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Coronavirus Is Pushing Teacher Hiring Online. Here's What That Means

Districts that can screen, interview, and select candidates virtually will have less disruption to their hiring, despite how coronavirus is upending every aspect of school operations.




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In Some States, ESSA Means More Powers for Local School Boards

Some states, such as California, Kentucky and North Dakota plan to use the Every Student Succeeds Act to bolster the decision-making powers of their local school boards in the coming years.




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Student Perspective: The True Meaning of Aloha

"Aloha" isn't just a greeting; in a way it is their way of life, and when you distort that sacred word, you distort their way of life.




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What Democratic Victories in Virginia and New Jersey Mean for K-12 Policy

Virginia Gov.-elect Ralph Northam has said he would further restrict that state's charter laws, and New Jersey Gov.-elect Phil Murphy has promised to pull the state out of the PARCC testing consortium.




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Stories from the soul : a guide to finding meaning in your story / Lyn Bray.




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Boys : what it means to become a man / Rachel Giese.

Boys -- Psychology.




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The slow moon climbs : the science, history and meaning of menopause / Susan P. Mattern.

Menopause.




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Directions for preparing aerated medicinal waters, by means of the improved glass machines made at Leith Glass-Works.

Edinburgh : printed for William Creech, 1787.




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Domestic midwife : or, the best means of preventing danger in child-birth, considered / by Margaret Stephen.

London : published by S.W. Fores, 1795.




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The educational and subsidiary provisions of the Birmingham Royal School of Medicine and Surgery set forth in a letter to the Rev. Dr. Samuel Wilson Warneford ... : the whole being intended to shew the importance and practicability of applying the means a

Oxford : printed by W. Baxter, 1843.




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Oregon's Sabrina Ionescu, Ruthy Hebard, Satou Sabally share meaning of Naismith Starting 5 honor

Pac-12 Networks' Ashley Adamson speaks with Oregon stars Sabrina Ionescu, Ruthy Hebard and Satou Sabally to hear how special their recent Naismith Starting 5 honor was, as the Ducks comprise three of the nation's top five players. Ionescu (point guard), Sabally (small forward) and Hebard (power forward) led the Ducks to a 31-2 record in the 2019-20 season before it was cut short.




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Univariate mean change point detection: Penalization, CUSUM and optimality

Daren Wang, Yi Yu, Alessandro Rinaldo.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1917--1961.

Abstract:
The problem of univariate mean change point detection and localization based on a sequence of $n$ independent observations with piecewise constant means has been intensively studied for more than half century, and serves as a blueprint for change point problems in more complex settings. We provide a complete characterization of this classical problem in a general framework in which the upper bound $sigma ^{2}$ on the noise variance, the minimal spacing $Delta $ between two consecutive change points and the minimal magnitude $kappa $ of the changes, are allowed to vary with $n$. We first show that consistent localization of the change points is impossible in the low signal-to-noise ratio regime $frac{kappa sqrt{Delta }}{sigma }preceq sqrt{log (n)}$. In contrast, when $frac{kappa sqrt{Delta }}{sigma }$ diverges with $n$ at the rate of at least $sqrt{log (n)}$, we demonstrate that two computationally-efficient change point estimators, one based on the solution to an $ell _{0}$-penalized least squares problem and the other on the popular wild binary segmentation algorithm, are both consistent and achieve a localization rate of the order $frac{sigma ^{2}}{kappa ^{2}}log (n)$. We further show that such rate is minimax optimal, up to a $log (n)$ term.




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Bayesian variance estimation in the Gaussian sequence model with partial information on the means

Gianluca Finocchio, Johannes Schmidt-Hieber.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 239--271.

Abstract:
Consider the Gaussian sequence model under the additional assumption that a fixed fraction of the means is known. We study the problem of variance estimation from a frequentist Bayesian perspective. The maximum likelihood estimator (MLE) for $sigma^{2}$ is biased and inconsistent. This raises the question whether the posterior is able to correct the MLE in this case. By developing a new proving strategy that uses refined properties of the posterior distribution, we find that the marginal posterior is inconsistent for any i.i.d. prior on the mean parameters. In particular, no assumption on the decay of the prior needs to be imposed. Surprisingly, we also find that consistency can be retained for a hierarchical prior based on Gaussian mixtures. In this case we also establish a limiting shape result and determine the limit distribution. In contrast to the classical Bernstein-von Mises theorem, the limit is non-Gaussian. We show that the Bayesian analysis leads to new statistical estimators outperforming the correctly calibrated MLE in a numerical simulation study.




