[15] Project Planning…so far

Following on from my blog just before Christmas, I’ve sat down to think about the approach to my project, a timeline and take a look at the literature. Here are my thoughts so far:

Research Idea One: Looking into PIP

What am I researching?

Two options are possible under this banner based on my current thoughts:

How accessible is a digital-as-default application for a cash transfer program for people with disabilities?
A comparison of two cash transfer programs for people with disabilities: PIP and ADP (ADP is the Scottish version of PIP and has had a staggered intro since March 2022)

What does the current literature say?

There is a lot of literature on the structural and social inequalities faced by people with disabilities.
Cash transfer programs like PIP/ADP are designed to bridge the gap regarding income inequality and in theory allow people with disabilities, though the execution of these programs means there is varied success.
The execution of the PIP program has received a lot of negative feedback – academically and by the disabled community.
E-goverment services to-date have been inconsistent with meeting the needs of people with disabilities.
There are some people with disabilities who believe they are treated as second class citizens under capitalism and patriarchy and that some governments actively reinforce an othering of disabled people.

Approach and Concerns?

Current thinking is a full text output. My approach to either of these questions would be predominately based on interviews with actual claimants (successful or not). The DWP does publish data that I can use but I have previously established this is a poor quality dataset and is limited in its scope. The main concern here is that I will be interviewing people with disabilities and I will need to establish if this is a vulnerable population for the ethics committee.

Research Idea Two: CfA Data Tool

What am I researching?

I still need to have a session with the team to understand the requirements in more detail but my toppling is:

Modelling change factors in wealth inequality across African nations.

What does the current literature say?

Research seems to center on: macroeconomic factors, links to health and education outcomes, taxation policies, the impact of colonialism
- Seems a lot of inequality > health outcome focused research…
Have to search for articles on each country to find microeconomic factors (as expected) – so will need to pick which countries to focus on for a narrower lit review. I pulled a few from Algeria and South Africa just as a test as this highlighted the main focus on health and education outcomes as an outcome of wealth inequality.

Note I need to do some more reading to consolidate thought on themes and literature funnel

Approach and Concerns?

This would be an artefact (forecasting tool) with a write-up that described what factors were chosen and how. I would have to decide these factors. My main concern is my lack of data engineering skills and whether I would need to build the actual models or work with a team to do so.

UPDATE: I had a call with the program director at CfA – they are currently in flight with cleansing, validating and mapping existing data to get it ready to be a training set for ML/AI. Their timeline to have the training set ready is only end of Q2 (June). As this is too late for me to do any meaningful work and submit a project, we discussed the idea that I would look for additional data sets to augment the training set & tool. I would need to work to map the data into their existing structures. I need to see if this is a valid project – I imagine that I would do a write up to reflect on the data sourcing process and explain the impact of the datasets being added into the tool (e.g. it helped add an additional dimension to the tool such as AGE that showed a lifetime inequality gap).

This is the link to the tool: https://gendergap.africa/
This is the supporting website: https://medium.com/wanadata-africa/gendergap-africa-67d6e36c075
Here is the latest report on the program: https://open.africa/dataset/global-gender-gap-report-2023

Next Steps: