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Quantum impurity models with frustrated Kondo interactions can support quantum critical points with fractionalized excitations. Recent experiments [arXiv:2108.12691] on a circuit containing two coupled metal-semiconductor islands exhibit transport signatures of such a critical point. Here we show using bosonization that the double charge-Kondo model describing the device can be mapped in the Toulouse limit to a sine-Gordon model. Its Bethe-ansatz solution shows that a $\mathbb{Z}_3$ parafermion emerges at the critical point, characterized by a fractional $\tfrac{1}{2}\ln(3)$ residual entropy, and scattering fractional charges $e/3$. We also present full numerical renormalization group calculations for the model and show that the predicted behavior of conductance is consistent with experimental results., Comment: 5 pages+, 3 figures

We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218 \pm 9 \mu s.

Anisotropic hopping in a toy Hofstadter model was recently invoked to explain a rich and surprising Landau spectrum measured in twisted bilayer graphene away from the magic angle. Suspecting that such anisotropy could arise from unintended uniaxial strain, we extend the Bistritzer-MacDonald model to include uniaxial heterostrain. We find that such strain strongly influences band structure, shifting the three otherwise-degenerate van Hove points to different energies. Coupled to a Boltzmann magnetotransport calculation, this reproduces previously-unexplained non-saturating $B^2$ magnetoresistance over broad ranges of density near filling $\nu=\pm 2$, and predicts subtler features that had not been noticed in the experimental data. In contrast to these distinctive signatures in longitudinal resistivity, the Hall coefficient is barely influenced by strain, to the extent that it still shows a single sign change on each side of the charge neutrality point -- surprisingly, this sign change no longer occurs at a van Hove point. The theory also predicts a marked rotation of the electrical transport principal axes as a function of filling even for fixed strain and for rigid bands. More careful examination of interaction-induced nematic order versus strain effects in twisted bilayer graphene could thus be in order., Comment: 11 pages main text (4 figures) + 8 pages supplementary material (11 figures)

There is empirical evidence of substantial heterogeneity in economic mobility across geographic areas and the efficacy of schools has been suggested as an explanatory factor. Using administrative microdata from seven states covering nearly 3 million students, we explore the potential role of schools in promoting economic mobility by estimating cross-district variation in "academic mobility"--a term we use to describe the extent to which students' ranks in the distribution of academic performance change during their schooling careers. We show that there exists considerable heterogeneity in academic mobility across school districts. However, after aggregating our district-level measures of academic mobility to the commuting-zone level and merging them with geographically matched external estimates of economic mobility, we find little scope for geographic differences in academic mobility to meaningfully account for differences in economic mobility.

What does it mean for students to be in a gifted program? While about 7% of students nationally participate in gifted programs, relatively little is known about the experiences of students in these programs or how they vary across districts. Combining administrative and survey data, we describe the structure of gifted programs across nearly 300 school districts in Washington State. Using covariate adjustments and student fixed effects, we find that participation in gifted programs increases access to advanced courses, high-achieving peers, smaller classrooms, and more qualified teachers. These effects are largely concentrated in larger urban and suburban school districts that frequently run large, self-contained gifted programs. Effects of participation are much smaller for small school districts, rural or town school districts, and districts with small gifted programs. While gifted participation changes the educational environment for the average student in the state, the median school district program effect is near zero across the measures of educational environments we consider. This divergence is driven by a pattern of large school districts, high-income school districts, and urban and suburban school districts having programs with significantly larger effects on learning environments. Finally, we find that gifted program effects are larger for some student subgroups, but this is entirely due to district treatment effect heterogeneity, not differential effects on subgroups within districts.

A number of school districts and states have implemented transition intervention programs designed to help high school students graduate ready for college. This study estimates the effectiveness of a transition program implemented statewide in Kentucky for high school seniors called Targeted Interventions (TI). Using 11 years of linked panel data, this study tracks the college progression of seven cohorts of students as they move from high school into college. Using a difference-in-regression discontinuity design, we estimate the program's impact on college credit attainment and transfer as well as the extent to which the program has helped reshape pathways through college. We find that the TI program significantly increased the likelihood that students would take at least 15 credits during the first term in college, a key measure that has been shown to be predictive of college completion. These early effects, however, do not translate into statistically significant impacts on the likelihood of transfers from a 2-year to a 4-year college, or the likelihood of earning enough credits to graduate from college. We discuss some possible explanations for why the TI program did not lead to observable improvements in college transfer or credit accumulation.

