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‘QuantCrit’ (Quantitative Critical Race Theory) is a rapidly developing approach that seeks to challenge and improve the use of statistical data in social research by applying the insights of Critical Race Theory. As originally formulated, QuantCrit rests on five principles; 1) the centrality of racism; 2) numbers are not neutral; 3) categories are not natural; 4) voice and insight (data cannot ‘speak for itself); and 5) a social justice/equity orientation (Gillborn et al, 2018). The approach has quickly developed an international and interdisciplinary character, including applications in medicine (Gerido, 2020) and literature (Hammond, 2019). Simultaneously, there has been ferocious criticism from detractors outraged by the suggestion that numbers are anything other than objective and scientific (Airaksinen, 2018). In this context it is vital that the approach establishes some common understandings about good practice; in order to sustain rigor, make QuantCrit accessible to academics, practioners, and policymakers alike, and resist widespread attempts to over-simplify and pillory. This paper is intended to advance an iterative process of expanding and clarifying how to ‘QuantCrit’.
We investigated the effectiveness of a sustained and spiraled content literacy intervention that emphasizes building domain and topic knowledge schemas and vocabulary for elementary-grade students. The Model of Reading Engagement (MORE) intervention underscores thematic lessons that provide an intellectual structure for helping students connect new learning to a general schema in Grade 1 (animal survival), Grade 2 (scientific investigation of past events like dinosaur mass extinctions), and Grade 3 (scientific investigation of living systems). A total of 30 elementary schools (N = 2,870 students) were randomized to a treatment or control condition. In the treatment condition (i.e., full spiral curriculum), students participated in MORE content literacy lessons from Grades 1 to 3 during the school year and wide reading of thematically related informational texts in the summer following Grades 1 and 2. In the control condition (i.e., partial spiral curriculum), students participated in MORE lessons in only Grade 3. The Grade 3 lessons for both conditions were implemented online during the COVID-19 pandemic school year. Results reveal that treatment students outperformed control students on science vocabulary knowledge across all three grades. Furthermore, we found positive transfer effects on Grade 3 science reading (ES = .14), domain-general reading comprehension (ES = .11), and mathematics achievement (ES = .12). Treatment impacts were sustained at 14-month follow-up on Grade 4 reading comprehension (ES = .12) and mathematics achievement (ES = .16). Findings indicate that a content literacy intervention that spirals topics and vocabulary across grades can improve students’ long-term academic achievement outcomes.
Educational researchers often report effect sizes in standard deviation units (SD), but SD effects are hard to interpret. Effects are easier to interpret in percentile points, but conversion from SDs to percentile points involves a calculation that is not intuitive to educational stakeholders. We point out that, if the outcome variable is normally distributed, simply multiplying the SD effect by 37 usually gives an excellent approximation to the percentile-point effect. For students in the middle half of the distribution, the approximation is accurate to within 1 percentile point for effect sizes of up to 0.8 SD (or 29 to 30 percentile points).
We examine the impact of local labor market shocks and state unemployment insurance (UI) policies on student discipline in U.S. public schools. Analyzing school-level discipline data and firm-level layoffs in 23 states, we find that layoffs have little effect on discipline rates overall. However, effects differ across the UI benefit distribution. At the lowest benefit level ($265/week), a mass layoff increases out-of-school suspensions by 4.5%, with effects dissipating as UI benefits increase. Effects are consistently largest for Black students - especially in predominantly White schools - resulting in increased racial disproportionality in school discipline following layoffs in low-UI states.
Partisanship influenced learning modality after the pandemic’s onset, but it is unknown whether partisanship predicted other aspects of educational operations. We study the role of partisanship, race, markets, and public health in predicting a range of operations—from modality to family engagement to social-emotional support to teacher PD—throughout 2020-21 in the context of Virginia. Districts’ partisan makeup and racial composition were similarly predictive of in-person offerings throughout 2020-21 but partisanship was less predictive over time. District characteristics explained limited variation in other aspects of operations, though districts with larger private school sectors provided more supports. Results emphasize the role of partisanship, race, and markets in reopening but also suggest school operational decisions were less politicized than choice of modality.
Scholars disagree about the effect out-of-state university students have on potential in-state students. Despite paying a premium to attend state universities, researchers argue that out-of-state students may come at a cost to in-state students by negatively affecting academic quality or by crowding out in-state students. To study this relationship, we examine the effect of a 2016 policy at a highly ranked state flagship university that removed the limit on how many out-of-state students it could enroll. We find the policy caused an increase in out-of-state enrollment by around 29 percent and increased tuition revenue collected by the university by 47 percent. We argue that this revenue was used to fund increases in financial aid disbursed at the university, particularly to students from low-income households, indicating that out-of-state students cross-subsidize lower income students. We also fail to find evidence that this increase in out-of-state students had any effect on several measures of academic quality.
We estimate the effect of universal free school meal access through the Community Eligibility Program (CEP) on child BMI. Through the CEP, schools with high percentages of students qualified for free or reduced-priced meals can offer freebreakfast and lunchto all students. With administrative data from a large school district in Georgia, we use student-level BMI measures from the FitnessGram to compare within-student outcomes before and after CEP implementation across eligible and non-eligible schools. We find one year of CEP exposure increased expected BMI percentile by about 0.085 standard deviations, equivalent to a nearly 1.88- pound weight increase for a student of average height. We also find that the program led to a small increase in the likelihood of overweight and limited evidence of a small decrease in the likelihood of underweight. We do not find that the program increased student obesity risk. Examining the effects of CEP on child BMI by grade suggests that the overall effect is largely driven by students in middle schools, highlighting potential heterogeneity in the program’s impact across grades. The findings of this paper are relevant for researchers and policymakers concerned with the effects of universal free school meals on student health.
College success requires students to engage with their institution academically and administratively. Missteps with required administrative processes can threaten student persistence and success. Through two experimental studies, we assessed the effectiveness of an artificially intelligent text-based chatbot that provided proactive outreach and support to college students to navigate administrative processes and use campus resources. In both the two-year and four-year college context, outreach was most effective when focused on discrete administrative processes such as filing financial aid forms or registering for courses which were acute, time-sensitive, and for which outreach could be targeted to those for whom it was relevant. In the context of replicating studies to better inform policy and programmatic decision making, we draw three core lessons regarding the effective use of nudge-type efforts to promote college success.
Complexity and uncertainty in the college application process contribute to longstanding racial and socioeconomic disparities in enrollment. We leverage a large-scale experiment that combines an early guarantee of college admission with a proactive nudge, fee waiver, and structural application simplification to test the impacts of emerging “direct admissions” policies on students’ college-going behaviors. Students in the intervention were 2.7 percentage points (or 12%) more likely to submit a college application, with larger impacts for racially minoritized, first-generation, and low-income students. Students were most responsive to automatic offers from larger, higher quality institutions on the application margin, but were not more likely to subsequently enroll. In the face of growing adoption, we show this low-cost, low-touch intervention can move the needle on important college-going behaviors but is insufficient alone to increase enrollment given other barriers to access, including the ability to pay for college.