]

I'm thinking about how is best to do this for the parameters that are dynamic like the work and decision making metrics. These will change over time via a function, but that leaves the question of how to initialize. Do we just pick an age (say age 15) and use the population distribution at that age? That would be easy but I'm afraid our function won't have enough power to account for changes over the whole lifetime. Let me brainstorm with @MObrien-IDM .

[pausz]

Empowerment data covers the range 15<= age < 50. There remains the question on how to initialise metrics for women aged < 15 and >=50.