There is growing interest in using measures of teacher applicant quality to improve hiring decisions, but the statistical properties of such measures are not well understood. We use unique data on structured ratings solicited from the references of teacher applicants to explore the dimensionality of measures of teacher applicant quality and the inter-rater reliability of the reference ratings. Despite questions about applicants designed to capture multiple dimensions of quality, factor analysis suggests that the reference ratings only capture one underlying dimension. Point estimates of inter-rater reliability range between 0.23 and 0.31 and are significantly lower for novice applicants. It is difficult to judge whether these levels of reliability are high or low in the current context given so little evidence on applicant assessment tools. [This paper was published in "Economics of Education Review" v83 Aug 2021.]

A growing quantitative literature finds evidence that student teaching placements predict later outcomes of teacher candidates and their students, but there is little large-scale quantitative evidence about the mechanisms for these estimated relationships. We use data from a survey of STEM teachers in Washington State to better understand how their perceptions of preparation are related to student teaching placements and current classroom environment. We find evidence that the composition of students in student teaching classrooms are predictive of STEM teachers' perceptions of their preparation. For example, STEM teachers who student taught in classrooms with more English Language Learners and economically disadvantaged students reported feeling prepared to teach these specific student populations. Likewise, STEM teachers who student taught in high-poverty classrooms tended to report feeling better prepared to manage their current classroom, particularly if they were currently teaching in a high-poverty classroom.

We used survey and administrative data from Washington State to assess the degree to which special education teacher preparation, district literacy instructional practices, and the alignment between preparation and practice were associated with the reading test score gains of students with high-incidence disabilities taught by early-career special education teachers in grades 4-8. These students tended to have larger reading gains when their district emphasized evidence-based literacy decoding practices (e.g., phonological awareness, phonics, and reading fluency) and when their special education teacher graduated from a teacher education program that also emphasized these practices. Students with high-incidence disabilities in districts that emphasized balanced literacy practices tended to have lower reading gains. Finally, students with high-incidence disabilities taught by early-career special education teachers tended to have larger reading gains when their teacher's student teaching placement was supervised by a more experienced cooperating teacher.

We use data on over 14,000 teacher candidates in Washington state, merged with employment data from the state's public schools and Unemployment Insurance system, to investigate the career paths and earnings of teacher candidates in the state. Around 75% of candidates are employed in some education position in each of the 5 years after student teaching, but we find considerable movement from education positions outside of public schools into public school teaching positions in the first few years after candidates complete student teaching. Candidates with STEM endorsements and candidates who graduated after the Great Recession are disproportionately likely to be employed in public K-12 teaching positions compared with other education positions. Finally, candidates employed in K-12 public schools earn considerably more on average than candidates employed outside of public schools, but due to the considerable compression of teacher salaries, many candidates who do not enter teaching--particularly candidates with STEM endorsements--earn more than they would have in K-12 public schools.

States are responsible for setting and evaluating the standards that teacher preparation programs (TPPs) must meet for accreditation. Despite the considerable investment that states make in this process, no prior research has linked the ratings of TPPs generated by program reviews to inservice teacher performance. In this paper, we describe analyses of program review ratings from Massachusetts and their relationship to formal inservice teacher evaluation ratings and the value-added effectiveness of teachers. When comparisons are made across all schools and districts in the state, we find that a TPP's review scores are positively predictive of both inservice teacher evaluations and value added of TPP graduates, particularly when scores are aggregated within specific categories like partnerships and field-based practices. These relationships, however, become more modest for teacher evaluations and statistically insignificant for value added when the relationships are identified based on comparisons between TPP graduates who are teaching in the same schools and districts. It is not possible to separate whether these differences are due to the TPPs, the schools and districts themselves, or the connections between them, so future work is necessary to further validate TPP review scores in this setting and others.

Since 2017, epitaxial graphene has been the base material for the US national standard for resistance. A future avenue of research within electrical metrology is to remove the need for strong magnetic fields, as is currently the case for devices exhibiting the quantum Hall effect. The quantum Hall effect is just one of many research endeavours that revolve around recent quantum physical phenomena like composite fermions, charge density waves, and topological properties [1-2]. New materials, like magnetically doped topological insulators (MTIs), offer access to the quantum anomalous Hall effect, which in its ideal form, could become a future resistance standard needing only a small permanent magnet to activate a quantized resistance value [3-5]. Furthermore, these devices could operate at zero-field for measurements, making the dissemination of the ohm more economical and portable. Here we present results on precision measurements of the h/e2 quantized plateau of Cr-Doped (BixSb1-x)2Te3 and give them context by comparing them to modern graphene-based resistance standards. Ultimately, MTI-based devices could be combined in a single system with magnetic-field-averse Josephson voltage standards to obtain an alternative quantum current standard.

