Quantifying Research Integrity

Quantifying Research Integrity

Morgan & Claypool | English | 2017 | ISBN-10: 1627056408 | 121 Pages | PDF | 677 kb
by Michael Seadle Dr (Author)

Institutions typically treat research integrity violations as black and white, right or wrong. The result is that the wide range of grayscale nuances that separate accident, carelessness and bad practice from deliberate fraud and malpractice often get lost. This lecture looks at how to quantify the grayscale range in three kinds of research integrity violations: plagiarism, data falsification, and image manipulation.

Quantification works best with plagiarism, because the essential one-to one matching algorithms are well known and established tools for detecting when matches exist. Questions remain, however, how many matching words of what kind in what location in which discipline constitute reasonable suspicion of fraudulent intent. Different disciplines take different perspectives on quantity and location. Quantification is harder with data falsification, because the original data are often not available, and because experimental replication remains surprisingly difficult. The same is true with image manipulation, where tools exist for detecting certain kinds of manipulations, but where the tools are also easily defeated.

This lecture looks at how to prevent violations of research integrity from a pragmatic viewpoint, and at what steps can institutions and publishers take to discourage problems beyond the usual ethical admonitions. There are no simple answers, but two measures can help: the systematic use of detection tools and requiring original data and images. These alone do not suffice, but they represent a start.

The scholarly community needs a better awareness of the complexity of research integrity decisions. Only an open and wide-spread international discussion can bring about a consensus on where the boundary lines are and when grayscale problems shade into black. One goal of this work is to move that discussion forward.

Download:

http://longfiles.com/4s6hms03lm9i/Quantifying_Research_Integrity.pdf.html

[Fast Download] Quantifying Research Integrity


Ebooks related to "Quantifying Research Integrity" :
Beginning Build and Release Management with TFS 2017 and VSTS: Leveraging Continuous Delivery for Yo
Metaprogramming in R: Advanced Statistical Programming for Data Science, Analysis and Finance
SQL By Example: Learn how to create and query databases in eight easy lessons!
A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years
Regression Analysis with Python
Exploring Data with RapidMiner
SQL Server 2005 Reporting Services in Action
Cody's Data Cleaning Techniques Using SAS, Second Edition
Data Modeling Fundamentals Jul 2007 eBook-BBL
Pro ASP.NET for SQL Server: High Performance Data Access for Web Developers
Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.