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Lesbian, gay, bisexual and trans+ a (LGBT+) people report poorer health than the general population and worse experiences of healthcare particularly cancer, palliative/end-of-life, dementia and mental health provision. This is attributable to: a) social inequalities, including 'minority stress'; b) associated health-risk behaviours (e.g. smoking, excessive drug/alcohol use, obesity); c) loneliness and isolation, affecting physical/mental health and mortality; d) anticipated/experienced discrimination and e) inadequate understandings of needs among healthcare providers. Older LGBT+ people are particularly affected, due to the effects of both cumulative disadvantage and ageing. There is a need for greater and more robust research data to support growing international and national government initiatives aimed at addressing these health inequalities. We identify seven key research strategies: 1) Production of large datasets; 2) Comparative data collection; 3) Addressing diversity and intersectionality among LGBT+ older people; 4) Investigation of healthcare services' capacity to deliver LGBT+ affirmative healthcare and associated education and training needs; 5) Identification of effective health promotion and/or treatment interventions for older LGBT+ people, and subgroups within this umbrella category; 6) Development an (older) LGBT+ health equity model; 7) Utilisation of social justice concepts to ensure meaningful, change-orientated data production which will inform and support government policy, health promotion and healthcare interventions.

"Behavioral scientists working in organizations today have access to unprecedented amounts of data. Networked computing and software tools are changing the landscape of organizational research in fundamental ways. Information technology facilitates creation of vast amounts of data. In organizational research, online surveys, interactive interviews, computer-based assessment, and other digital tools have become a preferred medium for collecting self-report and opinion data. Other unobtrusive, nontraditional sources of behavioral observation data are coming into use. Measures of online behavior and databases maintained by corporations and government agencies for other purposes can be a useful source of research data. Concurrent with expanding data availability, analytic capability and processing capacity have improved dramatically. One permutation of this evolution is the recent appearance of computationally intensive methods only recently enabled by spectacular gains in processing speed. These "brute force" computational techniques were often developed to solve highly complex problems in the physical sciences and are now migrating into the toolkit of organizational research. Artificial neural networks constitute one class of these powerful new tools. An artificial neural network (ANN) is a statistical model comprised of simple, interconnected processing elements that are configured through iterative exposure to sample data. The most significant departure of neural network analysis from conventional analysis is that neural model development is relatively unconstrained by researcher expectations compared with the defined parameters of anticipated functional relationships inherent to hypothesis testing. Several themes are in this chapter that are discussed in more detail in later chapters. When one or more of the following conditions are present in a research project, neural network analysis may have value in concert with or even in lieu of conventional multivariate analysis: When sample data show high dimensionality, multiple variable types, and complex interaction effects or do not meet parametric assumptions; When evaluation of alternative models is required; When relationships between independent and dependent variables are weak and unexplained variance is large; When the research application supports or requires the use of data-mining procedures; When the theoretical basis of prediction is ambiguous or poorly understood; When operational use of the predictive model requires high fault tolerance; and When conventional modeling is unnecessary or cannot be completed under operational time constraints." (PsycINFO Database Record (c) 2007 APA, all rights reserved)

Since becoming a wildlife biologist 40 years ago, I have seen many changes. Yet some things have remained the same, like the economic impact of wildlife damage, which was high in 1974 and even higher now. In 2014, the worldwide cost of damage by vertebrate pests to agriculture will exceed $1 billion. The world's human population has increased at an unprecedented rate, while some wildlife populations have also burgeoned over the past 40 years due to land-use changes and effective management programs. These simultaneous human and wildlife population increases have led to increasing conflicts between humans and wildlife. Nor has the international nature of damage changed: vertebrate pest control remains vital for agricultural production everywhere. And some types of wildlife damage are unchanged, such as livestock predation, bird damage to agricultural crops, and rodent damage to crops and stored grains. What has changed over the last 40 years? I see increasing complexity in the types of problems, in the solutions, and in the political landscape under which we work. Damage problems have become more complex, with invasive species being transported around the world, and with zoonotic diseases associated with wildlife becoming more prevalent. Solutions to damage problems have also become more complex, as simpler solutions have already been employed; solutions being sought now are more scientifically difficult and require collaboration by wildlife biologists with an increasing number of other scientific disciplines, such as toxicologists, geneticists, and epidemiologists. And society itself has become more complex, demanding solutions that not only prevent damage, but that are environmentally sound and politically acceptable. What does the future bring? Human population growth will mean more wildlife damage issues. Greater travel and international shipping will bring an increase in invasive species, and global warming will bring an increase in zoonotic diseases. Solutions will need to be innovative and reflect the complexity of the problems.

