Work-family policy trade-offs for mothers? Unpacking the cross-national variation in motherhood earnings penalties

Recent scholarship suggests welfare state interventions, as measured by policy indices, create gendered trade-offs wherein reduced work–family conflict corresponds to greater gender wage inequality. The authors reconsider these trade-offs by unpacking these indices and examining specific policy relationships with motherhood-based wage inequality to consider how different policies have different effects. Using original policy data and Luxembourg Income Study microdata, multilevel models across 22 countries examine the relationships among country-level family policies, tax policies, and the motherhood wage penalty. The authors find policies that maintain maternal labor market attachment through moderate-length leaves, publicly funded childcare, lower marginal tax rates on second earners, and paternity leave are correlated with smaller motherhood wage penalties

Use of Writing with Symbols 2000 Software to Facilitate Emergent Literacy Development

This paper outlines the use of the Writing with Symbols 2000 software to facilitate emergent literacy development. The program’s use of pictures incorporated with text has great potential to help young children with and without disabilities acquire fundamental literacy concepts about print, phonemic awareness, alphabetic principle, vocabulary development, and comprehension. The flexibility and features of the software allow early childhood professionals to create a variety of early literacy tools for the classroom, including worksheets, storybooks, and interactive activities

Detecting non-orthology in the COGs database and other approaches grouping orthologs using genome-specific best hits

Correct orthology assignment is a critical prerequisite of numerous comparative genomics procedures, such as function prediction, construction of phylogenetic species trees and genome rearrangement analysis. We present an algorithm for the detection of non-orthologs that arise by mistake in current orthology classification methods based on genome-specific best hits, such as the COGs database. The algorithm works with pairwise distance estimates, rather than computationally expensive and error-prone tree-building methods. The accuracy of the algorithm is evaluated through verification of the distribution of predicted cases, case-by-case phylogenetic analysis and comparisons with predictions from other projects using independent methods. Our results show that a very significant fraction of the COG groups include non-orthologs: using conservative parameters, the algorithm detects non-orthology in a third of all COG groups. Consequently, sequence analysis sensitive to correct orthology assignments will greatly benefit from these findings

Three strikes and you are out, but why? The psychology of public support for punishing rule breakers

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. . This study examines why the public supports the punishment of rule breakers. It does so within the context of a recently enacted California initiative mandating life in prison for repeat felons (the "three strikes" law). Antecedents of three aspects of people's reactions to rule breakers are explored: ( 1 ) support for the three strikes initiative, (2) support for punitiveness in dealing with rule breakers, and (3) willingness to abandon procedural protections when dealing with potential rule breakers. The results of interviews with members of the public suggest that the widely held view that public punitiveness develops primarily from concerns about crime and the courts and is primarily linked to public views about risk and dangerousness is incorrect. While these factors do influence public feelings, they are not the central reasons underlying public punitiveness. Instead, the source of people's concerns lies primarily in their evaluations of social conditions, including the decline in morality and discipline within the family and increases in the diversity of society. These concerns are about issues of moral cohesion with people feeling that the quality and extent of social bonds and social consensus has deteriorated in American society. Wiley and Law and Society Associatio

Microphysical particle properties derived from inversion algorithms developed in the framework of EARLINET

© Author(s) 2015. CC Attribution 3.0 License. An earlier version of this paper was published in Atmospheric Measurement Techniques Discussions: https://dx.doi.org/10.5194/amtd-8-12823-2015.We present a summary on the current status of two inversion algorithms that are used in EARLINET for the inversion of data collected with EARLINET multiwavelength Raman lidars. These instruments measure backscatter coecients at 355, 532, and 1064 nm, and extinction coecients at 355 and 532 nm. Development of these two algorithms started in 2000 when EARLINET was founded. The algorithms are based on manually controlled inversion of optical data which allows for detailed sensitivity studies and thus provides us with comparably high quality of the derived data products. The algorithms allow us to derive particle eective radius, and volume and surface-area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light-absorption needs to be known with high accuracy. Single-scattering albedo can be computed from the retrieved microphysical parameters and allows us to categorize aerosols into high and low absorbing aerosols. We discuss the current status of these manually operated algorithms, the potentially achievable accuracy of data products, and the goals for future work on the basis of a few exemplary simulations with synthetic optical data. The optical data used in our study cover a range of Ångström exponents and extinction-to-backscatter (lidar) ratios that are found from lidar measurements of various aerosol types.We also tested aerosol scenarios that are considered highly unlikely, e.g., the lidar ratios fall outside the commonly accepted range of values measured with Raman lidar, even though the underlying microphysical particle properties are not uncommon. The goal of this part of the study is to test robustness of the algorithms toward their ability to identify aerosol types that have not been measured so far, but cannot be ruled out based on our current knowledge of aerosol physics. We computed the optical data from monomodal logarithmic particle size distributions, i.e., we explicitly excluded the more complicated case of bimodal particle size distributions which is a topic of ongoing research work. Another constraint is that we only considered particles of spherical shape in our simulations. We considered particle radii as large as 7–10 μm in our simulations. That particle size does not only cover the size range of particles in the fine-mode fraction of naturally occurring particle size distributions but also covers a considerable part of the coarse-mode fraction of particle size distributions. We considered optical-data errors of 15% in the simulation studies. We target 50% uncertainty as a reasonable threshold for our data products, though we attempt to obtain data products with less uncertainty in future work.Peer reviewe

