America works for some of us, but it needs to work for all of us.
We need to rebuild our care, housing supply, education, economy, safety, democracy and community.
Let’s rebuild our systems from the ground up to deliver freedom, dignity and opportunity for everyone 🧵
The rich libs need to give a billion dollars to ProPublica
My daughter’s speech therapist went out of business because Medicaid reimbursement rates were too low. We do not have Medicaid. I’m going to keep posting this until people understand that when Medicaid gets cut *everyone* loses services.
Bad Bunny showcased his Puerto Rican heritage in his custom Prada look at the #MetGala.
Jeff Bezos has enough money to send Katy Perry and Gayle King on a joyride to space for 11 minutes.
He can afford to pay his fair share in taxes.
This Administration is trying to erase a human being.
Don't allow it.
We are all connected.
Sen. Booker’s speech was a substantive and moral account of this moment. He did not read the phone book. He did not babble.
For 24 hours @booker.senate.gov laid out a detailed, damning, and critical narrative of truth, history, politics, morality, humanity.
What will you do?
I may be tired and a little hoarse, but as I said again and again on the Senate floor, this is a moment where we cannot afford to be silent, when we must speak up.
Figured I’d hop on here today for the 15th anniversary of the Affordable Care Act.
With everything going on right now, it’s easy to feel like regular folks can’t make a difference – but the ACA is a reminder that change is possible when we fight for progress.
This essay provides an overview of statistical methods in public policy, focused primarily on the United States. I trace the historical development of quantitative approaches in policy research, from early ad hoc applications through the 19th and early 20th centuries, to the full institutionalization of statistical analysis in federal, state, local, and nonprofit agencies by the late 20th century. I then outline three core methodological approaches to policy-centered statistical research across social science disciplines: description, explanation, and prediction, framing each in terms of the focus of the analysis. In descriptive work, researchers explore what exists and examine any variable of interest to understand their different distributions and relationships. In explanatory work, researchers ask why does it exist and how can it be influenced. The focus of the analysis is on explanatory variables (X) to either (1) accurately estimate their relationship with an outcome variable (Y), or (2) causally attribute the effect of specific explanatory variables on outcomes. In predictive work, researchers as what will happen next and focus on the outcome variable (Y) and on generating accurate forecasts, classifications, and predictions from new data. For each approach, I examine key techniques, their applications in policy contexts, and important methodological considerations. I then consider critical perspectives on quantitative policy analysis framed around issues related to a three-part “data imperative” where governments are driven to count, gather, and learn from data. Each of these imperatives entail substantial issues related to privacy, accountability, democratic participation, and epistemic inequalities—issues at odds with public sector values of transparency and openness. I conclude by identifying some emerging trends in public sector-focused data science, inclusive ethical guidelines, open research practices, and future directions for the field.
Description Explanation Prediction General question What exists? Why does it exist? How can it be influenced? What will happen next? Focus of analysis Focus is on any variable—understanding different variables and their distributions and relationships Focus is on X —understanding the relationship between X and Y, often with an emphasis on causality Focus is on Y —forecasting or estimating the value of Y based on X, often without concern for causal mechanisms Names for variable of interest — Explanatory variable Independent variable Predictor variable Covariate Outcome variable Dependent variable Response variable Goal of analysis Summarize and explore data to identify patterns, trends, and relationships Estimation: Test hypotheses or theories and make inferences about the relationship between one or more X variables and Y Causal attribution: A special form of estimating—make inferences about the causal relationship between a single X of interest and Y through credible causal assumptions and identification strategies Generate accurate predictions; maximize the amount of explainable variation in Y while minimizing prediction error Evaluation criteria — Confidence/credible intervals, coefficient significance, effect sizes, and theoretical consistency Metrics like root mean square error (RMSE) and R^2; out-of-sample performance Typical approaches Univariate summary statistics like the mean, median, variance, and standard deviation; multivariate summary statistics like correlations and cross-tabulations t-tests, proportion tests, multivariate regression models; for causal attribution, careful identification through experiments, quasi-experiments, and other methods with observational data Multivariate regression models; more complex black-box approaches like machine learning and ensemble models
Table of contents Introduction Brief history of statistics in public policy Core methodological approaches Description Explanation Prediction The pitfalls of counting, gathering, and learning from public data Future directions References
New preprint! A general overview of stats in public policy research with this (oversimplified but still helpful) separation of methods into description, explanation, and prediction #policysky
HTML/PDF: stats.andrewheiss.com/snoopy-spring/
SocArXiv: doi.org/10.31235/osf...
Closing the DOE isn't about "efficiency." It's about profit, privatization, propaganda, punishment, privilege, and power.
open.substack.com/pub/jesscala...
“When victims can articulate their oppression, they become a threat.” - James Baldwin
I’m so grateful to have parents who made sure I got vaccinated.
Indeed
Men of America - we need tone doing MUCH better
There is a real, genuine 1st Amendment crisis in the United States right now.
The government is openly retaliating against anyone with a viewpoint it doesn't like: Pro-Palestinian protesters, law schools teaching Black History, pro-immigration public service loan forgiveness seekers.
This is why capitalism and patriarchy go hand-in-hand.
Oh myyyy!!! 😍❤️
I just got my new Neocaradina shrimp and my Blue girl is also super pregnant! I’m so excited! 🦐💕
Tweet from Scott Jennings, saying "um, yes, that's really a problem," with a quoted image saying "The problem with left-leaning media is they're intrinsically more strict with their propaganda to only using verifiable sources so it's really hard to poke holes in their ideology and arguments in comparison to a lot of low quality right-wing content. That makes attacking their points with fact checkers not very effective unless the fact checkers use misinformation tactics as well. In essence, people on the right have to work harder and more creatively to push their agendas as statistics and studies frustratingly aren't usually on our side."
This is why they're attacking science and education: if you can only win with disinformation, data become a threat.
A new era of government censorship has begun.
It started with the silencing of scientific speech, when the admin blocked release of research on bird flu. But MAGA has also cracked down on other wrongthink—on race, geography (!), and of course Trump himself
www.washingtonpost.com/opinions/202...
"All these new apartment buildings... Yet so many people forced to sleep outside.."
Seen in Bellingham Washington
