Book + Article + Podcast Club
We've received multiple requests for suggestions for books and other materials on equity, ethics, data, and evaluation. As a person who adores podcasts and maintains a huge pile of (sometimes admittedly unread) books on my table, I'm happy to share my list. And I would love it if you could share your lists with us as well. We've started a page here that we're calling the Books (Plus) Club.
Two of my favourite things right now are the book Decolonizing Methodologies by Linda Tuhiwai Smith (here's Linda doing a great talk). And the Equitable Evaluation Framing Paper from the Center for Evaluation Innovation, Institute for Foundation and Donor Learning, Dorothy A Johnson Center for Philanthropy and Luminare Group.
Please feel free to send me your book, paper, and podcast suggestions and we'll share them as we go along. Thanks!
Note that we are intentionally not linking to Amazon in this book list. Instead, we're linking to either independent book stores or the authors directly.
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Updated "Talk to your boss" materials
Thank you so much for all your wonderful comments, suggestions, and messages about the “Talk to your boss” sheets. As a result of these conversations, we’ve made some immediate changes to the sheets and we’ve got some new tools in production. You can download the newly updated sheets here (Feminist Data) and here (RCTs).
We particularly want to thank Kimberly Bowman, Director of Strategy at Girl Guides Canada, who contributed a lot of wonderful feedback, including ideas about how to think about bias in data products. Part of her input included these thoughts: “In most of the contexts where I’ve operated, we would consider bias to be something that can’t totally be eliminated – but one that we should seek to understand, honestly speak to and address the negative effects of (racism, sexism, etc.) where possible. As large organizations who are often implicated in step 1 (as guardians of the funding, and also of what is judged to be ‘good quality research’), a simple conversation among the research team on what biases we’re individually and collectively bringing has been a sometimes-uncomfortable but ultimately helpful step.”
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We'd love to hear your stories of data equity problems, learnings, and successes.
If you have a story or idea you want to share, send me a note by replying to this email.
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