Gender equality and girls education: Investigating frameworks, disjunctures and meanings of quality education

The article draws on qualitative educational research across a diversity of low-income countries to examine the gendered inequalities in education as complex, multi-faceted and situated rather than a series of barriers to be overcome through linear input–output processes focused on isolated dimensions of quality. It argues that frameworks for thinking about educational quality often result in analyses of gender inequalities that are fragmented and incomplete. However, by considering education quality more broadly as a terrain of quality it investigates questions of educational transitions, teacher supply and community participation, and develops understandings of how education is experienced by learners and teachers in their gendered lives and their teaching practices. By taking an approach based on theories of human development the article identifies dynamics of power underpinning gender inequalities in the literature and played out in diverse contexts and influenced by social, cultural and historical contexts. The review and discussion indicate that attaining gender equitable quality education requires recognition and understanding of the ways in which inequalities intersect and interrelate in order to seek out multi-faceted strategies that address not only different dimensions of girls’ and women’s lives, but understand gendered relationships and structurally entrenched inequalities between women and men, girls and boys

Motivation for or from bilingual education? A comparative study of learner views in the Netherlands

Teaching and Teacher Learning (ICLON

Beyond hybridization: the genetic impacts of non-reproductive ecological interactions of salmon aquaculture on wild populations

Cultured Atlantic salmon Salmo salar are of international socioeconomic value, and the process of domestication has resulted in significant behavioural, morphological, and allelic differences from wild populations. Substantial evidence indicates that direct genetic interactions or interbreeding between wild and escaped farmed Atlantic salmon occurs, genetically altering wild salmon and reducing population viability. However, genetic interactions may also occur through ecological mechanisms (e.g. disease, parasites, predation, competition), both in conjunction with and in the absence of interbreeding. Here we examine existing evidence for ecological and non-reproductive genetic interactions between domestic Atlantic salmon and wild populations and the potential use of genetic and genomic tools to resolve these impacts. Our review identified examples of genetic changes resulting from ecological processes, predominately through pathogen or parasite transmission. In addition, many examples were identified where aquaculture activities have either altered the selective landscape experienced by wild populations or resulted in reductions in population abundance, both of which are consistent with the widespread occurrence of indirect genetic changes. We further identify opportunities for genetic or genomic methods to quantify these impacts, though careful experimental design and pre-impact comparisons are often needed to accurately attribute genetic change to aquaculture activities. Our review indicates that ecological and non-reproductive genetic interactions are important, and further study is urgently needed to support an integrated understanding of aquaculture-ecosystem interactions, their implications for ecosystem stability, and the development of potential mitigation and management strategies

Text Mining Improves Prediction of Protein Functional Sites

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions

Can sexual selection drive female life histories? A comparative study on Galliform birds

Sexual selection is an important driver of many of the most spectacular morphological traits that we find in the animal kingdom (for example see Andersson, 1994). As such, sexual selection is most often emphasized as

The structural and content aspects of abstracts versus bodies of full text journal articles are different

<p>Abstract</p> <p>Background</p> <p>An increase in work on the full text of journal articles and the growth of PubMedCentral have the opportunity to create a major paradigm shift in how biomedical text mining is done. However, until now there has been no comprehensive characterization of how the bodies of full text journal articles differ from the abstracts that until now have been the subject of most biomedical text mining research.</p> <p>Results</p> <p>We examined the structural and linguistic aspects of abstracts and bodies of full text articles, the performance of text mining tools on both, and the distribution of a variety of semantic classes of named entities between them. We found marked structural differences, with longer sentences in the article bodies and much heavier use of parenthesized material in the bodies than in the abstracts. We found content differences with respect to linguistic features. Three out of four of the linguistic features that we examined were statistically significantly differently distributed between the two genres. We also found content differences with respect to the distribution of semantic features. There were significantly different densities per thousand words for three out of four semantic classes, and clear differences in the extent to which they appeared in the two genres. With respect to the performance of text mining tools, we found that a mutation finder performed equally well in both genres, but that a wide variety of gene mention systems performed much worse on article bodies than they did on abstracts. POS tagging was also more accurate in abstracts than in article bodies.</p> <p>Conclusions</p> <p>Aspects of structure and content differ markedly between article abstracts and article bodies. A number of these differences may pose problems as the text mining field moves more into the area of processing full-text articles. However, these differences also present a number of opportunities for the extraction of data types, particularly that found in parenthesized text, that is present in article bodies but not in article abstracts.</p

Social health and change in cognitive capability among older adults:findings from four European longitudinal studies

Introduction: In this study we examine whether social health markers measured at baseline are associated with differences in cognitive capability and in the rate of cognitive decline over an 11-to-18-year period among older adults and compare results across studies. Methods: We applied an integrated data analysis approach to 16,858 participants (mean age 65 years; 56% female) from the National Survey for Health and Development (NSHD), the English Longitudinal Study of Aging (ELSA), the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), and the Rotterdam Study. We used multilevel models to examine social health in relation to cognitive capability and the rate of cognitive decline. Results: Pooled estimates show distinct relationships between markers of social health and cognitive domains e.g., a large network size (≥6 people vs none) was associated with higher executive function (0.17 SD[95%CI:0.0, 0.34], I2=27%) but not with memory (0.08 SD[95%CI: -0.02, 0.18], I2=19%). We also observed pooled associations between being married or cohabiting, having a large network size and participating in social activities with slower decline in cognitive capability, however estimates were close to zero e.g., 0.01SD/year [95%CI: 0.01 to 0.02] I2=19% for marital status and executive function. There were clear study-specific differences: results for average processing speed were the most homogenous and results for average memory were the most heterogenous. Conclusion: Overall, markers of good social health have a positive association with cognitive capability. However, we found differential associations between specific markers of social health and cognitive domains and differences between studies. These findings highlight the importance of examining between study differences and considering context specificity of findings in developing and deploying any intervention