In this research brief, the authors present evidence on how the diversity of the teacher workforce changes as "prospective" teachers advance through the teacher pipeline: tracking from 12th grade students as some obtain the education and certifications required to be eligible to teach in public schools, and some apply to and are hired into public schools. The authors are not the first to examine the teacher pipeline in this way (e.g., see, Putman et al., 2016), but they advance the literature by incorporating increased (and more recent) knowledge about how changes in the demographics of individuals who advance through different junctures or "nodes" in the pipeline (e.g., graduating high school and college, taking required teacher licensure exams, etc.) affect the diversity of the teacher workforce. This technique is used to simulate how changes in the likelihood that different demographic groups advance through the pipeline would be expected to affect the diversity of the early teacher workforce.

Numerous stories raise concerns that as the pandemic ends, there might be a rash of public school teachers that opt to leave teaching. Will a recovering economy combined with an extremely challenging school year lead to very high levels of teacher attrition just when school recovery efforts are kicking into high gear? Of course, it is too soon to know, but a look at the history can help gauge the magnitude of what might be expected in terms of teacher attrition. The authors do this using more than three decades of administrative data on the entire teaching workforce in Washington state. In this report, the authors plot several different measures of teacher attrition and mobility over time in Washington and see how these vary with the annual unemployment rate in the state. In particular, the authors examine data from the 1984-85 school year to the 2020-21 school year and calculate the proportion of teachers who, in the following year: (1) leave their schools and the state's public school workforce entirely; (2) leave their current teaching position for a non-teaching position within the state's public school systems; and (3) leave their school for another public school teaching position in the state. There are of course unique elements to transition from a pandemic, but 35 years of history would suggest it is unlikely to see increases of attrition of more than a percentage point or two. Is this a concern? For sure! But it also might be an exaggeration to think of this as a mass exodus.

The overwhelming majority of public school teachers enter the teaching profession only after completing an apprenticeship as a student teacher. A growing body of research demonstrates how important the student teaching experience, also known as clinical practice, is for developing teaching capacities and shaping teacher career paths. But recent evidence also points to the broader ramifications of student teacher placements for teacher hiring and staffing challenges, particularly in rural and disadvantaged schools. In this piece, we summarize the connections between student teaching and the problems that some districts and schools face in staffing teaching positions. We argue that pandemic-induced changes to student teaching can be leveraged to address these longstanding issues in the teacher pipeline.

The decision about how and when to open schools to in-person instruction has been a key question for policymakers throughout the COVID-19 pandemic. The instructional modality of schools has implications not only for the health and safety of students and staff, but also student learning and the degree to which parents can engage in job activities. We consider the role of instructional modality (in-person, hybrid, or remote instruction) in disease spread among the wider community. Using a variety of regression modeling strategies to address unobserved heterogeneity, we find that simple correlations show in-person modalities are correlated with increased COVID cases, but accounting for both pre-existing cases and a richer set of covariates brings estimates close to zero on average. In Ordinary Least Squares (OLS) specifications, in-person modality options are not associated with increased spread of COVID at low levels of pre-existing COVID cases, but cases do increase at moderate to high pre-existing COVID rates. A bounding exercise suggests that the OLS findings for in-person modality are likely to represent an upper bound on the true relationship. These findings are robust to the inclusion of county and district fixed effects in terms of the insignificance of the findings, but the models with fixed effects are also somewhat imprecisely estimated.

We use comprehensive administrative data from three states to document the relationships between geographic mobility and student outcomes during K-12 schooling. We focus specifically on "nonstructural" mobility events--which we define as school or district changes that do not occur naturally as the result of planned transitions between schools--and on longitudinal measures that capture these events cumulatively for students. We show that the number of nonstructural moves experienced by a student is a powerful indicator of low academic performance and graduation rates. Longitudinal information on student mobility is unlikely to be readily available to local practitioners--i.e., individual districts, schools, or teachers. However, due to recent investments in longitudinal data systems in most states, this information can be made available at low cost by state education agencies.

