Science and Pseudoscience in Medicine: Evidence-Based Vs. Evidence-Biased Medicine
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Jackson: Choosing a Methodology: Philosophical Underpinning
JACKSON: CHOOSING A METHODOLOGY: PHILOSOPHICAL UNDERPINNING Choosing a Methodology: Philosophical Practitioner Research Underpinning In Higher Education Copyright © 2013 University of Cumbria Vol 7 (1) pages 49-62 Elizabeth Jackson University of Cumbria [email protected] Abstract As a university lecturer, I find that a frequent question raised by Masters students concerns the methodology chosen for research and the rationale required in dissertations. This paper unpicks some of the philosophical coherence that can inform choices to be made regarding methodology and a well-thought out rationale that can add to the rigour of a research project. It considers the conceptual framework for research including the ontological and epistemological perspectives that are pertinent in choosing a methodology and subsequently the methods to be used. The discussion is exemplified using a concrete example of a research project in order to contextualise theory within practice. Key words Ontology; epistemology; positionality; relationality; methodology; method. Introduction This paper arises from work with students writing Masters dissertations who frequently express confusion and doubt about how appropriate methodology is chosen for research. It will be argued here that consideration of philosophical underpinning can be crucial for both shaping research design and for explaining approaches taken in order to support credibility of research outcomes. It is beneficial, within the unique context of the research, for the researcher to carefully -
Science Standards
SCIENCE It is the policy of the Oklahoma State Department of Education (OSDE) not to discriminate on the basis of race, color, religion, gender, national origin, age, or disability in its programs or employment practices as required by Title VI and VII of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, and Section 504 of the Rehabilitation Act of 1973. Civil rights compliance inquiries related to the OSDE may be directed to the Affirmative Action Officer, Room 111, 2500 North Lincoln Boulevard, Oklahoma City, Oklahoma 73105-4599, telephone number (405) 522-4930; or, the United States Department of Education’s Assistant Secretary for Civil Rights. Inquires or concerns regarding compliance with Title IX by local school districts should be presented to the local school district Title IX coordinator. This publication, printed by the State Department of Education Printing Services, is issued by the Oklahoma State Department of Education as authorized by 70 O.S. § 3-104. Five hundred copies have been prepared using Title I, Part A, School Improvement funds at a cost of $.15 per copy. Copies have been deposited with the Publications Clearinghouse of the Oklahoma Department of Libraries. DECEMBER 2013. SCIENCE Table of Contents 5-8 Introduction 9 K-5 Overview 10-18 ■ KINDERGARTEN 19-28 ■ 1ST GRADE 29-39 ■ 2ND GRADE 40-54 ■ 3RD GRADE 55-68 ■ 4TH GRADE 69-82 ■ 5TH GRADE 83 6-12 Overview 84-101 ■ 6TH GRADE 102-119 ■ 7TH GRADE 120-137 ■ 8TH GRADE 138-152 ■ PHYSICAL SCIENCE 153-165 ■ CHEMISTRY 166-181 ■ PHYSICS 182-203 ■ BIOLOGY I 204-219 ■ EARTH & SPACE SCIENCE 220-235 ■ ENVIRONMENTAL SCIENCE Introduction Science uses observation and experimentation to explain natural phenomena. -
The Rhetoric of Positivism Versus Interpretivism: a Personal View1
Weber/Editor’s Comments EDITOR’S COMMENTS The Rhetoric of Positivism Versus Interpretivism: A Personal View1 Many years ago I attended a conference on interpretive research in information systems. My goal was to learn more about interpretive research. In my Ph.D. education, I had studied primarily positivist research methods—for example, experiments, surveys, and field studies. I knew little, however, about interpretive methods. I hoped to improve my knowledge of interpretive methods with a view to using them in due course in my research work. A plenary session at the conference was devoted to a panel discussion on improving the acceptance of interpretive methods within the information systems discipline. During the session, a number of speakers criticized positivist research harshly. Many members in the audience also took up the cudgel to denigrate positivist research. If any other positivistic researchers were present at the session beside me, like me they were cowed. None of us dared to rise and speak in defence of positivism. Subsequently, I came to understand better the feelings of frustration and disaffection that many early interpretive researchers in the information systems discipline experienced when they attempted to publish their work. They felt that often their research was evaluated improperly and treated unfairly. They contended that colleagues who lacked knowledge of interpretive research methods controlled most of the journals. As a result, their work was evaluated using criteria attuned to positivism rather than interpretivism. My most-vivid memory of the panel session, however, was my surprise at the way positivism was being characterized by my colleagues in the session. -