Non-perennial streams are widespread, critical to ecosystems and society, and the subject of ongoing policy debate. Prior large-scale research on stream intermittency has been based on long-term averages, generally using annually aggregated data to characterize a highly variable process. As a result, it is not well understood if, how, or why the hydrology of non-perennial streams is changing. Here, we investigate trends and drivers of three intermittency signatures that describe the duration, timing, and dry-down period of stream intermittency across the continental United States (CONUS). Half of gages exhibited a significant trend through time in at least one of the three intermittency signatures, and changes in no-flow duration were most pervasive (41% of gages). Changes in intermittency were substantial for many streams, and 7% of gages exhibited changes in annual no-flow duration exceeding 100 days during the study period. Distinct regional patterns of change were evident, with widespread drying in southern CONUS and wetting in northern CONUS. These patterns are correlated with changes in aridity, though drivers of spatiotemporal variability were diverse across the three intermittency signatures. While the no-flow timing and duration were strongly related to climate, dry-down period was most strongly related to watershed land use and physiography. Our results indicate that non-perennial conditions are increasing in prevalence over much of CONUS and binary classifications of 'perennial' and 'non-perennial' are not an accurate reflection of this change. Water management and policy should reflect the changing nature and diverse drivers of changing intermittency both today and in the future. ; US National Science FoundationNational Science Foundation (NSF) [DEB-1754389] ; Published version ; This manuscript is a product of the Dry Rivers Research Coordination Network, which was supported by funding from the US National Science Foundation (DEB-1754389). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. This manuscript was improved by constructive feedback from Kristin Jaeger and three anonymous reviews.

Purpose
This paper aims to further the understanding of Open Government Data (OGD) adoption by the government by invoking two quantum physics theories – percolation theory and expander graph theory.

Design/methodology/approach
Extant research on the barriers to adoption and rollout of OGD is reviewed to drive home the research question for the present study. Both the theories are summarized, and lessons are derived therefrom for answering the research question.

Findings
The percolation theory solves the riddle of why the OGD initiatives find it difficult to seep across the hierarchical and geographical levels of any administrative division. The expander graph theory builds the understanding of the need for having networking among and within the key government personnel for bolstering the motivation and capacity building of the operational personnel linked with the OGD initiative. The theoretical understanding also aids in the implementation and institutionalization of OGD in general.

Originality/value
Intersectionality of domains for conducting research on any theme is always a need. Given the fact that there are innumerable challenges regarding the adoption of OGD by the governments across the world, the application of the two theories of quantum physics might solve the quandary in a befitting way.

The federal government has a longstanding role in conducting education research and collecting education data, and the Department of Education's Institute of Education Services (IES) has a broad mission to provide this information to a wide variety of stakeholders. IES is Education's primary research and evaluation arm. This book examines the extent to which IES has demonstrated its ability to support high-quality research and fulfill its mission, the extent to which selected Education research and technical assistance groups disseminate relevant products to the education field, and how IES co

Summary
From the 1960s, the World Health Organization (WHO) sought to reconcile ambitious international goals with scarce resources and the socio-economic realities of low- and middle-income countries by developing a field called Health Systems Research (HSR). This field remained small, marginal and largely confined to WHO during the second half of the twentieth century. The WHO worked to promote HSR, apply it to concrete problems and define its scope and methodologies while linking it to policymaking. Results were seriously limited by lack of interest from policymakers, confusion about its scope and methods, and competition from numerous disciplines working on overlapping subjects, notably economic analysis. This latter rivalry originated with debates about Primary Health Care versus Selective Primary Healthcare in the late 1970s and was overcome, rhetorically, in the late 1980s. Tensions however remained, and by the end of the twentieth century, economic analysis had temporarily triumphed at the WHO.

Cover -- Half Title -- Title Page -- Copyright Page -- Contents -- Foreword -- Editors -- Contributors -- 1. Introduction -- 2. The theoretical underpinnings of primary care educational research -- 3. Underpinning medical education research with the disciplines of sociology and psychology -- 4. Co-creation and participatory processes in medical education research -- 5. Educational research and policy making -- 6. Scope and research environment -- 7. Integrating primary and secondary care educational research -- 8. Primary care interprofessional educational research -- 9. Research on patient education in primary care -- 10. Finding out what is already known: how to develop a literature review -- 11. Choosing your topic and defining your research question -- 12. Choosing your methodology to answer your question -- 13. Ethical issues for primary care educational research -- 14. Validity and reliability in primary care educational research -- 15. Quantitative study designs -- 16. Big data in primary care educational research -- 17. Social media and the internet in primary care educational research -- 18. Use of the Delphi technique in educational research -- 19. Qualitative methods -- 20. Action research -- 21. Case study research -- 22. Individual interviews and focus groups -- 23. Content analysis: a guide for primary health care education researchers -- 24. Ethnography -- 25. Doing a mixed methods research or evaluation project -- 26. Applying methodologies to the curriculum: researching curriculum development and delivery -- 27. Programme evaluation -- 28. Researching the informal and hidden curriculum -- 29. Mentoring: how to support and mentor early researchers in educational research -- 30. How to develop critical mass and ensure primary care educational innovations and initiatives are evidence-based.

International audience ; Au mois de juillet dernier, les Archives nationales ont adopté un nouveau règlement de réutilisation des « informations publiques » contenues dans les documents faisant partie de leurs collections, qui marque un tournant significatif. L'établissement a en effet choisi de renoncer à sa précédente politique de redevances pour appliquer par défaut un principe de gratuité valable pour les "les documents librement communicables à tous et sur lesquels des tiers ne détiennent pas des droits de propriété intellectuelle".

International audience ; Au mois de juillet dernier, les Archives nationales ont adopté un nouveau règlement de réutilisation des « informations publiques » contenues dans les documents faisant partie de leurs collections, qui marque un tournant significatif. L'établissement a en effet choisi de renoncer à sa précédente politique de redevances pour appliquer par défaut un principe de gratuité valable pour les "les documents librement communicables à tous et sur lesquels des tiers ne détiennent pas des droits de propriété intellectuelle".