Decipher City began as an app project project for a Hack for Change event in Austin, Texas. The goal was to develop an app that could be used to report the qualitative experiences of citizens and visitors at different commercial locations across town. We began this project for three reasons:
1. There is both a need for safe space resources for marginalized people and a need to collect data (anonymized, protected data) on the experience of marginalized people in cities;
2. There is a larger need to understand racial, ethnic, and gender identity formation in cities from a more complex perspective than standard research methodology and existing data sets, such as the Census, currently permits. The racial boxes we’ve created to track ethnic experiences are inadequate for the true range of diversity in our society.
3. Our cities are in dire need of better methods and processes of public participation and public notice. Our citizens need better tools, better education about their right to support or protest city measures, and more accountability and transparency from their leadership.
Our initial crew of four people (a developer, a web designer/architectect, a city planner and a geographer) was inspired by the level of enthusiasm and engagement our project initially generated. We decided to expand the scope of our project beyond the app and to provide a platform for continued engagement about issues of race and equity in urban planning.
The original app can be accessed here: https://deciphercity.com/app
We are always seeking new contributors to add to the conversation. If you are interesting in writing a guest post or becoming a regular contributor, reach out to us at firstname.lastname@example.org
The Decipher City app tracks the experiences of citizens in locations across their city. It allows contributors to leave an anonymous review of a location and to indicate (if they chose) the identifies that best describe them. Users can select as many identifiers as they feel apply to them–there are no mutually exclusive racial or gender categories.