Scientific Communities in the Developing World Scientific Communities in the Developing World
Scientific Communities in the Developing World Scientific Communities in the Developing World Edited by jacques Caillard V.V. Krishna Roland Waast Sage Publications New Delhiflhousand Oaks/London Copyright @) Jacques Gaillard, V.V. Krishna and Roland Waast, 1997. All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage or retrieval system, without permission in writing from the publisher. First published in 1997 by Sage Publications India Pvt Ltd M-32, Greater Kailash Market I New Delhi 110 048 Sage Publications Inc Sage Publications Ltd 2455 Teller Road 6 Bonhill Street Thousand Oaks, California 91320 London EC2A 4PU Published by Tejeshwar Singh for Sage Publications India Pvt Ltd, phototypeset by Pagewell Photosetters, Pondicherry and printed at Chaman Enterprises, Delhi. Library of Congress Cataloging-in-Publication Data Scientific communities in the developing world I edited by Jacques Gaillard, V.V. Krishna, Roland Waast. p. cm. Includes bibliographical references and index. 1. Science-Developing countries--History. 2. Science-Social aspect- Developing countries--History. I. Gaillard, Jacques, 1951- . 11. Krishna, V.V. 111. Waast, Roland, 1940- . Q127.2.S44 306.4'5'091724--dc20 1996 9617807 ISBN: 81-7036565-1 (India-hb) &8039-9330-7 (US-hb) Sage Production Editor: Sumitra Srinivasan Contents List of Tables List of Figures Preface 1. Introduction: Scientific Communities in the Developing World Jacques Gaillard, V.V. Krishna and Roland Waast Part 1: Scientific Communities in Africa 2. Sisyphus or the Scientific Communities of Algeria Ali El Kenz and Roland Waast 3. -
There Is No Pure Empirical Reasoning
There Is No Pure Empirical Reasoning 1. Empiricism and the Question of Empirical Reasons Empiricism may be defined as the view there is no a priori justification for any synthetic claim. Critics object that empiricism cannot account for all the kinds of knowledge we seem to possess, such as moral knowledge, metaphysical knowledge, mathematical knowledge, and modal knowledge.1 In some cases, empiricists try to account for these types of knowledge; in other cases, they shrug off the objections, happily concluding, for example, that there is no moral knowledge, or that there is no metaphysical knowledge.2 But empiricism cannot shrug off just any type of knowledge; to be minimally plausible, empiricism must, for example, at least be able to account for paradigm instances of empirical knowledge, including especially scientific knowledge. Empirical knowledge can be divided into three categories: (a) knowledge by direct observation; (b) knowledge that is deductively inferred from observations; and (c) knowledge that is non-deductively inferred from observations, including knowledge arrived at by induction and inference to the best explanation. Category (c) includes all scientific knowledge. This category is of particular import to empiricists, many of whom take scientific knowledge as a sort of paradigm for knowledge in general; indeed, this forms a central source of motivation for empiricism.3 Thus, if there is any kind of knowledge that empiricists need to be able to account for, it is knowledge of type (c). I use the term “empirical reasoning” to refer to the reasoning involved in acquiring this type of knowledge – that is, to any instance of reasoning in which (i) the premises are justified directly by observation, (ii) the reasoning is non- deductive, and (iii) the reasoning provides adequate justification for the conclusion. -
A Comprehensive Framework to Reinforce Evidence Synthesis Features in Cloud-Based Systematic Review Tools
applied sciences Article A Comprehensive Framework to Reinforce Evidence Synthesis Features in Cloud-Based Systematic Review Tools Tatiana Person 1,* , Iván Ruiz-Rube 1 , José Miguel Mota 1 , Manuel Jesús Cobo 1 , Alexey Tselykh 2 and Juan Manuel Dodero 1 1 Department of Informatics Engineering, University of Cadiz, 11519 Puerto Real, Spain; [email protected] (I.R.-R.); [email protected] (J.M.M.); [email protected] (M.J.C.); [email protected] (J.M.D.) 2 Department of Information and Analytical Security Systems, Institute of Computer Technologies and Information Security, Southern Federal University, 347922 Taganrog, Russia; [email protected] * Correspondence: [email protected] Abstract: Systematic reviews are powerful methods used to determine the state-of-the-art in a given field from existing studies and literature. They are critical but time-consuming in research and decision making for various disciplines. When conducting a review, a large volume of data is usually generated from relevant studies. Computer-based tools are often used to manage such data and to support the systematic review process. This paper describes a comprehensive analysis to gather the required features of a systematic review tool, in order to support the complete evidence synthesis process. We propose a framework, elaborated by consulting experts in different knowledge areas, to evaluate significant features and thus reinforce existing tool capabilities. The framework will be used to enhance the currently available functionality of CloudSERA, a cloud-based systematic review Citation: Person, T.; Ruiz-Rube, I.; Mota, J.M.; Cobo, M.J.; Tselykh, A.; tool focused on Computer Science, to implement evidence-based systematic review processes in Dodero, J.M. -
