Global Data and Insights/Movement Data/Equity Landscape/Introduction

Equity Landscape

• Introduction
• Metrics Schema
• Glossary
• FAQ
• Pilot

By 2030, Wikimedia will become the essential infrastructure of the ecosystem of free knowledge, and anyone who shares our vision will be able to join us.

Background

The Wikimedia movement ecosystem is a global, volunteer-driven network of individuals, chapters, affiliates and partners who work to advance the agenda of Open Knowledge. At the core of this agenda is the position that universal access to reliable and verifiable knowledge is a basic human right. And, that a consensus-based dialogue on what constitutes verifiable knowledge is the best method we currently have for collectively generating the knowledge all of us can depend upon. A central modality of the Movement is that dialogue is valued, fluid and ongoing across languages, cultures, geographies and interest groups. We seek consensus but nothing is ever settled.

Equity Data Landscape project overview slides

Trying to understand how well we are reaching our goal brings many questions about the bounds of our movement ecosystem:

• Who is part of our movement?
• How are people getting involved and where?
• Where are our fastest growing communities?
• Where are Wikimedia projects and communities keeping up or falling behind global infrastructure gains?
• Where are we showing promise in diversity and inclusion; where are we most challenged, and how?
• What voices are missing from our projects and communities?
• What supports movement collaboration; how and where can we improve?
• Are our growth targets equitable?
• Are we equitably supporting emerging communities?

Many of our questions about our communities ask who and where our community members are; historically we have only been able to examine data by Wikimedia project or special data collection event. To understand the context of movement organizing, we must understand the “where” geographically as well. Of course, thematic and language areas intersect these geographic spaces where our communities exist and grow - for this reason we are working to map languages and thematic groups to geographic spaces this year also as we work to develop our initial dashboard.

Our MTP and movement strategy bring a need to define what equity, diversity, and inclusion mean in data.

Diversity, inclusion, and equity are now central to the Foundation’s MTP and movement strategy aims; in order for us to understand the political, social, and economic barriers contributors may face in their movement engagement, we need to measure and track changes.

However, measuring inequality and diversity is not straightforward; it requires decisions to be made on the metrics and distributional characteristics of interest. These decisions influence the conclusions and must be closely linked to specific use cases for movement decision-making.

Following the lead of the National Equity Atlas (2019) and Chicago Beyond (2019), we have begun to map our existing wealth of landscape data to develop an equity landscape data reference and index to track the Wikimedia movement’s progress in breaking down the social, political, and technical barriers to full participation in free knowledge, based on what is already being captured.

We have a lot of data, the world has a lot of data, let’s compile what we have to begin answering basic questions.

To begin to do this, we have assembled our internal engagement and social research metrics alongside aligned global data indicators to enable easy examination of the Foundation's progress within national or regional contexts using available data.

We intend to view our data through the lens of social inequities already mapped in available global data in order to identify key progress levers to support healthy movement development without adding additional burden to our stakeholders who are always being asked to input.

As movement leaders, it is critical that we all take the time to pause to appreciate the evolving landscape of data and engage in a data-informed dialogue around equity across our movement organizing spaces to better calibrate both our tools and our practices. Travelling this road together will improve the validity of evaluative tools as well as the feedback stakeholders are provided, it also can make data, its analysis, and reporting, more usefully relevant to a broader audience of stakeholders.

The Big Idea: Provide easily accessible data on inequities within the world and our movement.

With increased data awareness of inequities, movement stakeholders can reinforce pathways for diversity, inclusion, and equity and target interventions that eliminate barriers in the Wikimedia Movement. Most importantly, we envision that identifying disparities in outcomes across movement spaces, tracking our shared progress at increasing diversity, inclusion, and equity, and providing data and analyses by which we can hold ourselves accountable to our movement strategy aims will enable us, as an organization and a movement, to prioritize efforts that achieve the impact we wish to see in 2030.