PG&E power lines are photographed in Fremont, on Friday, Oct. 9, 2020. Photo by Anda Chu, Bay Area News Group
The state’s primary utility regulator is under new management. Gov. Gavin Newsom promoted Commissioner John Reynolds to president of the California Public Utilities Commission this week as part of a “new phase” of Newsom’s effort to address sky-high power bills. bit.ly/4aqs3mN
📸 Anda Chu
CalBallot homepage showing a dark header, stats ribbon (11,485 total measures, 67.5% pass rate, 1998–2026), filter buttons for level, region, topic, year, and status, and a 2x2 grid of measure cards including Prop 36, Prop 3, Prop 33, and Prop 32.
I built CalBallot — a free tool for exploring 28 years of California ballot measures across all 58 counties. Over 11,400 measures from 1998 to 2026, filterable by region, topic, year, and outcome. (1/7)
Free, no login required. It's still early and I'm eager for feedback — visit the site, poke around, and let me know what you find or what's broken. (7/7)
cal-vgp.igorgeyn.com
Chat interface titled "Ask CalBallot." A user asks "What were the 5 closest ballot measures in the last 10 years?" and the bot responds with a SQL query and a results table showing five measures decided by margins under 1%, topped by a 2016 Fresno sales tax that passed by 0.01%.
You can also ask questions in plain English — it translates them to SQL and runs queries in-browser via DuckDB-WASM. I've spent a ton of time playing with this myself. (6/7)
Campaign finance view for Prop 36 showing side-by-side Support ($12.4M, led by Walmart and CA Grocers Assn) and Oppose ($3.1M, led by CA Teachers Assn and ACLU) panels with top donors, a fundraising timeline bar chart, and a donor composition bar with a grassroots score of 8%.
For statewide propositions, there's campaign finance data from CalAccess — top donors on each side, fundraising timelines, and a grassroots score showing how much comes from small vs. mega donors. (5/7)
Detail page for Prop 36: Criminal Penalties and Treatment (2024, Passed 68.4%). Shows an AI-generated plain-language summary, a vote bar, and a grid of four related measures found by text similarity.
Every measure gets plain-language summaries — no legal jargon — plus vote totals and a list of semantically related measures. The goal is to make ballot measures actually understandable. (4/7)
Heatmap table with 11 county rows (Statewide, Los Angeles, San Francisco, Alameda, San Diego, Santa Clara, Contra Costa, Orange, Sacramento, San Mateo, Fresno) and 4 topic columns (Tax, Education, Housing, Safety). Cells are color-coded from green (high pass rate) to red (low), with pass percentages and measure counts in each cell.
My favorite feature: a heatmap that breaks down pass rates by county and topic. You can immediately see that SF passes 81% of tax measures while Orange County passes 58% — patterns like that jump right out. (3/7)
Year filter panel showing filter buttons for level, region, topic, year, and status, with the year filter expanded to display clickable chips for every election year from 2026 down to 1998, each showing a measure count.
Ballot measure data in California is scattered across county sites, state archives, and PDFs. So I pulled it all together — filterable by year, region, topic, and outcome. If you spot missing data, let me know. (2/7)
CalBallot homepage showing a dark header, stats ribbon (11,485 total measures, 67.5% pass rate, 1998–2026), filter buttons for level, region, topic, year, and status, and a 2x2 grid of measure cards including Prop 36, Prop 3, Prop 33, and Prop 32.
I built CalBallot — a free tool for exploring 28 years of California ballot measures across all 58 counties. Over 11,400 measures from 1998 to 2026, filterable by region, topic, year, and outcome. (1/7)
PoliSci Friends- I'm updating some MRP-based public opinion estimates. Anyone willing to share micro data from recent nationally representative surveys you've run (e.g., CES modules) that ask one or more batteries of binary questions about the American public's issue/policy preferences?