Students' performance on standardized tests is clearly predictive of their later outcomes (Goldhaber & Özek, 2019) but whether the costs of administering tests are justified by the value of the tests for improving students' outcomes is controversial. This controversy fuels heated debates over federal testing requirements, such as those instituted under No Child Left Behind (NCLB) and continued under the Every Student Succeeds Act (ESSA). All ESSA-required tests were canceled in the 2019-20 school year due to COVID-19, and there was significant political debate about whether they ought to be required in 2020-21. Ultimately the U.S. Department of Education (USDOE) allowed for some testing flexibility in the form of ESSA waivers. Below, we outline some of the common ways states might use tests to improve student outcomes and the implications of requested and approved waivers on these uses. In particular, we highlight features of waiver requests that are especially important if tests are to be used by specific actors (e.g., families) to benefit students in specific ways. We conclude with a discussion of how testing policy needs to be designed if statewide tests are going to both be useful and maintain political support.

Over the last few months, media outlets including Axios, CNN, The New York Times, and The Wall Street Journal have raised the specter that there may be a rise in teachers exiting the profession. The concern is that a post-pandemic private sector boom, combined with relatively low teacher pay and burnout from online teaching, are a combustible mix that will lead to sharply higher teacher attrition. This in turn could leave schools scrambling to address a teacher "shortage" at the very time they are trying to help students recover from the COVID pandemic. But, so far at least, data from a number of states and large cities suggest that fewer teachers left the profession in 2020 than in normal years. This brief uses data from more than three decades of administrative data on the entire teaching workforce in Washington state to analyze the degree to which variation in teacher turnover for individual schools and school types relative to variation over time that may be connected to economic conditions is observed. The authors examine two reasons that teachers leave their (public) school teaching positions: (1) "mobility," which tracks teachers who leave one public school, but end up employed in a teaching position in another (Washington) public school; and (2) "attrition," which tracks teachers who leave public school teaching in Washington entirely. The focus is on both of these types of turnover because both are connected to the ability of individual schools and districts to staff their classrooms, and prior work has connected both attrition and mobility to the characteristics of schools and districts.

We use a novel database of over 15,000 teacher candidates from 15 teacher education programs in Washington state to investigate the connections between specific teacher preparation experiences (e.g., endorsements, licensure test scores, and student teaching placements) and the likelihood that these candidates enter and leave the state's public teaching workforce within their first 2 years. As has been found in prior research, candidates with endorsements in hard-to-staff subjects like science, technology, engineering, and math and special education are significantly more likely to enter the public teaching workforce than candidates with elementary endorsements. We also find large differences in hiring rates over time, as candidates who graduated in the years prior to and during the Great Recession are far less likely to be hired than candidates in recent years. Finally, teacher candidates hired into the same school type (elementary, middle, or high school) or into schools and classrooms with similar student demographics as their student teaching placement are more likely to stay in the teaching workforce than other candidates who experience less alignment.

We use teacher candidate test scores on the Massachusetts Tests for Educator Licensure (MTEL), linked to student and teacher outcomes in the state, to investigate the predictive validity of these teacher licensure tests. We find that MTEL scores are positive and statistically significant predictors of teachers' in-service performance ratings and contributions to student test scores (i.e., value added) once they enter the workforce. We then explore whether these relationships vary for candidates and teachers of color. We find that teacher candidates of color have lower first-time pass rates and are also less likely to retake licensure tests if they fail than are White teacher candidates, but we do not find consistent evidence that MTEL scores are less predictive of value added for teachers of color. Finally, we find that MTEL scores are more predictive of teacher performance ratings for teachers of color than for White teachers.

How much do teachers value compensation that is deferred until retirement? This question is important because the vast majority of public school teachers are covered by defined benefit (DB) pension plans that "backload" a large share of compensation to retirement relative to the compensation structure in the private sector. There is little evidence, other than Fitzpatrick (2015), however, about whether DB pensions are consistent with teacher preferences for current and deferred compensation. This study examines a unique setting in Washington State, where teachers enroll in a hybrid, DB-Defined Contribution (DC) pension system, and have choices over their DC contribute rate. These choices reveal preferences about the value teachers place on current versus retirement compensation. We find that teachers choose to contribute an average of 8.18 percent, significantly more than the minimum required contribution of 5 percent. This suggests that teachers value retirement compensation significantly more than previously estimated by Fitzpatrick. Potential explanations for the difference in findings from prior evidence are discussed, including estimation strategies, differences in state settings, overall plan generosity, and the potential for teachers to view DB and DC pensions as different products.