An approach to describing and analysing bulk biological annotation quality: a case study using UniProtKB

Motivation: Annotations are a key feature of many biological databases, used to convey our knowledge of a sequence to the reader. Ideally, annotations are curated manually, however manual curation is costly, time consuming and requires expert knowledge and training. Given these issues and the exponential increase of data, many databases implement automated annotation pipelines in an attempt to avoid un-annotated entries. Both manual and automated annotations vary in quality between databases and annotators, making assessment of annotation reliability problematic for users. The community lacks a generic measure for determining annotation quality and correctness, which we look at addressing within this article. Specifically we investigate word reuse within bulk textual annotations and relate this to Zipf's Principle of Least Effort. We use UniProt Knowledge Base (UniProtKB) as a case study to demonstrate this approach since it allows us to compare annotation change, both over time and between automated and manually curated annotations. Results: By applying power-law distributions to word reuse in annotation, we show clear trends in UniProtKB over time, which are consistent with existing studies of quality on free text English. Further, we show a clear distinction between manual and automated analysis and investigate cohorts of protein records as they mature. These results suggest that this approach holds distinct promise as a mechanism for judging annotation quality. Availability: Source code is available at the authors website: http://homepages.cs.ncl.ac.uk/m.j.bell1/annotation. Contact: [email protected]: Paper accepted at The European Conference on Computational Biology 2012 (ECCB'12). Subsequently will be published in a special issue of the journal Bioinformatics. Paper consists of 8 pages, made up of 5 figure

Public attitudes towards healthcare policies promoting tobacco cessation in Germany: results from the representative German study on tobacco use (DEBRA study)

Objective The aim of this study was to assess public acceptance of four possible healthcare policies supporting tobacco dependence treatment in line with the Framework Convention for Tobacco Control, Article 14 recommendations in Germany. Design Cross-sectional household survey. Setting Data were drawn from the German population and collected through computer-assisted, face-to-face interviews. Participants Representative random sample of 2087 people (>14 years) from the German population. Outcome measures Public acceptance was measured regarding (1) treatment cost reimbursement, (2) standard training for health professionals on offering cessation treatment, and making cessation treatment a standard part of care for smokers with (3) physical or (4) mental disorders. Association characteristics with smoking status and socio-economic status (SES) were assessed. Results Support for all policies was high (50%–68%), even among smokers (48%–66%). Ex-smokers and neversmokers were more likely to support standard training on cessation for health professionals than current smokers (OR 1.43, 95%CI 1.07 to 1.92; OR 1.43; 95%CI 1.14 to 1.79, respectively). Ex-smokers were also more likely than current smokers to support cessation treatment for smokers with mental disorders (OR 1.39, 95%CI 1.11 to 1.73). Men were less likely than women to support cessation treatment for smokers with physical diseases (OR 0.74, 95%CI 0.60 to 0.91) and free provision of treatment (OR 0.80, 95%CI 0.66 to 0.97). Offering cessation treatment to smokers with physical disorders was generally more accepted than to those with mental health issues. Conclusions The majority of the German population supports healthcare policies to improve the availability and affordability of tobacco dependence treatment. Nonsmokers were more supportive than current smokers of two of the four policies, but odds of support were only about 40% higher. SES characteristics were not consistently associated with public acceptance

German Public Support for Tobacco Control Policy Measures: Results from the German Study on Tobacco Use (DEBRA), a Representative National Survey

Smoking prevalence in Germany remains high at approximately 28%. We assessed public support for tobacco legislation and associations between level of support and smoking and socio-demographic characteristics. Data from 2087 people were collected as part of the German Study on Tobacco Use (“DEBRA”): a nationally representative, face-to-face household survey. Public support was measured on total ban of sale, raising the minimum age for sales, taxation of tobacco industry sales, research into e-cigarettes, and ban of smoking in cars when children are present. Associations were assessed with multivariate logistic regression. Over 50% of the German population support taxing industry profits (57.3%) and assessing e-cigarettes as an aid to quit smoking (55.5%). Over 40% support raising the legal age of sale (43.1%), and 22.9% support a total ban on tobacco sales. A smoking ban in cars when children are present was most popular (71.5%), even among current smokers (67.0%). There is public support for stricter tobacco control measures in Germany. A smoking ban in cars when children are present could be a feasible policy to implement

Solution Synthesis and Characterization of a Long and Curved Graphene Nanoribbon with Hybrid Cove–Armchair–Gulf Edge Structures

Dedicated to Professor Klaus Müllen on the occasion of his 75th birthday