Data Day 2020

We are excited to announce Data Day 2020, coming Friday, March 13 2020!

Location: Rainier Avenue Church

Top session choices:

  • Creating a Data Culture
  • Data for Advocacy
  • Data Quality (Train the Trainer)
  • Focus Groups Basics
  • Introduction to Qualitative Data Analysis
  • Introduction to Data Visualization
  • Painless Processes
  • What About Staff?
  • Working With Public Data

What is a Public Sociologist and Why Are you Touching our Data?

By: Janae Teal and Meredith Williams

Let’s be real. None of us grew up dreaming of being a public sociologist. Janae wanted to be a doctor, a waitress, or (okay, pulling back the curtain here), a nun. Meredith wanted to be a lawyer because she heard they make LOTS of money which sounded great as a kid. We wanted to be what we had heard about–what we were told were “real” or valid jobs.

We both grew up working class. Our parents worked in auto body shops and tree tops more than offices. We wanted to be something exciting, like we had seen on TV, or read about in books. When Janae started college, she was a microbiology major. Which was perhaps not a great fit, considering she doesn’t tend to like things that are micro. Or biology-y. Meredith was a consumer affairs major, because she wanted to be Ralph Nader.

And then…we found Sociology. Sociology gave us the language to understand our lives, like how expensive it is to be poor, and the school-to-prison pipeline. It helped us to zoom out and see things from further away, and to see life is complex and messy, with so many intersecting factors. So, here we are.

Public Sociology Star Wars

One of the values that unites all of us at ML Whalen Consulting is our shared identity as Public Sociologists. So what is this? What does it mean? Why should you care?

To start, we are all trained as sociologists. This means a few things:

First, we have received extensive (seriously, Jedi level) training in social science research methods, including a wide variety of quantitative and qualitative approaches to collecting and analyzing data. That means we can do anything from writing a survey to gathering oral histories, then we can turn around and make predictions about social trends like we work with crystal balls and tea leaves. Don’t worry, we use our powers for good and not evil (but we’re sociologists, so of course we ask…who even gets to define what is “evil” in the first place…?).

Second, we have read, thought, fought and taught about social stratification for a huge chunk of our lives. We put everything through the lens of equity, thinking about race, class, gender, sexuality, immigration status, language, size, ability, and all the other ways our intersecting identities and social locations impact our lived experiences and opportunities. This doesn’t mean we think we know everything–it means we know we don’t, and we are ready to listen and learn. This does mean that we are TERRIBLE people with whom to watch TV. We will call out all the racist and sexist tropes. Hell, we make drinking games out of them (“Heterosexual love saves the day! Drink!”), as we rant about representation. But luckily, you don’t have to watch TV with us!

This doesn’t mean we think we know everything–it means we know we don’t, and we are ready to listen and learn.

Third, we have been trained to look at the big picture, and the connections. When we talk about inequality, we are talking about structures, institutions and norms. When we talk about solutions, we don’t talk about band-aids—we talk about real, systemic, sustainable changes. Society is complex, and social change can be messy.

For us: challenge accepted. This is why we get up in the morning!

On top of our mad skills, we all have a public orientation to our sociological practice. This means taking the tools of the “ivory tower” (academia/higher education) and using them for the public. For us as sociologists, that means:

  • We recognize the historical power dynamics between researcher and those being researched, and we actively work to make sure we are not reproducing those power dynamics.
    SPACE
  • We use the research tools and theories to work with communities, as collaborators and partners. We know the limitations of our own lived experiences and knowledge, and would rather create knowledge together.
    SPACE
  • We understand that people are already experts on their lives and communities—they don’t need us for that. We are just contributing our research and data expertise, with an eye on the big picture.

Another thing we have in common is—let’s face it—we are nerds. We love data. Where some see nonsensical numbers, we see stories. Where some see scary formulas, we see empowerment. For us, data is not the dark side—it’s the force with which we give voice to the voiceless. We use data to give organizations opportunities to heal, solve, and create in their communities.

We use the research tools and theories to work with communities, as collaborators and partners. We know the limitations of our own lived experiences and knowledge, and would rather create knowledge together.

Let us use our powers for the good of your community. Reach out if you want to collaborate, or if we can help you tell your organization’s and community’s stories.

1280px-Lightsaber_blue.svgPhoto Credit: _.Yann Cœuru ._

Data and Representation: From Drunken Rants to Expert Research

By: Megan Whalen

I have to admit that I am more obsessed with data than most people. Ask me to talk about my work and I will give you an impassioned sermon about how data is a key part of representation in the twenty-first century. Buy me a couple of cocktails and I’ll flourish the conversation with rants on structural inequality and the intentional silencing of huge swathes of our population. A few more cocktails will take you down a curse-word laden rabbit hole of righteous indignation and conspiracy theorizing. I suggest you stop at two cocktails.

Buy me a couple of cocktails and I’ll flourish the conversation with rants on structural inequality and the intentional silencing of huge swathes of our population.

Fortunately, other researchers are also concerned about the ways that some groups of people are being denied representation in important public data and you don’t even have to buy them a cocktail to hear their perspectives. A recent report by the Urban Indian Health Institute (UIHI) provides a much more reasoned and thought out example of how a lack of representation in public data collection matters – in this case, it is hurting efforts to address the high rates of missing and murdered indigenous women and girls (MMIWG) in urban areas. In 2017, UIHI began a study to assess the number of missing and murdered indigenous women and girls in urban areas across the US. While media coverage tends to focus on crimes that occur on tribal lands, the 2010 Census estimates that 71% of American actually Indians/Alaska Natives live in urban areas.

