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arxiv: 2601.14094 · v3 · submitted 2026-01-20 · 💰 econ.GN · q-fin.EC

Hot Days, Unsafe Schools? The Impact of Heat on School Shootings

Pith reviewed 2026-05-16 12:37 UTC · model grok-4.3

classification 💰 econ.GN q-fin.EC
keywords school shootingstemperatureheatclimate changeviolenceeducationsafetyinterpersonal conflict
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The pith

Days above 90°F raise school shooting incidence by about 90 percent compared to days below 70°F.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper uses records of K-12 school shootings from 1981 to 2022 to measure how daily maximum temperature affects incident counts. It reports a large increase on the hottest days, driven mainly by interpersonal conflicts that occur before school, at lunch, or after dismissal. The authors then apply the historical temperature response to climate projections to estimate additional shootings and their social costs by mid-century.

Core claim

The paper claims that maximum daily temperatures above 90°F raise the incidence of school shootings by approximately 90 percent relative to days below 70°F, with the response concentrated in interpersonal incidents and in non-class periods such as before school, dismissal, after school, and lunch, while class-time shootings show no detectable response; effects appear for both indoor and outdoor locations and are larger for incidents involving fatalities or injuries.

What carries the argument

Daily maximum temperature thresholds, specifically the contrast between days above 90°F and below 70°F, used to identify shifts in shooting rates across time periods and incident types.

If this is right

  • Shootings during non-class periods more than triple on days above 90°F.
  • The temperature response holds for both indoor and outdoor shootings.
  • Incidents with fatalities or injuries rise more than those with only minor or no injuries.
  • Interpersonal school shootings increase by 6 percent by 2051-2060 under moderate emissions and 8 percent under high emissions.
  • Mid-century social costs reach $599 million under moderate emissions and $799 million under high emissions, driven by lost lifetime earnings.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Schools in hotter regions may face rising safety pressures that extend beyond traditional heat-stress concerns.
  • Mitigation such as improved cooling or adjusted schedules could be tested as ways to offset the temperature-linked rise in incidents.
  • The pattern may point to broader heat effects on youth aggression or supervision gaps that apply to other forms of school violence.

Load-bearing premise

Daily temperature fluctuations are not systematically linked to other factors such as school calendars, holidays, or unmeasured socioeconomic conditions that independently change shooting rates.

What would settle it

Finding no temperature effect on school shootings after accounting for exact school calendars, holidays, and local socioeconomic trends would falsify the central temperature-response estimate.

read the original abstract

Using data on shootings in U.S.\ K--12 schools from 1981 to 2022, we estimate the effect of temperature on school shootings and assess climate-change impacts. We find that days with maximum temperatures above 90$^{\circ}$F increase school shooting incidence by approximately 90\% relative to days with maximum temperatures below 70$^{\circ}$F. The response is concentrated in interpersonal incidents and in non-class periods, such as before school, dismissal, after school, and lunch: shootings during these periods more than triple on days with maximum temperatures above 90$^{\circ}$F, while shootings during class time show no detectable temperature response. The estimated effects are positive for both indoor and outdoor shootings and are larger for shootings involving fatalities or injuries than for shootings involving only minor or no injuries. Applying the estimated dose-response to future warming, we estimate that interpersonal school shootings increase by 6\% by mid-century (2051--2060) under moderate emissions (SSP2--4.5) and 8\% under high emissions (SSP5--8.5), or about 12 and 16 additional incidents per decade. The present discounted value of mid-century social costs is \$599 million under SSP2--4.5 and \$799 million under SSP5--8.5, driven primarily by lost lifetime earnings among exposed students. The results suggest that climate damages in schools may include rare but high-cost safety events, not only heat stress and learning losses.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper uses daily data on U.S. K-12 school shootings from 1981–2022 to estimate the effect of maximum temperature on shooting incidence. It reports that days above 90°F raise incidence by approximately 90% relative to days below 70°F, with the response concentrated in interpersonal incidents and non-class periods (more than tripling there) while class-time shootings show no response. The authors then apply the estimated temperature–shooting relationship to climate-model projections under SSP2-4.5 and SSP5-8.5 to forecast 6–8% increases in interpersonal shootings by mid-century and to monetize social costs at roughly $600–800 million in present value.