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$k$-means clustering of extremes

Anja Janßen, Phyllis Wan.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1211--1233.

Abstract:
The $k$-means clustering algorithm and its variant, the spherical $k$-means clustering, are among the most important and popular methods in unsupervised learning and pattern detection. In this paper, we explore how the spherical $k$-means algorithm can be applied in the analysis of only the extremal observations from a data set. By making use of multivariate extreme value analysis we show how it can be adopted to find “prototypes” of extremal dependence and derive a consistency result for our suggested estimator. In the special case of max-linear models we show furthermore that our procedure provides an alternative way of statistical inference for this class of models. Finally, we provide data examples which show that our method is able to find relevant patterns in extremal observations and allows us to classify extremal events.




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Oriented first passage percolation in the mean field limit

Nicola Kistler, Adrien Schertzer, Marius A. Schmidt.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 2, 414--425.

Abstract:
The Poisson clumping heuristic has lead Aldous to conjecture the value of the oriented first passage percolation on the hypercube in the limit of large dimensions. Aldous’ conjecture has been rigorously confirmed by Fill and Pemantle ( Ann. Appl. Probab. 3 (1993) 593–629) by means of a variance reduction trick. We present here a streamlined and, we believe, more natural proof based on ideas emerged in the study of Derrida’s random energy models.




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A joint mean-correlation modeling approach for longitudinal zero-inflated count data

Weiping Zhang, Jiangli Wang, Fang Qian, Yu Chen.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 1, 35--50.

Abstract:
Longitudinal zero-inflated count data are widely encountered in many fields, while modeling the correlation between measurements for the same subject is more challenge due to the lack of suitable multivariate joint distributions. This paper studies a novel mean-correlation modeling approach for longitudinal zero-inflated regression model, solving both problems of specifying joint distribution and parsimoniously modeling correlations with no constraint. The joint distribution of zero-inflated discrete longitudinal responses is modeled by a copula model whose correlation parameters are innovatively represented in hyper-spherical coordinates. To overcome the computational intractability in maximizing the full likelihood function of the model, we further propose a computationally efficient pairwise likelihood approach. We then propose separated mean and correlation regression models to model these key quantities, such modeling approach can also handle irregularly and possibly subject-specific times points. The resulting estimators are shown to be consistent and asymptotically normal. Data example and simulations support the effectiveness of the proposed approach.




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Can $p$-values be meaningfully interpreted without random sampling?

Norbert Hirschauer, Sven Grüner, Oliver Mußhoff, Claudia Becker, Antje Jantsch.

Source: Statistics Surveys, Volume 14, 71--91.

Abstract:
Besides the inferential errors that abound in the interpretation of $p$-values, the probabilistic pre-conditions (i.e. random sampling or equivalent) for using them at all are not often met by observational studies in the social sciences. This paper systematizes different sampling designs and discusses the restrictive requirements of data collection that are the indispensable prerequisite for using $p$-values.




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Detecting relevant changes in the mean of nonstationary processes—A mass excess approach

Holger Dette, Weichi Wu.

Source: The Annals of Statistics, Volume 47, Number 6, 3578--3608.

Abstract:
This paper considers the problem of testing if a sequence of means $(mu_{t})_{t=1,ldots ,n}$ of a nonstationary time series $(X_{t})_{t=1,ldots ,n}$ is stable in the sense that the difference of the means $mu_{1}$ and $mu_{t}$ between the initial time $t=1$ and any other time is smaller than a given threshold, that is $|mu_{1}-mu_{t}|leq c$ for all $t=1,ldots ,n$. A test for hypotheses of this type is developed using a bias corrected monotone rearranged local linear estimator and asymptotic normality of the corresponding test statistic is established. As the asymptotic variance depends on the location of the roots of the equation $|mu_{1}-mu_{t}|=c$ a new bootstrap procedure is proposed to obtain critical values and its consistency is established. As a consequence we are able to quantitatively describe relevant deviations of a nonstationary sequence from its initial value. The results are illustrated by means of a simulation study and by analyzing data examples.




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Semi-supervised inference: General theory and estimation of means

Anru Zhang, Lawrence D. Brown, T. Tony Cai.

Source: The Annals of Statistics, Volume 47, Number 5, 2538--2566.

