- Jan 2023
Seven Principles of Data Feminism
- Examine power
- Challenge power
- Rethink binaries and hierarchies
- Elevate emotion an embodiment
- Embrace pluralism
- Consider context
- Make labor visible
There are some interesting analogies to be drawn between the abolitionist movement in the 1800s and modern day movements like abolition of police and racial justice, etc.
Topic modeling - What would topic modeling look like for corpuses of commonplace books? Over time?
wrt article: Soni, Sandeep, Lauren F. Klein, and Jacob Eisenstein. “Abolitionist Networks: Modeling Language Change in Nineteenth-Century Activist Newspapers.” Journal of Cultural Analytics 6, no. 1 (January 18, 2021). https://doi.org/10.22148/001c.18841. - Brings to mind the difference in power and invisible labor between literate societies and oral societies. It's easier to erase oral cultures with the overwhelm available to literate cultures because the former are harder to see.
How to find unbiased datasets to study these?
aspirational abolitionism driven by African Americans in the 1800s over and above (basic) abolitionism
- orality vs. literacy
- intersectional feminism
- data science
- Data Feminism
- Catherine D'Ignazio
- Lauren F. Klein
- invisible labor
- topic modeling
- emotional labor
- aspirational abolitionism
- power frameworks
- defunding police
- dodging the memory hole
- Jul 2022
- May 2019
Calling them “emotional labor,” as Julie Beck points out, has the curiously sexist implication that all work performed by women is somehow about feelings.
"them" referring to domestic work - chores.
The original meaning was the labor involved in regulating, evoking and suppressing certain feelings while you’re at work — as Hochschild puts it, it’s “trying to feel the right feeling for the job.” It described work for which you are paid (although not always adequately compensated) and didn’t only apply to labor performed by women.