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Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309486165
Category : Science
Languages : en
Pages : 257
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Book Description
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309486165
Category : Science
Languages : en
Pages : 257
Get Book Here
Book Description
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 030948619X
Category : Science
Languages : en
Pages : 257
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Book Description
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
Author: Engineering National Academies of Sciences
Publisher:
ISBN: 9780309486170
Category : Reproducible research
Languages : en
Pages : 234
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Book Description
"One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science"--Publisher's description
Author: R. Barker Bausell
Publisher: Oxford University Press
ISBN: 0197536549
Category : Psychology
Languages : en
Pages : 297
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Book Description
Recent events have vividly underscored the societal importance of science, yet the majority of the public are unaware that a large proportion of published scientific results are simply wrong. The Problem with Science is an exploration of the manifestations and causes of this scientific crisis, accompanied by a description of the very promising corrective initiatives largely developed over the past decade to stem the spate of irreproducible results that have come to characterize many of our sciences. More importantly, Dr. R. Barker Bausell has designed it to provide guidance to practicing and aspiring scientists regarding how (a) to change the way in which science has come to be both conducted and reported in order to avoid producing false positive, irreproducible results in their own work and (b) to change those institutional practices (primarily but not exclusively involving the traditional journal publishing process and the academic reward system) that have unwittingly contributed to the present crisis. There is a need for change in the scientific culture itself. A culture which prioritizes conducting research correctly in order to get things right rather than simply getting it published.
Author: Jakub Bijak
Publisher: Springer Nature
ISBN: 303083039X
Category : Social Science
Languages : en
Pages : 277
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Book Description
This open access book presents a ground-breaking approach to developing micro-foundations for demography and migration studies. It offers a unique and novel methodology for creating empirically grounded agent-based models of international migration – one of the most uncertain population processes and a top-priority policy area. The book discusses in detail the process of building a simulation model of migration, based on a population of intelligent, cognitive agents, their networks and institutions, all interacting with one another. The proposed model-based approach integrates behavioural and social theory with formal modelling, by embedding the interdisciplinary modelling process within a wider inductive framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based simulations, and to learn about modelling the simulated individuals and the way they make decisions. The identified knowledge gaps are subsequently filled with information from dedicated laboratory experiments on cognitive aspects of human decision-making under uncertainty. In this way, the models are built iteratively, from the bottom up, filling an important epistemological gap in migration studies, and social sciences more broadly.
Author: National Research Council
Publisher: National Academies Press
ISBN: 030921954X
Category : Science
Languages : en
Pages : 42
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Book Description
The publication of research articles involving animal studies is central to many disciplines in science and biomedicine. Effective descriptions in such publications enable researchers to interpret the data, evaluate and replicate findings, and move the science forward. Analyses of published studies with research animals have demonstrated numerous deficiencies in the reporting of details in research methods for animal studies. Considerable variation in the amount of information required by scientific publications and reported by authors undermines this basic scientific principle and results in the unnecessary use of animals and other resources in failed efforts to reproduce study results. Guidance for the Description of Animal Research in Scientific Publications outlines the information that should be included in scientific papers regarding the animal studies to ensure that the study can be replicated. The report urges journal editors to actively promote effective and ethical research by encouraging the provision of sufficient information. Examples of this information include: conditions of housing and husbandry, genetic nomenclature, microbial status, detailed experimental manipulations, and handling and use of pharmaceuticals. Inclusion of this information will enable assessment and interpretation of research findings and advancement of knowledge based on reproducible results.
Author: Victoria Stodden
Publisher: CRC Press
ISBN: 1466561599
Category : Mathematics
Languages : en
Pages : 450
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Book Description
In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.
Author: James Mattingly
Publisher: University of Chicago Press
ISBN: 022680478X
Category : Philosophy
Languages : en
Pages : 373
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Book Description
An ambitious new model of experimentation that will reorient our understanding of the key features of experimental practice. What is experimental knowledge, and how do we get it? While there is general agreement that experiment is a crucial source of scientific knowledge, how experiment generates that knowledge is far more contentious. In this book, philosopher of science James Mattingly explains how experiments function. Specifically, he discusses what it is about experimental practice that transforms observations of what may be very localized, particular, isolated systems into what may be global, general, integrated empirical knowledge. Mattingly argues that the purpose of experimentation is the same as the purpose of any other knowledge-generating enterprise—to change the state of information of the knower. This trivial-seeming point has a non-trivial consequence: to understand a knowledge-generating enterprise, we should follow the flow of information. Therefore, the account of experimental knowledge Mattingly provides is based on understanding how information flows in experiments: what facilitates that flow, what hinders it, and what characteristics allow it to flow from system to system, into the heads of researchers, and finally into our store of scientific knowledge.
Author: Craig A. Hill
Publisher: John Wiley & Sons
ISBN: 1118976320
Category : Social Science
Languages : en
Pages : 784
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Book Description
Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.
Author: Colin Elman
Publisher: Cambridge University Press
ISBN: 1108486770
Category : Language Arts & Disciplines
Languages : en
Pages : 569
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Book Description
A wide-ranging discussion of factors that impede the cumulation of knowledge in the social sciences, including problems of transparency, replication, and reliability. Rather than focusing on individual studies or methods, this book examines how collective institutions and practices have (often unintended) impacts on the production of knowledge.