Abstract:
We propose a general semi-supervised inference framework focused on the estimation of the population mean. As usual in semi-supervised settings, there exists an unlabeled sample of covariate vectors and a labeled sample consisting of covariate vectors along with real-valued responses (“labels”). Otherwise, the formulation is “assumption-lean” in that no major conditions are imposed on the statistical or functional form of the data. We consider both the ideal semi-supervised setting where infinitely many unlabeled samples are available, as well as the ordinary semi-supervised setting in which only a finite number of unlabeled samples is available. Estimators are proposed along with corresponding confidence intervals for the population mean. Theoretical analysis on both the asymptotic distribution and $ell_{2}$-risk for the proposed procedures are given. Surprisingly, the proposed estimators, based on a simple form of the least squares method, outperform the ordinary sample mean. The simple, transparent form of the estimator lends confidence to the perception that its asymptotic improvement over the ordinary sample mean also nearly holds even for moderate size samples. The method is further extended to a nonparametric setting, in which the oracle rate can be achieved asymptotically. The proposed estimators are further illustrated by simulation studies and a real data example involving estimation of the homeless population.




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On estimation of nonsmooth functionals of sparse normal means

O. Collier, L. Comminges, A.B. Tsybakov.

Source: Bernoulli, Volume 26, Number 3, 1989--2020.

Abstract:
We study the problem of estimation of $N_{gamma }( heta )=sum_{i=1}^{d}| heta _{i}|^{gamma }$ for $gamma >0$ and of the $ell _{gamma }$-norm of $ heta $ for $gamma ge 1$ based on the observations $y_{i}= heta _{i}+varepsilon xi _{i}$, $i=1,ldots,d$, where $ heta =( heta _{1},dots , heta _{d})$ are unknown parameters, $varepsilon >0$ is known, and $xi _{i}$ are i.i.d. standard normal random variables. We find the non-asymptotic minimax rate for estimation of these functionals on the class of $s$-sparse vectors $ heta $ and we propose estimators achieving this rate.




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Interacting reinforced stochastic processes: Statistical inference based on the weighted empirical means

Giacomo Aletti, Irene Crimaldi, Andrea Ghiglietti.

Source: Bernoulli, Volume 26, Number 2, 1098--1138.

Abstract:
This work deals with a system of interacting reinforced stochastic processes , where each process $X^{j}=(X_{n,j})_{n}$ is located at a vertex $j$ of a finite weighted directed graph, and it can be interpreted as the sequence of “actions” adopted by an agent $j$ of the network. The interaction among the dynamics of these processes depends on the weighted adjacency matrix $W$ associated to the underlying graph: indeed, the probability that an agent $j$ chooses a certain action depends on its personal “inclination” $Z_{n,j}$ and on the inclinations $Z_{n,h}$, with $h eq j$, of the other agents according to the entries of $W$. The best known example of reinforced stochastic process is the Pólya urn. The present paper focuses on the weighted empirical means $N_{n,j}=sum_{k=1}^{n}q_{n,k}X_{k,j}$, since, for example, the current experience is more important than the past one in reinforced learning. Their almost sure synchronization and some central limit theorems in the sense of stable convergence are proven. The new approach with weighted means highlights the key points in proving some recent results for the personal inclinations $Z^{j}=(Z_{n,j})_{n}$ and for the empirical means $overline{X}^{j}=(sum_{k=1}^{n}X_{k,j}/n)_{n}$ given in recent papers (e.g. Aletti, Crimaldi and Ghiglietti (2019), Ann. Appl. Probab. 27 (2017) 3787–3844, Crimaldi et al. Stochastic Process. Appl. 129 (2019) 70–101). In fact, with a more sophisticated decomposition of the considered processes, we can understand how the different convergence rates of the involved stochastic processes combine. From an application point of view, we provide confidence intervals for the common limit inclination of the agents and a test statistics to make inference on the matrix $W$, based on the weighted empirical means. In particular, we answer a research question posed in Aletti, Crimaldi and Ghiglietti (2019).




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4 Ways to Help Students Cultivate Meaningful Connections Through Tech

The CEO of Move This World isn't big on screen time, but in the midst of the coronavirus pandemic, technology--when used with care--can help strengthen relationships.

The post 4 Ways to Help Students Cultivate Meaningful Connections Through Tech appeared first on Market Brief.




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Conditionally Conjugate Mean-Field Variational Bayes for Logistic Models

Daniele Durante, Tommaso Rigon.

Source: Statistical Science, Volume 34, Number 3, 472--485.