The UIHI wanted this study to help shine a light on violence against American Indian/Alaska Native women and girls living in urban areas. What they discovered was that they were unable to really examine these rates or locations of violence due to a lack of quality data. The UIHI report provides a great breakdown of why the needed data is missing as well as discussing the impacts of this lack of data.

I strongly urge you to check out the report yourself, but here’s a few highlights for the tl;dr types:

Findings on data quality and access

  • 5,712 cases of MMIWG were reported in 2016 but only 116 were logged in the Department of Justice database.
  • Although UIHI used Freedom of Information Act (FOIA) guidelines for requesting data from 72 law enforcement agencies, two-thirds of those either provided no data or provided data of such low quality it was unusable.
  • The FOIA process is expensive and very time consuming, so the grassroots organizers and nonprofit organizations that most need access to this data often cannot afford it.
  • There is a lack of standardization in collecting race information across law enforcement agencies; some agencies surveyed couldn’t even provide data broken down by race categories, others only counted people as Native American if they were a member of a federally recognized tribe and counted all others as white, and several departments submitted data including both Native American and Indian-American individuals (i.e., people from or descended from people from India).
  • Using other research methods, UIHI found 153 cases of MMIWG that were not included in the data submitted by city and state law enforcement agencies.

Suggestions for improving data quality and access

  • Better methods for community access to public data.
  • Updated record-keeping and data management guidelines across all law enforcement agencies.
  • Accounting for the violence that Native American communities experience in policies addressing MMIWG.
  • Acknowledging Indigenous Data Sovereignty; The US Indigenous Data Sovereignty Network defines this as “the right of a nation to govern collection, ownership, and application of its own data, including any data collected on its tribal citizens.”
  • Immediate and adequate funding for research to support effective policies for protecting Native American/Alaska Native women and girls in urban areas.

What data are collected and who has control over the data can have far-reaching impacts.

Just as data can be used to tell stories, it can also be used to keep stories from being told.  Whenever we find a lack of quality, culturally relevant data collection about communities of color, immigrant communities, LGBTQ communities, folks living with disabilities, or people with other marginalized identities, we need to address it. What data are collected and who has control over the data can have far-reaching impacts. My team and I are dedicated to contributing to efforts to increase equitable data collection and reporting. Buy us a round and we’ll tell you all about it.

Photo Credit: Clare Mackintosh

Let’s Start Talking about Equitable Data

By: Megan Whalen

Three and a half years ago, I quit my job at a well-respected nonprofit organization and became an independent consultant. It was kind of a fluke; I had been thinking about consulting for a while but thought I needed more experience and a stronger professional network to make it happen. But after several months of trying to survive in a super toxic work environment I decided to quit without having another job lined up. To save face, I told everyone I was leaving to become a consultant. I thought it would buy me some time to figure out my next steps, but within a few months I had three clients and more interest in my work than I ever expected. So here we are.

In the years before I started consulting, I had noticed a worrying dynamic in the nonprofit sector. Only large-budget nonprofits could afford to have a data professional like myself on staff, but all nonprofits were expected to collect and report the same amount and quality data to their funders. Not only were smaller-budget nonprofits losing out on funding because they didn’t have data to include in grant applications, but even when they did receive grant money, they were struggling to keep it because they simply could not report the kinds of information the funders required.

The issue is expecting all organizations to be able to produce quality data when only a handful of organizations have the budget to pay for quality data collection, management, and reporting.  When you consider that organizations run by and for people of color and immigrant communities are more likely to have smaller budgets, it is obvious that the way data is being used in the nonprofit sector is not just problematic, it is a mechanism of inequity.

Here’s the thing: using data to examine the impact of nonprofit work is not inherently bad; I believe that data can and should be used to build our understanding of how well our programs are serving communities. The issue is expecting all organizations to be able to produce quality data when only a handful of organizations have the budget to pay for quality data collection, management, and reporting. When you consider that organizations run by and for people of color and immigrant communities are more likely to have smaller budgets, it is obvious that the way data is being used in the nonprofit sector is not just problematic, it is a mechanism of inequity.

(For a great quick breakdown of the problems with this unequitable use of data, check out this great blog post by Vu Le of Nonprofit AF.)

ML Whalen Consulting is dedicated to confronting this inequity. Most of our clients have been organizations run by and for communities of color and immigrant communities. Race and class equity lenses are incorporated into all facets of our work. We are guided by these truths:

  • We acknowledge our own social location. As white people doing this work, we must remain aware that U.S. society is structured to always center white, middle-class values and perspectives, and top-down power dynamics. We strive to keep whiteness decentered in our work and make sure the perspectives of the communities we serve are central in all projects.
  • Our clients have already proven their impact. We do not need to see quantitative data to know that our clients are doing impactful work. Instead, our job is to use our skillset to help them communicate the impacts they are making in their communities.
  • Our clients are the experts. We have expertise in research methods and data analysis, but we avoid applying top-down solutions. We take time to understand the work being accomplished and the community being served. We collaborate with both leaders and staff members in order to address all data needs. When we build tools to capture funder requirements, we strive to capture two organization-specific metrics for every one funder required metric. In this way, we use our expertise to center community knowledge.

My team and I believe that it’s time to start talking about data in the nonprofit sector.  We plan on using this blog as a way to share tips and tricks for doing nonprofit data, discuss relevant trends in social data, and have critical conversations that encourage changes the way nonprofit data is funded and used. We hope you’ll join us.

Photo Credit: Jennifer Arlem Molina