Centering community voice in data collection.

Welcome to Data Uncollected, a newsletter designed to enable nonprofits to listen, think, reflect, and talk about data we missed and are yet to collect. In this newsletter, we will talk about everything the raw data is capable of – from simple strategies of building equity into research+analytics processes to how we can make a better community through purpose-driven analysis.

Hello, there. Can I start with the cheesy first? (You know me!)

I missed talking to you in this space. Believe me; you push me to seek more ideas and voices from my local library. That effect continued without you and this space in the past two weeks (did it?). I?got into a comforting rabbit hole?became differently curious. I picked some reading on designing theatre plays in the Western world and choosing patterns of traditional clothes in the Eastern world. Completely different topics but there are some commonalities there. No particular reason why I picked them other than that I was passing by an interesting shelf on a not-the-usual floor at the library. I believe in those topics lies a range of fundamental community ideas on outlook towards data – as in how it is seen in non-traditional ways and settings. I am still reading, so there is nothing to report there yet. Nevertheless, I am back – ready to continue building this space with you.

Today I want to explore with you something I have been questioning for a while now – is there a framework we can design to guide us in centering community voice in our data collection in a non-extractive way? Of course, I mean a framework that will be evolving by nature.

This is not an easy task, considering that to respond to it, we will always have to start with defining the community we intend to engage in the data collection.?Community?is a complex word. Does it refer to the intersectional identity-based communities (by ethnicity, race, etc.)? Or is it a more simplistic view by neighborhood or zip code? Graeme Stuart, the author of the community engagement blog series ‘Sustaining Community’ (link included at the bottom of this article), beautifully captures some meaning. He says, “Communities are not homogeneous nor conflict free, but encompass diversity, competing interests and priorities, and unequal access to resources and influence. It is thus important to think about who is at the table when making decisions. An equity lens and a commitment to social justice mean that collective impact needs to place a priority on ensuring that marginalised or voiceless sections of the community have the opportunity to be engaged. It can even be worth asking ‘who?owns?the table?’?”

Clearly, “community” is a nuanced word, and going back to the original point, lack of clarity on it (“community”) adds a challenge to designing that pseudo-universal framework using which we ensure to center the community’s voice. For the sake of our topic, let’s say we have a mechanism to identify and establish who we mean by the community (and we will explore this more in a future edition). Now what?

For starters, when it comes to including a community in data collection, we must prioritize a strengths-based approach over a deficit-based approach. Deficit-based approach refers to collecting data around the collective community challenges. In contrast, the strengths-based approach refers to collecting data on the community’s strengths to enable individuals to solve the challenges they may identify. It is not a transparent black-and-white distinction as to which approach must be locked with which scenario. It also depends on the context. But, broadly speaking, to enable a community, leveraging a strengths-based approach in data collection allows you to collect data points that can lead to sustainable development and long-term growth.

Here is an example: say you want to collect data from the local community on youth growth and development. You recognize that your local community comprises many identities (such as race, ethnicity, nationality, and sexual orientation). A deficit-based data collection would mean asking the community questions about what can be improved in the city for youth development. On the contrary, a strengths-based approach asks what parts of the city and its offerings allow the youth to be their best self. The strengths-based approach focuses on the strengths of respondents, so you don’t create change?for?them but?with?them.

Another example would be – say, LinkedIn wants to identify new features for their product to support BIPOC professionals. Deficit-based data collection would ask self-identified BIPOC users to identify specific challenges that can be turned into platform features. On the contrary, a strengths-based approach would ask self-identified BIPOC users about their ways of engagement on the platform that make them feel most accomplished, (professionally) whole, and successful. Features can then be derived based on those identified indicators of success. This way, a change is not just created?for?BIPOC professionals but?with?them.

Using that knowledge, here is a starting point, an evolving community engagement framework I propose we can use when centering community voice in data collection. This model is derived from the core ideas of Strengths-based data collection techniques, Gender-based analysis model, Responsive Research method by Quinless and Corntassel, and some community engagement strategies.

(image description: a table with blue, gray, and green boxes that captures 5 steps of community engagement framework. The purpose of this framework is to collect data, with the community, in a process grounded in trust, empathy, and ethics).

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Working with the community in a non-extractive way requires trust, empathy, flexibility, and willingness to unlearn. This framework that we designed here is a start to learning while unlearning. Questions, observations, and continuous learning can refine every step of that framework. Use your imagination, curiosity, and empathy to refine this framework appropriately.

Let’s hear that community voice, pure and unadulterated, in our data.

***?So, what do I want from you today (my readers)?

Today, I want you to share your thoughts on this framework. What can we add here to make it more inclusive and sustainable?

*** Here is the continuous prompt for us to keep the?list of community-centric data principles?alive.

*** Link to ‘Sustaining Community’ blog series by Graeme Stuart:?https://sustainingcommunity.wordpress.com/about-2/