Over the next 10 years, the City of Ottawa along with community partners, agencies and institutions will work across sectors to improve the safety, health and well-being of Ottawa residents. The Community Safety and Well-Being (CSWB) Plan will guide these efforts.
Data and research are central to the Community Safety and Well-Being Plan. The Community Safety and Well-Being Office has developed a way to measure success and guide actions based on data through the Performance Measurement Framework - Community Safety and Well-Being. The Framework helps understand where the plan is making positive change and where more work is needed. It identified three pillars to measure progress:
Pillar 1: Ottawa population-level indicators look at key information about safety and well-being in Ottawa. These indicators are important to understand how the entire population of Ottawa is doing but are areas where the municipal government is not solely responsible for the outcome. Rather, the purpose of this level of measurement is to provide a centralized source of publicly available information. The population indicators also provide a frame of reference for the actions taken under the CSWB Plan.
Pillar 2: CSWB Plan stakeholder-level indicators keep track of the Community Safety and Well-Being Office’s operations related to stakeholder partnership and community engagement, such as meetings, funding contributions and partnerships, and evaluate their effectiveness. This pillar also involves collecting common indicators from agencies funded by the City of Ottawa under the Community Funding Framework.
Pillar 3: Program-intervention level indicators are used to evaluate Community Safety and Well-Being programs and projects.
The data and the dashboard pages serve as a tool to help people understand data, empowering them to make informed contributions towards community change and enhance overall community well-being. The pages are a work in progress, and we welcome your feedback as we continue to develop them.
Collecting and analyzing sociodemographic data can help to remove barriers to health and social services, identify needed community supports, and work toward equity. While data provides valuable insight, it is important to recognize its limits, such as under-representation of groups and communities due to barriers and lack of data/data gaps.
Our history of systemic racism, sexism and colonization has resulted in deep social inequities. It is time to harness and reposition the potential of data to shed light on these deepening inequalities and enable solutions and change for an equitable community.
We recognize we need quality person-level gender and socio-demographic (age, sex, race, ethnicity, Indigenous identity, etc.) data to properly understand and gauge if we are meeting the needs of all residents. Without gender and socio-demographic data, we risk taking a ‘one-size-fits-all’ approach and implement programs and services that do not consider the specific needs and barriers experienced by Indigenous and Black communities, women and gender diverse people, and equity-deserving groups in Ottawa.
The Community Safety and Well-Being Office is committed to enhancing the collection of socio-demographic information through the performance measurement framework, with the aim of bridging existing data gaps and ensuring a more comprehensive and inclusive representation of all communities.
Collecting socio-demographic data and utilizing disaggregated data*** is complex, requires significant time and resources, and presents challenges for effective and lasting implementation. We commit to a careful and thorough approach to ensure that the process of data collection, reporting and use does not create problems like limiting access to services, causing harm or reinforcing stereotypes.
The dashboard pages are tools to help people understand data, empowering them to make informed contributions towards community change and enhance overall community well-being. The pages are a work in progress, and we welcome your feedback as we continue to develop them.
***Disaggregated data is the term for breaking down data into specific populations. This is important to understand how different groups in the city experience inequity.