Abstract:
Variational Bayes (VB) is a common strategy for approximate Bayesian inference, but simple methods are only available for specific classes of models including, in particular, representations having conditionally conjugate constructions within an exponential family. Models with logit components are an apparently notable exception to this class, due to the absence of conjugacy among the logistic likelihood and the Gaussian priors for the coefficients in the linear predictor. To facilitate approximate inference within this widely used class of models, Jaakkola and Jordan ( Stat. Comput. 10 (2000) 25–37) proposed a simple variational approach which relies on a family of tangent quadratic lower bounds of the logistic log-likelihood, thus restoring conjugacy between these approximate bounds and the Gaussian priors. This strategy is still implemented successfully, but few attempts have been made to formally understand the reasons underlying its excellent performance. Following a review on VB for logistic models, we cover this gap by providing a formal connection between the above bound and a recent Pólya-gamma data augmentation for logistic regression. Such a result places the computational methods associated with the aforementioned bounds within the framework of variational inference for conditionally conjugate exponential family models, thereby allowing recent advances for this class to be inherited also by the methods relying on Jaakkola and Jordan ( Stat. Comput. 10 (2000) 25–37).




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Heteromodal Cortical Areas Encode Sensory-Motor Features of Word Meaning

The capacity to process information in conceptual form is a fundamental aspect of human cognition, yet little is known about how this type of information is encoded in the brain. Although the role of sensory and motor cortical areas has been a focus of recent debate, neuroimaging studies of concept representation consistently implicate a network of heteromodal areas that seem to support concept retrieval in general rather than knowledge related to any particular sensory-motor content. We used predictive machine learning on fMRI data to investigate the hypothesis that cortical areas in this "general semantic network" (GSN) encode multimodal information derived from basic sensory-motor processes, possibly functioning as convergence–divergence zones for distributed concept representation. An encoding model based on five conceptual attributes directly related to sensory-motor experience (sound, color, shape, manipulability, and visual motion) was used to predict brain activation patterns associated with individual lexical concepts in a semantic decision task. When the analysis was restricted to voxels in the GSN, the model was able to identify the activation patterns corresponding to individual concrete concepts significantly above chance. In contrast, a model based on five perceptual attributes of the word form performed at chance level. This pattern was reversed when the analysis was restricted to areas involved in the perceptual analysis of written word forms. These results indicate that heteromodal areas involved in semantic processing encode information about the relative importance of different sensory-motor attributes of concepts, possibly by storing particular combinations of sensory and motor features.

SIGNIFICANCE STATEMENT The present study used a predictive encoding model of word semantics to decode conceptual information from neural activity in heteromodal cortical areas. The model is based on five sensory-motor attributes of word meaning (color, shape, sound, visual motion, and manipulability) and encodes the relative importance of each attribute to the meaning of a word. This is the first demonstration that heteromodal areas involved in semantic processing can discriminate between different concepts based on sensory-motor information alone. This finding indicates that the brain represents concepts as multimodal combinations of sensory and motor representations.




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The power of pollinators: why more bees means better food

What do cucumbers, mustard, almonds and alfalfa have in common? On the surface it appears to be very little. However, there is one thing they do share: They all owe their existence to the service of bees. There is more to the tiny striped helper than sweet honey and a painful sting. For millennia, it has carried out its service [...]




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Quarantine diaries: The meaning of cake

For close to 15 years, Reema Singh has been baking and selling cakes from her tiny shop on Parc Avenue in Montreal's Mile End. Cocoa Locale has been open throughout the pandemic because — well, it turns out that cake is essential.



  • News/Canada/Montreal

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The Moral Meaning of the Plague

The virus is a test. We have the freedom to respond.





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CFL's Tackle Hunger program holds special meaning for Argos' Jamal Campbell

Jamal Campbell was never quite sure how the box of food ended up at his home while growing up in the community of Jane and Finch in Toronto, but he understood what it meant to his family.



  • Sports/Football/CFL

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Here are the latest COVID-19 statistics for Alberta — and what they mean

As the COVID-19 pandemic continues, there are so many numbers flying around, it's hard to keep track. Here, we'll do our best to keep track for you, with new charts updated daily and the context surrounding the data.



  • News/Canada/Calgary

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The meaning of baptism

A public baptism ceremony at the river becomes an opportunity to teach an onlooker about the true meaning of baptism.




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Donkey teaches Irish children true meaning of Christmas

The Creative Arts team perform their Christmas show for school children all over Ireland in the course of three weeks.




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The way I see it  - When it means what it says

It matters not if we are from 200 countries; we are one in Christ and shall be for eternity. OMNI-team member Greg Kernaghan about ‘globalisation’.




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Can you find meaning in failure?