This brief is one in a series aimed at providing K-12 education decision makers and advocates with an evidence base to ground discussions about how to best serve students during and following the novel coronavirus pandemic. Student teaching placements influence teacher effectiveness. If student teaching experiences are constrained by the pandemic, teacher candidates may lose valuable experiences and schools may lose the opportunity to shape and evaluate prospective hires. Teacher preparation programs and student teaching experiences play a major role in determining where candidates take job placements, in ways that can influence both job markets and staffing shortages. Teachers and teachers-in-training who participate in online practice teaching see significant improvements in teaching skills. School systems can provide in-service supports for new teachers whose student teaching experiences were interrupted or incomplete. Stronger partnerships between teacher preparation providers and remote districts have the potential to bring significant benefits, both for student teachers and for districts facing staffing shortages. Student teachers represent an important pool of additional talent for schools; creative deployment of student teachers could provide a major boost as the COVID-19 crisis continues. Low-quality teacher mentoring programs, as well as those that are not sustained across multiple years, are likely to be ineffective. Teacher effectiveness might show up differently in an online setting -- so relying on past measures of teacher quality will likely be insufficient.

The clinical teaching experience is one of the most important components of teacher preparation. Prior observational research has found that more effective mentors and schools with better professional climates are associated with better preparation for teacher candidates. We test these findings using an experimental assignment of teacher candidates to placement sites in two states. Candidates who were randomly assigned to higher quality placement sites experienced larger improvements in performance over the course of the clinical experience, as evaluated by university instructors. The findings suggest that improving clinical placement procedures can improve the teaching quality of candidates.

Defined benefit (DB) pension systems determine the size of pension payments using an employee's "final average salary". Thus, employees enrolled in DB pension systems face an incentive to "salary spike" -- strategically increase late career pensionable compensation -- to increase their retirement income. This is an important issue given that public pension systems face increasing scrutiny due to ongoing concerns about their fiscal sustainability. This paper develops an empirical method to quantify the prevalence of salary spiking by identifying cases where end-of-career compensation deviates from expected levels of compensation. We apply this method to the teacher pension systems in Illinois and examine how salary spiking changed in response to policy reform. The results suggest that salary spiking is very common, with about half of late career employees observed as having pensionable compensation that exceeds expectations. Policies designed to dissuade salary spiking by internalizing its costs across districts appear to reduce the prevalence of salary spiking, but there may be unintended consequences for individuals who are "not actually spiking," as such discouraging the assignment of supplementary responsibilities to late career employees.

There is growing interest in using measures of teacher applicant quality to improve hiring decisions, but the statistical properties of such measures are poorly understood. We present evidence on structured ratings solicited from teacher applicants' references. We find that the reference ratings capture only one underlying dimension of applicant quality, which may indicate a need to broaden the range of questions posed to professional references. Point estimates of inter-rater reliability range between 0.23 and 0.31 and are significantly lower for novice applicants. It is difficult to judge whether these levels of reliability are high or low in the current context given so little evidence on comparable applicant assessment tools.

Testing students and using test information to hold schools and, in some cases, teachers accountable for student achievement has arguably been the primary national strategy for school improvement over the past decade and a half. Tests are also intended to be used as a diagnostic tool to identify individual student needs, so that students can be set on a trajectory for long-term academic success. We use panel data from three states -- North Carolina, Massachusetts and Washington State -- to investigate how accurate early measures of achievement are in predicting later high school outcomes. We contribute to the literature in three distinct ways. First, the long panels we employ allow us to quantify the accuracy of models predicting how early (3rd and 4th grade) measures of student background and achievement predict several later schooling outcomes: 8th grade test achievement, high school course-taking, and high school graduation. Second, we test the extent to which predictions based on distinct segments of student data (e.g. grades 3 to 8, then 8 to 12) sacrifice forecast accuracy; this is of particular policy relevance for states or localities that do not yet have long administrative data panels. Finally, we test the degree to which the use of parameter estimates from models predicting schooling outcomes derived from one state diminish the accuracy of predicting outcomes in other states.

We use a novel database of student teaching placements in Washington State to investigate teachers' transitions from student teaching classrooms to first job classrooms and the implications for student achievement. We find that first-year teachers are more effective when they are teaching in the same grade, in the same school level, or in a classroom with student demographics similar to their student teaching classroom. We also document that only 27% of first-year teachers are teaching the same grade they student taught, and that first-year teachers tend to begin their careers in higher-poverty classrooms than their student teaching placements. This suggests that better aligning student teacher placements with first-year teacher hiring could be a policy lever for improving early-career teacher effectiveness.