Barbara Binder

@barbarabinder.bsky.social

Sociologist | Income inequality, poverty, social inequality | GESIS, working on digital behavioral data in surveys

Large-scale online deanonymization with LLMs shows how easily pseudonymous users can now be re-identified from unstructured text alone. When discussing our EJMR paper at NBER SI 2023 Catherine Tucker argued that rising compute would soon erode online anonymity. The future may already be here.

BildBildBild

Who opts into a data donation study asking for Google Search histories – and more importantly, who actually donates their data? Sina Chen and I found that Green Party and FDP voters were more likely to follow through, hinting at political skew in donated data 👇

The figure shows the predicted probabilities by party vote, derived from the partially observed bivariate probit model, separately for willingness and completion, and the joint probability. Voters of the CDU/CSU, the AfD, the SPD, the LINKE, and BSW exhibit predicted probabilities of willingness to participate close to the sample average of 50%. Green Party voters show a higher predicted probability of willingness to participate, while the elevated probabilities among FDP voters are not statistically different from those of CDU/CSU voters. In contrast, voters of other parties and non-voters, including those who did not disclose their vote choice, display lower predicted probabilities of willingness. When it comes to donation completion, both Green Party and FDP voters stand out with higher predicted probabilities. As a result, the joint predicted probabilities indicate that voters of the Greens and FDP are the most likely to both opt-in and follow through with the data donation, even when controlling for age, gender, and education.

The field of gender and sexual minority (LGBTQ) health is being erased. Hundreds of ongoing NIH grants being immediately terminated. Deb Umberson and my decade long longitudinal study on marriage and health joined the termination list last night.

🚨 Policy works! 🚨 Low-wage workers saw dramatically fast wage growth from 2019-2023—even after accounting for inflation—largely because of federal and state policy measures like COVID relief and minimum wage increases. This is in stark contrast to prior decades. 🧵 1/4

A graph with the headline "The lowest-wage workers had the strongest wage growth during the pandemic" and a sub-headline that reads "Real wage growth across the wage distribution, 2019-2023"