Institution
Queensland University of Technology
Education•Brisbane, Queensland, Australia•
About: Queensland University of Technology is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 14188 authors who have published 55022 publications receiving 1496237 citations. The organization is also known as: QUT.
Topics: Population, Poison control, Raman spectroscopy, Health care, Curriculum
Papers published on a yearly basis
Papers
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TL;DR: In this article, the role of schooling and its contribution to the successful resettlement of refugee children is investigated. And the authors discuss how educational institutions might play a more active role in facilitating transitions to citizenship for refugee youth through an inclusive approach.
Abstract: The worldwide rise in numbers of refugees and asylum seekers suggests the need to examine the practices of those institutions charged with their resettlement in host countries. In this paper, we investigate the role of one important institution – schooling – and its contribution to the successful resettlement of refugee children. We begin with an examination of forced migration and its links with globalisation, and the barriers to inclusion confronting refugees. A discussion of the educational challenges confronting individual refugee youth and schools is followed by case studies of four schools and the approaches they had developed to meet the needs of young people from a refugee background. Using our findings and other research, we outline a model of good practice in refugee education. We conclude by discussing how educational institutions might play a more active role in facilitating transitions to citizenship for refugee youth through an inclusive approach.
354 citations
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TL;DR: In this article, the authors proposed two new methods for conditional distribution estimation based on locally fitting a logistic model and an adjusted form of the Nadaraya-Watson estimator.
Abstract: Motivated by the problem of setting prediction intervals in time series analysis, we suggest two new methods for conditional distribution estimation. The first method is based on locally fitting a logistic model and is in the spirit of recent work on locally parametric techniques in density estimation. It produces distribution estimators that may be of arbitrarily high order but nevertheless always lie between 0 and 1. The second method involves an adjusted form of the Nadaraya–Watson estimator. It preserves the bias and variance properties of a class of second-order estimators introduced by Yu and Jones but has the added advantage of always being a distribution itself. Our methods also have application outside the time series setting; for example, to quantile estimation for independent data. This problem motivated the work of Yu and Jones.
354 citations
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TL;DR: A systematic and overarching review of different spatial and temporal factors affecting the UHI effect is provided and discusses the findings in policy terms and provides directions for future research.
353 citations
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University of California, Santa Cruz1, Queensland University of Technology2, Stockholm Environment Institute3, University of Potsdam4, Woodrow Wilson International Center for Scholars5, North Carolina Museum of Natural Sciences6, American Museum of Natural History7, Northern Arizona University8, Catholic University of the North9, University College London10, Federal University of Campina Grande11, Trinity College, Dublin12, University of California, Davis13, University of Natural Resources and Life Sciences, Vienna14, Allegheny College15, Wageningen University and Research Centre16
TL;DR: The authors reviewed the theoretical, historical, geopolitical, and disciplinary context of citizen science terminology and provided a collection of potential terms and definitions for "citizen science" and people participating in citizen science projects.
Abstract: Much can be at stake depending on the choice of words used to describe citizen science, because terminology impacts how knowledge is developed. Citizen science is a quickly evolving field that is mobilizing people’s involvement in information development, social action and justice, and large-scale information gathering. Currently, a wide variety of terms and expressions are being used to refer to the concept of ‘citizen science’ and its practitioners. Here, we explore these terms to help provide guidance for the future growth of this field. We do this by reviewing the theoretical, historical, geopolitical, and disciplinary context of citizen science terminology; discussing what citizen science is and reviewing related terms; and providing a collection of potential terms and definitions for ‘citizen science’ and people participating in citizen science projects. This collection of terms was generated primarily from the broad knowledge base and on-the-ground experience of the authors, by recognizing the potential issues associated with various terms. While our examples may not be systematic or exhaustive, they are intended to be suggestive and invitational of future consideration. In our collective experience with citizen science projects, no single term is appropriate for all contexts. In a given citizen science project, we suggest that terms should be chosen carefully and their usage explained; direct communication with participants about how terminology affects them and what they would prefer to be called also should occur. We further recommend that a more systematic study of terminology trends in citizen science be conducted.
353 citations
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TL;DR: In this paper, the authors evaluate the role of selectivity as a potential explanation for the existence of the healthy immigrant effect across source and destination countries using a set of consistently defined measures of health, and find that selectivity plays an important role in the observed better health of migrants vis a vis those who stay behind in their country of origin.
Abstract: The existence of a healthy immigrant effect—where immigrants are on average healthier than the native born—is a widely cited phenomenon across a multitude of literatures including epidemiology and the social sciences. There are many competing explanations. The goals of this paper are twofold: first, to provide further evidence on the presence of the healthy immigrant effect across source and destination country using a set of consistently defined measures of health; and second, to evaluate the role of selectivity as a potential explanation for the existence of the phenomenon. Utilizing data from four major immigrant recipient countries, USA, Canada, UK, and Australia allows us to compare the health of migrants from each with the respective native born who choose not to migrate. This represents a much more appropriate counterfactual than the native born of the immigrant recipient country and yields new insights into the importance of observable selection effects. The analysis finds strong support for the healthy immigrant effect across all four destination countries and that selectivity plays an important role in the observed better health of migrants vis a vis those who stay behind in their country of origin.
352 citations
Authors
Showing all 14597 results
Name | H-index | Papers | Citations |
---|---|---|---|
Nicholas G. Martin | 192 | 1770 | 161952 |
Paul M. Thompson | 183 | 2271 | 146736 |
Christopher J. O'Donnell | 159 | 869 | 126278 |
Robert G. Parton | 136 | 459 | 59737 |
Tim J Cole | 136 | 827 | 92998 |
Daniel I. Chasman | 134 | 484 | 72180 |
David Smith | 129 | 2184 | 100917 |
Dmitri Golberg | 129 | 1024 | 61788 |
Chao Zhang | 127 | 3119 | 84711 |
Shi Xue Dou | 122 | 2028 | 74031 |
Thomas H. Marwick | 121 | 1063 | 58763 |
Peter J. Anderson | 120 | 966 | 63635 |
Bruno S. Frey | 119 | 900 | 65368 |
David M. Evans | 116 | 632 | 74420 |
Michael Pollak | 114 | 663 | 57793 |