A Christian football coach experiences what he says is the best gift from God, something “so much more than winning”.




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Fin24.com | MONEY CLINIC | Does lockdown mean my overdue tenants can't move out?

A landlord asks if his current tenants will still be able to move out at the end of the month as planned and whether his new tenant would be hindered from taking occupation. An attorney responds.




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Culture wars mean being gay isn’t good enough any more

Try to make sense of this if you can. The other day, a fund-raising event for the Democratic presidential candidate Pete Buttigieg, who is gay, was disrupted by protesters. But they weren’t the kind of protesters you’d expect to get angry about a gay candidate. The protesters were gay themselves. It was a protest against a gay man staged by gays. It was gays against gays. It was pink on pink. It was confusing.




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Courage for the Crimean Tatars 

A Crimean Tatar man shares how he gained courage and learnt vital truths through reading Into the Den of the Infidels, produced by OM EAST.




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When caring for the needy means us

"In order to fulfil our mandate, there are several needs we must invest in," says Stephan Bauer.




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Iain Macwhirter: Failures over testing means no end to coronavirus lockdown in Scotland

Next week, Nicola Sturgeon is promising to outline her proposals for lifting the lockdown. Good luck with that. She is unlikely to open the schools because she can't rely on parents to send their children.




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A New ESEA: A Cheat Sheet on What the Deal Means for Teachers

Your cheat sheet to the ESEA rewrite's teacher provisions.




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What Does Trump's Proposed Budget Mean for Schools? (Video)

In this Facebook Live discussion, Education Week reporters Alyson Klein and Andrew Ujifusa discuss President Trump's budget, and what it means for public education.




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It's One of the Most Fraught Words in Education. What Does It Mean?

Loaded or empirical? Incendiary or honest? Unavoidable or misleading? There’s a big disconnect around how we use the word “segregation.”




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Transgender Students, Athletics, Bullying: What the Equality Act Would Mean for Schools

Supporters of the bill say it would extend critical civil rights protections to more students. But opponents say it ignores parents' rights in schools and could lead to confusing situations for some children.




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Current Referral Patterns and Means to Improve Accuracy in Diagnosis of Undescended Testis

Primary care providers (PCPs) identify patients with undescended testis (UDT) and refer them to surgical specialists. Referral beyond the recommended times for orchiopexy has been reported, and PCPs' accuracy in identifying and distinguishing UDTs from retractile testes has been questioned.

We describe 3 observations that are strongly correlated with UDT, that is, birth history of UDT, prematurity, and visible scrotal asymmetry. UDT diagnoses are best made by 8 months of age, to reduce confusion with testicular retraction and to facilitate timely orchiopexy. (Read the full article)




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Obtaining Consent from Both Parents for Pediatric Research: What Does "Reasonably Available" Mean?

When research involving children is determined to present greater than minimal risk but no potential for direct benefit, permission is required from both parents, unless one is not reasonably available. These requirements are variably understood and applied, and guidance is lacking.

In a study on newborn screening, a sizeable percentage of fathers were not reasonably available, reflecting complexities of parental status and family relations. Guidelines developed in this project may provide tools for researchers and institutions to apply in other contexts. (Read the full article)




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Factors Associated With Meaningful Use Incentives in Children's Hospitals

Meaningful use (MU) incentive payments have been developed to encourage adoption and use of electronic health records (EHRs). Several studies have revealed children’s hospitals have unique barriers to the use of EHRs but were relatively early adopters of information technology.

Although a minority of children’s hospitals have succeeded with MU incentives, freestanding children’s hospitals are significantly more likely to succeed. Improvement of EHRs for pediatric use should focus on information exchange, quality reporting, and MU relevance to pediatrics. (Read the full article)




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Professional Learning Is More Meaningful When Done as a Team

High-quality professional learning is difficult to provide in education, principal Jasmine Kullar writes. Here's a solution.




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Supreme Court to Tackle DACA. What Does It Mean for Students, Teachers, and Schools?

The justices hear arguments Nov. 12 on the Trump administration's effort to end deportation relief under Deferred Action for Childhood Arrivals, in a case pitting the administration and GOP-leaning states against a host of education and advocacy groups.




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Three Things New Higher Education Bills Would Mean for Teachers and Students

It may be a slow time for K-12 activity on Capitol Hill, but you can't really same the same about higher education, with competing bills vying for attention in the House and Senate.




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Finding the meaning to life

A man thought he understood how life worked until he had a conversation with OM workers in Bangladesh. Then Jesus changed his life.