Kenyan Government have historically not
collected comprehensive data
disaggregated by disability.
The problem with data
(And what to do about it)
fortunately, The Government of Kenya together with United Kingdom Government Co-hosted and International Disability Alliance (IDC) in 2018. One of the commitments that Kenya made was to promote collection of accurate data on Persons with Disabilities, disaggregated by gender, age, disability and geographic location for the use in planning and programming. The Ministry also signed up to an Inclusive Data Charter (IDC) champion.
The Ministry in consultation with various key stakeholders launched the development of an Inclusive Data Charter Action Plan whose main aim is to guide and enhance deliberate collection and use of inclusive disaggregated disability data in both State and non-State agencies.
Moreover, this action plan will guide the roadmap towards 2023 when the Kenyan government has made the commitment of conducting disability survey.
The cabinet administrator Mr. Patrick Ole Ntutu made this commitment and was received with ululation during the action plan launch on 30th November 2021 by both live coverage and virtual participants.
The message was emphasized the involvement of persons with disabilities and OPDs.
This would enhance, budgeting, planning and enhanced service delivery by all duty bearers.
The second and proper disability survey will be a collaborative effort in 20223 by the Kenya beural of statistics, ministry of public service, gender senior citizens, special programmes.
so, what are the barriers in data collection in Kenya?
the social model identifies several barriers
to the collection of data from reporting
tools; for example, people with disability
may communicate differently, have barriers
to accessing mainstream emergency
services (such as the police), and face
discrimination when giving evidence or
telling their story.
Some of the obstacles people with
disability can face trying to report them
experiences may include:
• Have trouble communicating, or not
being given access to devices or
translators to help them communicate.
• Having trouble physically accessing
external help (for example, police).
• Having difficulty being believed or taken
• Having trouble being seen as credible
• Being coerced into not reporting
their experiences or reporting false
• Not being legally allowed to testify due
to their disability.
• Being afraid for their safety upon
reporting a crime.
• Not being aware that what is happening
to them is a crime, or
• Not knowing how to get help.
Policy makers should bear these issues in
mind when seeking and reporting on data
regarding people with disability. They
should also understand that persons with disabilities are often not captured in regular
data capture, which is not disaggregated.
Why duty bearers need to understand
Disaggregated data has been broken down
by detailed sub-categories, for example, by
marginalised group, gender, race, or level
of education, income, etc. Disaggregated
data can reveal inequalities that may not be
fully reflected in aggregated data.
Why is data disaggregation
Fully disaggregating data helps to
expose hidden trends. It can enable the
identification of vulnerable populations, for
instance, or help establish the scope of the
problem and make vulnerable groups more
visible to policymakers.
*A word about the census
The 10-yearly Kenyan Census is the
usual go-to for a snapshot of the nation.
However, in the 2019 census it didn’t directly ask about
disability as per the standard definitions. As a public policy scholar, I observe the intent of the Washington Group questions was not to focus so much on the conditions that cause the functional problem, but to talk about the functioning because that's where you're going to make the interaction with the environment work. It isn’t the diagnosis, but how the diagnosis manifest itself in terms of functioning that creates the lack of connection between the person and the environment.
According to the technical WGQ committee that it's not sufficient to get questions in just one area; it is necessary to get full information in all of the parts of that overarching disability definition. In 2001 there were a lot of data needs but a lot of poorly collected and confusing data. They were in a position where they really needed to stop doing what they had been doing, because it wasn’t getting them where they wanted to be from a data standpoint.
How the inclusive chatter will serve the data administration?
As disability sausage media we opine There are two kinds of administrative systems. There are administrative systems that are not related to disability and cover a broader population. All children in school are in the Kenyan Education Management Information System, for example. If it was possible to identify children with disabilities within that system it would be possible to disaggregated indicators obtained from the system.
There are other administrative systems that are targeted for Kenyan with disabilities and depend on people applying to the program and meeting eligibility criteria. For instance, the cash transfer targeting the severe persons with disabilities. It is ideal to link administrative data with a broader population data system. The administrative data provides information on those who have applied and met the eligibility requirements. If the system also obtains information using the general functioning questions used in representative data collections then it is possible to see how many people in that system are similar to people identified, for example, in the census but who are not in that system. Cross-walking across data systems really increases analytic capability, which then increases the amount of data you have for policy.
As disability sausage media we observe
Without high-quality data, it is difficult
for national and county governments and organisations to
plan policies and programs to prevent
violence against and abuse, neglect and
exploitation of people with disability. Also its difficult to access the service delivery.
Furthermore, Data is needed to set goals and measure
success against these goals and to
allow others to hold governments and
organizations accountable for delivering
on sustainable development goals.
As a public policy scholar, we advise Before using statistics, one should take a
look at how they were gathered.
Consider who conducted the
survey, who participated, and,
crucially, who didn’t. Ask why.
2. Balance data with lived experience
by contacting the relevant OPDS organizations of persons with disabilities
for their view of the data
and position on some issues. Ask if
the experiences of their members
supports the data. Some OPDs and their representatives
may have research of them
own to add to the story.
All in all, there will be a lot of evolving opportunities for data collection that we're not using right now, like crowdsourcing or big data, that can be taken advantage of.
Again, my personal take home is, always understand the process by which the data were collected in terms of how they will be used. It doesn't have to be perfect; it has to be fit for use. Don't discard data just because it's not fit for every use. This requires a certain amount of data sophistication that isn’t as widespread as we would like but, hopefully, we are making progress. There are a lot of opportunities in the future and we can use current data even if they're not perfect as we make improvements.
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The views expressed here are for the author and do not represent any agency or organization.
Mugambi Paul is a public policy, diversity, inclusion and sustainability expert.
Australian Chief Minister Award winner
“Excellence of making inclusion happen”