Gender Data Review for SDGs Monitoring in Kenya and

Tanzania Presenter:

Kennedy Karani

Researchers:

Dr. Evans Gacheru

John Njoka

o DataShift Is an initiative that builds the capacity and confidence of civil society organisations to produce and use citizen-generated data.

o CIVICUS World Alliance for Citizen Participation is an international alliance of members and partners which constitutes an influential network of organisations at the local, national, regional and international levels, and spans the spectrum of civil society.

o IRES is a research and capacity development firm supporting the development community with skills and innovations on data science.

o Focus is to strengthen capacity of civil society to monitor SDGs

2

1. Background

2. Objectives of the review o Review gender indicators related to but not limited to, health, education, women's

economic empowerment and entrepreneurship, social exclusion of women and girls, water and sanitation, unpaid care and domestic work, equal opportunities for leadership.

o Map key gender players (both state and non-state actors) at national and sub-national levels.

o Review gender data collection methodologies, types and formats (including citizen-generated data), availability, accessibility and use, and gaps related disaggregation, interoperability, and usability; including highlighting case studies of good practice.

o Examine power dynamics, opportunities, and barriers to the generation, accessibility, harmonization, and use of gender data by civil society, government, and donors.

o Examine policy, legal, institutional frameworks, structures, cultures and financing mechanisms or lack-thereof (including investments) and how these support civil society, private sector, donors, academia, media, among other stakeholders (or not) to advance gender equality and the empowerment of women and girls.

3

3. Methodology used Mapping of the key gender players to identify the organizations to be studied.

Mapping criteria included players (both state and non-state actors) at national and the

sub- national levels, their approaches, for data collection and use.

Players grouped into 6 categories; Gvt (national or sub-national), Civil Society

Organizations (CSOs), Donors (Multilateral or Bilateral), Research/academia, Private

sectors and Media.

Data collection approaches included:

Desk review of documents of data policies and indicators of SDG 5 and related

gender indicators.

KIIs with selected organizations’ representatives sample from each category.

Case studies capturing good practices.

4

4. Preliminary findings: The NSOs in both countries have data disaggregated by sex for some SDGs

indicators. Kenya KDHS 2014, Kenya Gender Data Sheet 2011, 2015; Tanzania TDHS 2016, AIS 2015.

Some indicator are not consistent with SDGs indicators. Ex; Indicator on health under DHS report has no data on adolescent women for age grp 10-14 years. (3.7.2).

Legal framework and policies in place in both countries. Kenya: Constitution 2010, NGEC commission, Vision 2030, MTP II, commission on human rights; Tanzania: Vision 2025 for Tanzania Mainland; Zanzibar Development Vision 2020; Five Year Development Plan 2011/12–2015/16.

Some CSO have sectoral data that can compliment national data collected by NSIs. Example Uwezo’s – Education, NTA – Governance.

5

4. Preliminary findings… There are capacity building efforts by donor agencies such as UN Women on

gender data to gvt MDAs. Kenya MED, KNBS. However sustainability concerns exists - trained officers always transferred leaving the core department incapacitated.

In Kenya, an SDGs unit has been established.

6

4. Preliminary findings…….

In Kenya, Nakuru County, Lanet Location, localized monitoring for SDG 1, 3, 4, 5, and 6 through Nyumba Kumi (ten houses) concept been (Initiative by Chief Kariuki working with CIVICUS and Open Institute).

In Tanzania the localization of SDGs is yet to be implemented at the sub-national level (Districts).

7

4. Preliminary findings……. Data collection, analysis and management practices

Quantitative data gathering methods (surveys) is used by CSOs. Example UWEZO.

The Gap - Qualitative data (the whys) not collected in most cases.

Budget/Funding determines intensity of data collection.

Some software for data management and analysis include Excel, SPSS, CsPro and Stata. Data mainly in flat files (spreadsheets).

Metadata is weak.

Projects have case studies that can be used to measure qualitative aspects.

8

Preliminary findings……. Institutional analysis and capacities for gender monitoring of SDGs

Kenya

Constitution 2010 and other provisions give effect to gender issues.

Sex disaggregation not enshrined in MDGs but now in SDGs.

NIMES and CIMES working with dept of gender, KNBS & the SDGs unit to pursue this -work in progress with UN support.

Organizations have sector or project indicators.

Financing is heavily by donors…govt. investing in staff.

Access is mixed - cases of protectionism abound due to fear of data misuse but also for commercial reasons. Govt. indicates an open data policy but CSOs feel there is heavy bureaucracy.

9

Preliminary findings……. Institutional analysis and capacities for gender monitoring of SDGs

Tanzania

Gender issues has not been covered comprehensively in National plans and goals.

Organizations have sector or project indicators.

Financing is heavily by donors…govt is coordinating.

10

Preliminary findings……. Identifiable good practices

Kenya

KNBS/SDGs Unit’s efforts- A ministerial committee on SDGs with 31 members.

UWEZO’s education and literacy data.

CGD in Nakuru (Community Feedback).

Tanzania

UWEZO’s education and literacy data

11

Challenges CSOs have a challenge in accessing the data from the government

particularly in Kenya.

CSOs lack adequate capacity to collect and analyze data.

CSOs engage contracted consultants who sometimes only submit the reports – without raw data.

Lack of a database of key competencies required and capacities available.

Organizations are constrained by finances for data collection and analysis thus affecting the intensity of data collection.

Some of the data for the CSOs are not disaggregated by sex despite being a requirement by the donors.

Some organizations use different indicators and metrics from the ones proposed for monitor the SDGs.

12

Conclusion and Recommendations There is need for a platform bringing all stakeholders involved in gathering and using gender data together.

There is need for the organizations dealing with data both at the national and sub-national level to

strengthen open access to data to enhance availability of the data for possible users.

There is need to sustainably support training activities particularly on relevant methodologies of data

collection and data analysis among the stakeholders that will yield usable, comparable and interoperable

data.

A Gender data capacity assessment is required- database of key competencies required and capacities

available.

The government should ensure retention of trained staffs in the core departments to ensure continuity and

sustainability of the implementation of the SDGs.

Harmonize the national statistics with the SDGs indicators to allow for proper monitoring of SDGs.

There is a need to recognize social media as an important source of data. Social media interact with

citizens through citizen reporting initiative and gather data.

13