Appendix A7 most striking graph for me:
In recent years, white turnout has spiked. But turnout among Black and other non-white Americans has stagnated. @devincaughey.bsky.social, Bernard Fraga, @rpgriffin.bsky.social & I have a summary in @goodauth.bsky.social of our work on turnout in U.S. elections. goodauthority.org/news/2024-br...
Genuinely useful academic contribution! UCLA has a "cluster" sequence teaching the music/history/politics of the 1960s, and I've used Billboard charts in a bunch of teaching material.
Now there's music to go with it. Good on you, Wouter!
It's possible that the almost-certainly-short-term deployment of federal agents/NG is going to abate crime in D.C. (I'm skeptical), but it seems--at a minimum--a good idea to also consider the many research-backed ideas presented by @jenniferdoleac.bsky.social and others.
youtu.be/BbLDpIXnNkk?...
drop your best book recs 📚💙
Cross-posting to offset some bad karma (posting to X) with good karma.
I wrote up a quick tweet thread covering a super-interesting AEJ: EP paper on natural disasters and special interest pandering, which is forthcoming in the same edition as my paper with Daniel Firoozi.
x.com/GeynIgor/sta...
38 states have legalized sports betting, but little is known about the financial, social, and behavioral impacts.
@arnoldventures.bsky.social is committed to building the evidence base with our newest RFP.
LOIs due 9/15 and details here: www.arnoldventures.org/causal-resea...
I noticed only because I update the @calmatters.org Trump lawsuit tracker, but the URL for the FEMA memo from April that cancelled $4.5B in disaster-prevention grants is now dead. The multi-state suit linked to this: www.fema.gov/press-releas.... It's a 404 error. But it lives on the Wayback Machine
What are some good things to read to learn more about production approaches to causal inference--for example in tech--for someone who's mostly been exposed to one-off analyses a la academic papers?
one last post on international students -- public opinion is not in the administration's favor on this, and universities should not let them forget it
Medicaid is the primary payer for maternity care in the U.S. It finances about 4 in 10 (41%) births nationally — nearly half in rural communities (47%).
Our new brief covers more facts you may find surprising.
Our community must take this issue very seriously!
ideally, we'd post these publicly:
raw_no_pii.csv
cleaning.R
clean.rds
analysis.R
but destroy or archive privately:
raw.csv
remove_pii.R
(was glad to see in this thread political science apparently does better than other fields but still)
Forthcoming in AEJ: Economic Policy: "Do Tuition Subsidies Raise Political Participation?" by Daniel Firoozi and Igor Geyn. www.aeaweb.org/articles?id=...
I am hiring a PhD student on the meaningful interpretation of effect sizes as part of my VICI funded project. This is a 4 year paid position in a welcoming and collaborative environment. Find out more or apply at www.tue.nl/werken-bij-t...
#edresearch #education research friends—the CRDC website has a (seemingly) random smattering data on its website. What I've been able to find is excellent, but many years missing.
Does anyone know where I might the missing years? Many thanks!
civilrightsdata.ed.gov/data
position_jitter()
position_jitter_ellipse()
position_sunflower()
position_circlepack()
New visualization tool alert!
The vayr package version 1.0.0 is now on CRAN.
It contains position adjustments for ggplot2 that help with overplotting in pleasing ways. My favorite is position_sunflower().
- install.packages("vayr")
- alexandercoppock.com/vayr
#rstats #ggplot2 #dataviz
we have now posted the 2024 Cooperative Election Study common content dataset to the @harvarddataverse.bsky.social! data from 60,000 American adults interviewed before & after the election. thanks to @today.yougov.com & Caroline Soler for getting this data produced & posted doi.org/10.7910/DVN/...
Regrettably, not a single question about union status, especially given the large contrast in satisfaction between older and younger workers.
Perhaps more precisely: What quality does the American worker perceive from these reshored jobs?
Headline overstates the results a bit (IMO), but still makes you think: of what quality is the typical regained job, if 'Liberation' is somehow able to reshore in some industries?
www.pewresearch.org/short-reads/...