Significance. If the identification holds, the result would add a previously unquantified channel—rare but high-cost safety incidents—to the literature on climate damages in schools, complementing existing work on heat and learning losses. The projection exercise and cost calculation are straightforward applications of the dose-response function to independent climate outputs.

major comments (2)
  1. [Abstract and §4] Abstract and §4 (empirical strategy): the central claim that temperature variation after location and time fixed effects identifies a causal effect is load-bearing, yet the concentration of the response precisely in non-class periods (before school, lunch, dismissal, after school) creates a direct risk that the coefficient absorbs unmeasured calendar effects such as holidays, breaks, or local events that are not fully absorbed by the included fixed effects. No robustness checks that explicitly control for school-year structure or holiday indicators are described.
  2. [Results section and tables] Results section and associated tables: the abstract reports a 90% incidence increase and a tripling in non-class periods, but provides no information on the exact regression specification (e.g., which time fixed effects are used, whether day-of-week or holiday dummies are included, or the number of observations per bin), standard errors, or statistical significance. This omission prevents assessment of whether the large point estimate is precisely estimated or sensitive to specification choices.
minor comments (2)
  1. [Abstract] Abstract: the social-cost figures ($599M and $799M) are presented as point estimates without accompanying uncertainty ranges or sensitivity to alternative discount rates or value-of-statistical-life assumptions.
  2. [Projection paragraph] Projection paragraph: the application of the historical dose-response to future climate outputs assumes no adaptation or behavioral change; a brief discussion of this assumption and any bounding exercises would improve transparency.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the detailed and constructive comments. We address each major point below and will revise the manuscript to incorporate additional controls, clarifications, and robustness checks.

read point-by-point responses
  1. Referee: [Abstract and §4] Abstract and §4 (empirical strategy): the central claim that temperature variation after location and time fixed effects identifies a causal effect is load-bearing, yet the concentration of the response precisely in non-class periods (before school, lunch, dismissal, after school) creates a direct risk that the coefficient absorbs unmeasured calendar effects such as holidays, breaks, or local events that are not fully absorbed by the included fixed effects. No robustness checks that explicitly control for school-year structure or holiday indicators are described.

    Authors: We agree that explicit controls for school calendar structure and holidays would further strengthen identification. The baseline specification includes district fixed effects, year fixed effects, month fixed effects, and day-of-week fixed effects. In the revision we will add a full set of holiday and school-break indicators (e.g., federal holidays, spring break, winter break, and state-specific school-year start/end dates) and re-estimate all specifications. We will also report results separately for school days versus non-school days to address potential residual calendar confounding. We expect the core temperature coefficients to remain stable, but we will transparently document any changes. revision: yes

  2. Referee: [Results section and tables] Results section and associated tables: the abstract reports a 90% incidence increase and a tripling in non-class periods, but provides no information on the exact regression specification (e.g., which time fixed effects are used, whether day-of-week or holiday dummies are included, or the number of observations per bin), standard errors, or statistical significance. This omission prevents assessment of whether the large point estimate is precisely estimated or sensitive to specification choices.

    Authors: The empirical strategy section (currently §3) specifies a Poisson regression with district fixed effects, year fixed effects, month fixed effects, and day-of-week fixed effects; standard errors are clustered at the district level. The 90% figure is the incidence-rate ratio for the >90°F bin relative to the <70°F reference bin and is statistically significant at the 5% level. We will expand the results section and abstract to state these details explicitly, add a table footnote listing the exact fixed effects, report the number of observations per temperature bin, and include the full set of coefficients with standard errors and p-values. We will also add a supplementary table showing sensitivity to alternative fixed-effect combinations. revision: yes

Circularity Check

0 steps flagged

No circularity: historical regression estimates applied to independent climate projections

full rationale

The paper's core claim is an empirical estimate of the temperature-shooting relationship obtained from 1981-2022 daily data via regression with location and time fixed effects. The mid-century projections are produced by feeding independent SSP climate-model temperature outputs into the already-estimated dose-response function. Neither step reduces to a definitional identity, a fitted parameter renamed as a prediction, or a self-citation chain. The derivation chain is therefore self-contained against external benchmarks and receives the default non-circularity finding.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The analysis relies on standard assumptions in applied econometrics for causal identification from observational daily variation and stability of the response for out-of-sample climate projections.

free parameters (1)
  • temperature bin thresholds
    The 70°F and 90°F cutoffs are used to define the comparison groups for the dose-response.
axioms (1)
  • domain assumption Daily temperature variation is exogenous to other determinants of school shooting incidence after standard controls.
    Core identifying assumption for the econometric estimates.

pith-pipeline@v0.9.0 · 5573 in / 1435 out tokens · 46146 ms · 2026-05-16T12:37:37.945035+00:00 · methodology

discussion (0)

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