Mothers in Science
The aim of this book is to illustrate, graphically, that it is perfectly possible to combine a successful and fulfilling career in research science with motherhood, and that there are no rules about how to do this. On each page you will find a timeline showing on one side, the career path of a research group leader in academic science, and on the other side, important events in her family life. Each contributor has also provided a brief text about their research and about how they have combined their career and family commitments. This project was funded by a Rosalind Franklin Award from the Royal Society 1 Foreword It is well known that women are under-represented in careers in These rules are part of a much wider mythology among scientists of science. In academia, considerable attention has been focused on the both genders at the PhD and post-doctoral stages in their careers. paucity of women at lecturer level, and the even more lamentable The myths bubble up from the combination of two aspects of the state of affairs at more senior levels. The academic career path has academic science environment. First, a quick look at the numbers a long apprenticeship. Typically there is an undergraduate degree, immediately shows that there are far fewer lectureship positions followed by a PhD, then some post-doctoral research contracts and than qualified candidates to fill them. Second, the mentors of early research fellowships, and then finally a more stable lectureship or career researchers are academic scientists who have successfully permanent research leader position, with promotion on up the made the transition to lectureships and beyond. -
The Law and the Brain: Judging Scientific Evidence of Intent
The Journal of Appellate Practice and Process Volume 1 Issue 2 Article 4 1999 The Law and the Brain: Judging Scientific videnceE of Intent Erica Beecher-Monas Edgar Garcia-Rill Follow this and additional works at: https://lawrepository.ualr.edu/appellatepracticeprocess Part of the Evidence Commons, Jurisprudence Commons, and the Science and Technology Law Commons Recommended Citation Erica Beecher-Monas and Edgar Garcia-Rill, The Law and the Brain: Judging Scientific videnceE of Intent, 1 J. APP. PRAC. & PROCESS 243 (1999). Available at: https://lawrepository.ualr.edu/appellatepracticeprocess/vol1/iss2/4 This document is brought to you for free and open access by Bowen Law Repository: Scholarship & Archives. It has been accepted for inclusion in The Journal of Appellate Practice and Process by an authorized administrator of Bowen Law Repository: Scholarship & Archives. For more information, please contact [email protected]. THE LAW AND THE BRAIN: JUDGING SCIENTIFIC EVIDENCE OF INTENT Erica Beecher-Monas* and Edgar Garcia-Rill, Ph.D.** INTRODUCTION As evidentiary gatekeepers, judges must be ready to evaluate expert testimony about science and the brain. A wide variety of cases present issues of mental state, many doubtless with battling experts seeking to testify on these issues. This poses a dilemma for nonspecialist judges. How is a nonscientist to judge scientific evidence? How can a nonscientist decide if testimony about mental state meets the criteria of good science? This essay offers a general overview of the issue of evaluating scientific evidence and is aimed at exploring the issues involved, but not attempting easy answers. Of necessity, this requires thinking about how science works. -
Urban Myths Mythical Cryptids
Ziptales Advanced Library Worksheet 2 Urban Myths Mythical Cryptids ‘What is a myth? It is a story that pretends to be real, but is in fact unbelievable. Like many urban myths it has been passed around (usually by word of mouth), acquiring variations and embellishments as it goes. It is a close cousin of the tall tale. There are mythical stories about almost any aspect of life’. What do we get when urban myths meet the animal kingdom? We find a branch of pseudoscience called cryptozoology. Cryptozoology refers to the study of and search for creatures whose existence has not been proven. These creatures (or crytpids as they are known) appear in myths and legends or alleged sightings. Some examples include: sea serpents, phantom cats, unicorns, bunyips, giant anacondas, yowies and thunderbirds. Some have even been given actual names you may have heard of – do Yeti, Owlman, Mothman, Cyclops, Bigfoot and the Loch Ness Monster sound familiar? Task 1: Choose one of the cryptids from the list above (or perhaps one that you may already know of) and write an informative text identifying the following aspects of this mythical creature: ◊ Description ◊ Features ◊ Location ◊ First Sighting ◊ Subsequent Sightings ◊ Interesting Facts (e.g. how is it used in popular culture? Has it been featured in written or visual texts?) Task 2: Cryptozoologists claim there have been cases where species now accepted by the scientific community were initially considered urban myths. Can you locate any examples of creatures whose existence has now been proven but formerly thought to be cryptids? Extension Activities: • Cryptozoology is called a ‘pseudoscience’ because it relies solely on anecdotes and reported sightings rather than actual evidence. -
