Public data as a decision system.

Maternal mortality rates for 2023 show the Black rate at 50.3 per 100k births, holding near the 50 mark seen in 2022 (49.5), while the White rate fell to 14.5 from 19.0. These are small annual counts (669 deaths in 2023 versus 817 in 2022 nationally), so single-year movement in any group's rate is noisy and may not be statistically significant. The data detected a wider Black-White ratio in 2023 (roughly 3.5-to-1) than in 2022, consistent with the White average moving downward while the Black rate stayed anchored near 50 — the durable finding is this persistent gap, not the year-to-year tick in either bar. No causal claim is warranted: the pattern is observational, and the data is consistent with, rather than proof of, any driver of the White-rate decline. Notably, the 12-month postpartum Medicaid extension postdates the 2023 outcome window entirely, so it cannot be credited with or blamed for the 2023 figures; it stands as a forward-looking lever aimed at closing the gap, not an explanation of what already happened.

Grade 8 math is the panel's clearest warning. Black students sit at 251.0 in 2024 against 252.0 in 2022, and Hispanic students sit at 257.0 against 261.0 in 2022; both moves are within sampling error and neither should be read as a real one-year gain or loss. NAEP scores carry sampling error by design, so single-year shifts of a point or two are not statistically significant on their own. What is real: White students hold at 284.0 across both years while Hispanic students fall from 261.0 to 257.0, meaning the White-Hispanic gap widened rather than closed. The recovery signal in this dataset is concentrated at grade 4, and it coincides with states that mandated high-dosage tutoring: Louisiana was the only state to top its pre-pandemic grade-4 reading mark, and Alabama's grade-4 math score moved from 230 to 236 in that same window. None of this proves the tutoring mandate caused those grade-4 numbers; the design is observational, and the data is consistent with recovery tracking where the lever was actually deployed at dosage, not with any lever working everywhere. Grade 8 shows no such pattern — it shows a stalled gap, and a widening one for Hispanic students.

Overdose mortality rates across all reported racial and ethnic groups declined from 2023 to 2024, with the national total falling to 79384 deaths, but the drop was not uniform. American Indian/Alaska Native communities remained the highest-rate group in both years (65.0 in 2023, 51.6 in 2024), followed by Black (48.9, then 33.8) and White populations (33.1, then 24.7), while Native Hawaiian/Pacific Islander, Hispanic, and Asian groups tracked at consistently lower levels. This persistent gap means the overall decline masks a continuing, disproportionate burden on American Indian/Alaska Native and Black populations rather than an equal easing of risk. Note that American Indian/Alaska Native overdose death counts are widely understood to be undercounted due to racial misclassification on death certificates, so the true disparity is likely even larger than these figures show. The timing of naloxone expansion coincided with this downturn, but it occurred alongside major supply-side shifts (fentanyl market saturation and precursor-chemical changes) that can dwarf harm-reduction levers in top-line mortality; the data here detected the turn but does not establish that the program caused it. Any interpretation should treat the panel as evaluative surveillance, not causal proof, and should flag the widening disparity for equity review.

The bars pair 2010, when the ACA created the Hospital Readmissions Reduction Program (Social Security Act section 1886(q)), against 2016: raw, unadjusted 30-day readmissions across all Medicare fee-for-service discharges fell from 16.7 percent to 15.6 percent. Read the concentration, not the top line - readmissions for the penalized conditions dropped 13.2 percent against 4.5 percent for conditions the program does not cover (a 2.4 versus 0.7 percentage-point gap), the sign that the lever, not a background trend, moved the number. MedPAC tested the obvious dodge, hospitals shifting patients into observation stays and ED visits, and found near-identical growth for covered and non-covered conditions, so the drop was not mostly relabeling. Two honest limits: on a risk-adjusted basis heart failure readmissions fall further, 23.9 to 20.5 percent, but part of that reflects hospitals coding more diagnoses after the secondary-diagnosis fields expanded from 9 to 24 in 2011 - a measure that improves partly because it got easier to satisfy is a Goodhart risk, so the raw rates are the conservative read - and the raw decline stalled after 2014. On mortality MedPAC found no adverse effect: risk-adjusted mortality fell across every condition studied.

Pulled from the College Scorecard field-of-study API - Computer Science bachelor's, median earnings four years after completion, Title IV federal-aid recipients only. These six schools are a hand-picked illustration, not a representative sample, so read the spread as a contrast, not the distribution. For the same credential in the same field, Carnegie Mellon reports 268,121 and MIT 225,141 at the top against CUNY York 73,044 and Fayetteville State 36,164 at the bottom - a five- to sevenfold range that widens further at longer horizons. Three caveats travel with it. First, at the regionals the completer counts are thin enough that horizons run non-monotonic (Fayetteville reads 50,940 at one year but 36,164 at four), so the medians are noisy. Second, the same federal source answers differently by door - the field-of-study API returns no CS figure for Brown, whose single-year cohort is below the privacy threshold, while the public web tool shows about 214,000 by pooling two award years - so the grain of the query decides whether a number exists at all. Third, the cross-school gap blends the school's effect with selection (who it admitted), so it is not a clean read on what the degree itself causes.

Virginia's SCHEV report links K-12, higher-ed, and employment records to publish post-completion wages: median annual wage five years out for 2017-18 graduates, measured on 2023 Unemployment-Insurance records (nominal). At the credential median the premium is smaller than the folk model assumes: a four-year bachelor's earns 65,249, an applied-science (AAS) associate 58,393, and a transfer associate 49,444, so 'higher credential = higher pay' holds on average but only barely, and the distributions overlap heavily, so at these medians a strong applied-science associate can out-earn a weaker bachelor's, and credential tier alone is a poor predictor of individual pay. Two caveats travel with every wage here: it is UI-covered, in-state employment only (out-of-state, federal, military, self-employed, and gig work are invisible), and not every graduate has a reported wage, and match rates differ by credential, so the medians describe differently-selected subpopulations. SCHEV itself warns against ranking programs on these wages without adjusting for family wealth, residency, and demographics.