I'm excited an in-progress preprint of our work is out! Read more here: https://arxiv.org/abs/2605.15165
Over the next few weeks, we will be spinning out various explainers, one-pagers/policy briefs, interactive dashboard in an attempt to reach different audiences. Until then, because I'm a little tired, here is a Bad Graphic Design visual abstract to celebrate the drop, exclusively for bsky/leaflet/AtProto, made in google slides as a blatant aspirational rip-off of bootboyzbiz:
It all started from reading Dave Guarino's Substack post:
Over the next few weeks, I'll be sharing more in little bits and pieces, attempting to weave together a picture of "public-interest data-driven decisions". I'm hopeful the marginalia of Leaflet is an opportunity to share some of my favorite stories from the lovely time I spent catching up on books about 70s/80s public administration. Why do I find the identity of a "bureaucratic justice warrior" so compelling? How do we find other normative frameworks to translate algorithmic insights (is) to policy imperatives (ought) beyond anti-discrimination law?
Here is the real abstract of the paper:
The U.S. social safety net delivers essential services at mass scale, but access burdens persist, as congested contact or call centers serve as a primary mode of application completion and assistance. In Holmes v. Knodell, Missouri's SNAP call centers were so congested that nearly half of all application denials were procedural, caused by applicants' inability to complete required interviews, rather than underlying ineligibility. The judge ruled these system failures led to a violation of procedural due process. We propose a performance evaluation framework based on queueing models from operations research and management to assess and improve access in such systems. Operational access failures of call centers are distinct from prior automation failures in benefits provision. Emergent arbitrariness arises from interactions between system dynamics and access demand, rather than from an explicit algorithmic rule, making diagnosis and repair inherently system-level. We develop a queueing model that incorporates phenomena that distinguish social services from standard service domains, redials and abandonment, through which backlogs generate endogenous congestion. Standard queueing guidance from Erlang-A that does not address endogenous congestion fundamentally understaffs, which could lead to persistent shortfalls in practice. Using a fluid approximation, we derive steady-state performance metrics to analytically characterize the impacts of bundled staffing and service delivery changes. We fit model parameters to call-center data disclosed in court documents. Our queueing model can support ex-ante evaluation and design of access systems, inform policy levers for improving access, and provide evidence about whether applicants are afforded a meaningful opportunity to be served at scale.
I am so grateful to my brilliant colleague Andrew Daw for being gracious enough to get dragged into this and teach me about queueing ! And our brilliant undergrad researcher Chloe Pache who worked on this last summer. And - everyone we spoke to on the legal/legal aid/benefits advocacy side (counsel on Holmes v Knodell, Benefits Tech Advocacy Hub) and my legal acquaintances that I could bug to explain that judges in administrative law generally don't want to micromanage agencies how to do things (thank you Dan and Issa).