Wikipedia:Equity lists

= Equity lists =

How do these lists work?
Wikipedia is missing many articles about people. This tool uses Wikidata, a Wikimedia project, to query Wikipedia articles in different languages to show gaps where others can write articles in their own language. Prioritizing articles that already exist in other languages means that they (likely) pass notability and have sources associated with them. This should make Wikipedia articles easier to write. If you are familiar with Women in Red, this tool is inspired by their work.
 * What is this tool?

This tool focuses on several demographic characteristics to improve representation on Wikipedia. Capturing data about demographics is inherently problematic and differs from country to country and from community to community. This tool does not seek to minimize this, but rather use what we have to improve what we can.
 * Scope

Wikidata has over 10 million humans items (query). Only a fraction of these have the accompanying statements to help understand equity, diversity, and representation on Wikidata. For every variable, we will provide a query of how many times those statements appear on items to understand how underused each of these properties are. As comprehensive as these lists are, the data will always be incomplete. If you are looking for a particular person and you don't seem them on the list, it may be the case that they don't have an article in another language version of Wikipedia. Remember you can always create an new article.
 * Background on the data

Take a look at these different categories. Each page will contain lists based off of different characteristics - ethnicity, sexual orientation, and medical conditions among others. These pages generate lists from all language versions of Wikipedia that are not English to reveal missing articles on English Wikipedia. Select a person, check out the references in the various language versions, look for new sources, and write an article in English. When you publish the article, the person will be automatically removed from the list. This tool uses various Wikipedia and Wikidata tools. PetScan is a tool that generates lists based on a set of criteria - Wikipedia categories, Wikidata queries, manually curated lists to name a few. This tool also uses Listeria, a bot that generates tables based on a SPARQL query. These tables update regularly and pull data from both Wikipedia and Wikidata. You can sort these lists by variables and values that most interest you. These lists are incomplete because they only pull in a few hundred results each. This helps us avoid a timeout, but can obscure results.
 * How does it work?

If you are using the Outreach Dashboard, you can integrate these lists into your Dashboard. Each list (query) has a corresponding PetScan ID (PSID). PetScan is a tool that generates lists of Wikipedia articles based on a set of criteria. These lists contain unique identifiers. These identifiers represent the lists and allow us to call the same kinds of lists over and over. You can plug these PSIDs into the Dashboard to scope the Dashboard to a specific set of articles. Scoping should draw more attention to a given set of articles. If you keep scrolling down, there is a detailed set of instructions to follow that will describe how to do this.
 * Dashboard integration

Dashboard integration
The Dashboard is a tool that allows you to track edits, articles, and participants in a course. It is customizable and useful to see the impact of a group over time on Wikipedia.
 * Follow this link to some trainings slides that will walk you through how to connect these lists to your Dashboard
 * Instructions - You can also click this link for a detailed set of steps to scope your Dashboard
 * Use these lists to identify gaps on English Wikipedia. Click on a red link and write an article about that person. For anyone using the Outreach Dashboard use a PetScan ID (PSID) to scope your Dashboard to that set of people
 * Customize these queries to identify gaps on any language version of Wikipedia
 * Identify individuals lacking specific statements on Wikidata (like gender, sexual orientation, ethnicity, nationality, etc.)