James Özden and Sam Glover at Social Change Lab wrote a literature review on protest outcomes[1] as part of a broader investigation[2] on protest effectiveness. The report covers multiple lines of evidence and addresses many relevant questions, but does not say much about the methodological quality of the research. So that's what I'm going to do today.
I reviewed the evidence on protest outcomes, focusing only on the highest-quality research, to answer two questions:
1. Do protests work?
2. Are Social Change Lab's conclusions consistent with the highest-quality evidence?
Here's what I found:
Do protests work? Highly likely (credence: 90%) in certain contexts, although it's unclear how well the results generalize. [More]
Are Social Change Lab's conclusions consistent with the highest-quality evidence? Yes—the report's core claims are well-supported, although it overstates the strength of some of the evidence. [More]
Cross-posted from my website.
Introduction
This article serves two purposes: First, it analyzes the evidence on protest outcomes. Second, it critically reviews the Social Change Lab literature review.
Social Change Lab is not the only group that has reviewed protest effectiveness. I was able to find four literature reviews:
1. Animal Charity Evaluators (2018), Protest Intervention Report.
2. Orazani et al. (2021), Social movement strategy (nonviolent vs. violent) and the garnering of third-party support: A meta-analysis.
3. Social Change Lab – Ozden & Glover (2022), Literature Review: Protest Outcomes.
4. Shuman et al. (2024), When Are Social Protests Effective?
The Animal Charity Evaluators review did not include many studies, and did not cite any natural experiments (only one had been published as of 2018).
Orazani et al. (2021)[3] is a nice meta-analysis—it finds that when you show people news articles about nonviolent protests, they are more likely to express support for the protesters' cause. But what people say in a lab setting mig
I think ~1.1% (with fairly wide uncertainty) is a fairly realistic guess for a global IFR (including all age ranges). I basically don't buy that the balance of factors would necessarily favor poorer and younger countries over richer/healthier/older ones, though it certainly is possible.
Here's a preliminary document listing why I believe this. Usual caveats of being a non-professional apply, and also the tone is a bit sharper than I'd use on the EA Forum (basically the intended audience was other amateur forecasters so there are certain stylistic differences, especially around caveats).
~0.1%, or even slightly lower, seems believable for <60s in some rich countries but I don't think you want to extrapolate age-structure arguments too strongly to novel situations (in essence I think age is a biased estimator whereas something like crude death rate may not be), and if you want to look at specific countries you'd want to look at a bunch of known comorbidities*; eg per capita, Nigerians die of heart disease at ~1/10 the rate of Indians.
One thing that I didn't mention in my document above is that even if .1%-.2% is a realistic IFR for young people in developing countries, and developing countries are skewed young, the full IFR in developing countries will likely still be much higher.
For example, Guayas province in Ecuador has had ~11,561 excess deaths from the beginning of March to mid-April (base rate is ~3000 in that time period). My understanding is that close to all of it is directly due to covid-19 (I talked to people from Ecuador and if there was mass starvations or a different epidemic that accounted for even 2x all-cause mortality I'd have heard by now). The population of Guayas is ~3 million, so this is already a lower bound of ~0.39% of the entire population(!), and I really don't buy that anywhere near 100% of Guayas were infected as of mid-April (or more accurately late March to account for lag between infection and death).
Ecuador has a median age of 27.9, a life expectancy of 76.6, and a GDP per capita of $6400, so definitely not unusually old or unhealthy by middle-income country standards.