The Role of Social Context in the Production of Scientific Knowledge
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Supervised Undergraduate Student Research Chancellor’s Honors Program Projects and Creative Work 5-2015 The Role of Social Context in the Production of Scientific Knowledge Kristen Lynn Beard [email protected] Follow this and additional works at: https://trace.tennessee.edu/utk_chanhonoproj Part of the Philosophy of Science Commons Recommended Citation Beard, Kristen Lynn, "The Role of Social Context in the Production of Scientific nowledgeK " (2015). Chancellor’s Honors Program Projects. https://trace.tennessee.edu/utk_chanhonoproj/1852 This Dissertation/Thesis is brought to you for free and open access by the Supervised Undergraduate Student Research and Creative Work at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Chancellor’s Honors Program Projects by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. The Role of Social Context in the Production of Scientific Knowledge Kristen Lynn Beard The University of Tennessee, Knoxville Chancellor’s Honors Program Department of Philosophy Undergraduate Thesis Submitted December 8, 2014 Thesis Advisor: Dr. Nora Berenstain Beard 1 Model 1: The Influence of Social Context on the Scientific Method Beard 2 Introduction: Scientific Knowledge as Both Social and Rational A person may believe that a certain theory is true and explain that he does so, for instance, because it is the best explanation he has of the facts or because it gives him the most satisfying world picture. This does not make him irrational, but I take it to be part of empiricism to disdain such reasons. -
Bringing Science and Scientists to Life in Post-Secondary Science Education
Sci & Educ DOI 10.1007/s11191-010-9310-7 The Story Behind the Science: Bringing Science and Scientists to Life in Post-Secondary Science Education Michael P. Clough Ó Springer Science+Business Media B.V. 2010 Abstract With funding from the United States National Science Foundation, 30 histor- ical short stories designed to teach science content and draw students’ attention to the nature of science (NOS) have been created for post-secondary introductory astronomy, biology, chemistry, geology, and physics courses. The project rationale, story development and structure, and freely available stories at the project website are presented. 1 Introduction The phrase ‘‘nature of science’’ (NOS) has been used for some time, particularly in the science education community, in referring to what science is, how science works, the epistemological and ontological foundations underlying science, the culture of science, and how society both influences and reacts to scientific activities (Clough 2006). Accurately understanding the NOS is crucial for science literacy (AAAS 1989; Matthews 1994; McComas and Olson 1998; NRC 1996) and can perhaps play an important role in enticing students to further their science education. Matthews (1994), McComas et al. (1998) and others have argued that knowledge of scientists and how science works will enhance students’ understanding of science as a human endeavor; increase interest in science and science classes; improve student learning of science content; and promote better social decision-making. Morris Shamos (1995) claimed that understanding the NOS is the most important component of scientific literacy because that knowledge, accurate or not, is what citizens use when assessing public issues involving science and technology. -
How Science Works
PB 1 How science works The Scientific Method is traditionally presented in the first chapter of science text- books as a simple recipe for performing scientific investigations. Though many use- ful points are embodied in this method, it can easily be misinterpreted as linear and “cookbook”: pull a problem off the shelf, throw in an observation, mix in a few ques- tions, sprinkle on a hypothesis, put the whole mixture into a 350° experiment—and voila, 50 minutes later you’ll be pulling a conclusion out of the oven! That might work if science were like Hamburger Helper®, but science is complex and cannot be re- duced to a single, prepackaged recipe. The linear, stepwise representation of the process of science is simplified, but it does get at least one thing right. It captures the core logic of science: testing ideas with evidence. However, this version of the scientific method is so simplified and rigid that it fails to accurately portray how real science works. It more accurately describes how science is summarized after the fact—in textbooks and journal articles—than how sci- ence is actually done. The simplified, linear scientific method implies that scientific studies follow an unvarying, linear recipe. But in reality, in their work, scientists engage in many different activities in many different sequences. Scientific investigations often involve repeating the same steps many times to account for new information and ideas. The simplified, linear scientific method implies that science is done by individual scientists working through these steps in isolation. But in reality, science depends on interactions within the scientific community.