An Introduction to Scientific Research Methods in Geography and Environmental Studies

Daniel Montello, Paul Sutton

• Publisher: SAGE Publications Ltd
• Year: 2012
• Print ISBN: 9781446200759, 9781446200742
• eBook ISBN: 9781446291214
• Edition: 2
• Topic: Physical Sciences

"Covers a broad range of subjects that undergraduates in the discipline should be familiar and comfortable with upon graduation. From chapters on the scientific method and fundamental research concepts, to experimental design, sampling and statistical analysis, the text offers an excellent introduction to the key concepts of geographical research. The content is applicable for students at the beginning of their studies right through to planning and conducting dissertations. The book has also been of particular support in designing my level 1 and 2 tutorials which cover similar ground to several of the chapters."
- Joseph Mallalieu, School of Geography, Leeds University

"Montello and Sutton is one of the best texts I?ve used in seminars on research methodology. The text offers a clear balance of quantitative vs. qualitative and physical vs. human which I?ve found particularly valuable. The chapters on research ethics, scientific communication, information technologies and data visualization are excellent."
- Kenneth E. Foote, Department of Geography, University of Colorado at Boulder

This is a broad and integrative introduction to the conduct and interpretation of scientific research, covering both geography and environmental studies. Written for undergraduate and postgraduate students, it:

• Explains both the conceptual and the technical aspects of research, as well as all phases of the research process
• Combines approaches in physical geography and environmental science, human geography and human-environment relations, and geographic and environmental information techniques (such as GIS, cartography, and remote sensing)
• Combines natural and social scientific approaches common to subjects in geography and environmental studies
• Includes case studies of actual research projects to demonstrate the breadth of approaches taken

It will be core reading for students studying scientific research methods in geography, environmental studies and related disciplines such as planning and earth science.

1

INTRODUCTION: A SCIENTIFIC APPROACH TO GEOGRAPHY AND ENVIRONMENTAL STUDIES

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LEARNING OBJECTIVES

• What is a scientific approach to geography and environmental studies?
• How is science both an individual and a social activity?
• What are several metaphysical beliefs characteristically held by scientists?
• What are four goals of scientific activity?
• What are the relationships of natural science, social science, and the humanities to the disciplines of geography and environmental studies, currently and throughout their history?

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John was pursuing his Master’s degree in a department of geography and environmental studies.¹ He was interested in geographical and environmental factors that contribute to causing social ills, such as violent crime, in inner cities. Having read some of the literature on this subject, John had discovered the concepts of “associative” and “dissociative” institutions. The first are thought to create community identity and social cohesion – churches might be an example. The second are thought to destroy community identity and social cohesion – crack houses might be an example. John theorized that “social decay in the inner city is caused by a prevalence of dissociative, rather than associative, institutions.” To test his theory, John looked at the city of Milwaukee (it was convenient for him). He got data from the police department on the number of suicides and homicides that had occurred in the previous ten years in Milwaukee. He also looked in the phone book Yellow Pages for the Milwaukee Metropolitan Area, which includes suburbs and peripheral areas as well as the urban core of Milwaukee. From the phone book, John counted the number of liquor stores, noting their addresses. He then organized his data into census tract units; census tracts were created by the U.S. Census Bureau, and include regions in cities at about the size of neighborhoods where about 3,000 to 8,000 people reside. Each census tract was thus assigned two numbers, the number of “wrongful deaths” and the number of liquor stores. John calculated a Pearson correlation coefficient on these two variables, a statistical index that identifies linear patterns of relationships between two metric-level variables. He found a positive correlation of .31, which suggests that census tracts with more liquor stores in his data set were somewhat more likely to have more wrongful deaths, at least within the previous ten years. John concluded that he had proven that dissociative institutions cause social decay in inner cities, and he recommended getting rid of liquor stores in inner-city areas.

Should we accept John’s conclusions and agree with his recommendation? Probably not. There are numerous problems with the way his study was conceived, conducted, and interpreted. For instance, the Yellow Pages lists most businesses but not all. Why only look at liquor stores and not bars? In Wisconsin (Milwaukee’s state), alcohol is often purchased in grocery stores and small markets. Shouldn’t John have looked at other potentially dissociative institutions, like adult clubs, gambling parlors, or criminal organizations? His theory is about the presence of dissociative institutions relative to associative institutions, but he didn’t even look at associative institutions. What about other indicators of social ills besides murder and suicide, like assault? Are there other factors that we might expect to be related to the incidence of murder and suicide that vary considerably across census tracts in Milwaukee? Potential candidates are socioeconomic status (SES), age, residential density and housing style, housing tenure (ownership status), ethnic makeup, citizenship, and immigration history. John used census tracts as the unit of analysis because of convenience, but are census tracts the proper unit of analysis for the concepts that interested him? And why Milwaukee in the first place? Are there any special characteristics of Milwaukee that makes it less representative of cities, including inner cities?

Our story about John’s research and its faults and limitations provides a concrete introduction to the topic of this book: scientific research methods. Scientific research methods (or methodologies) are the suite of techniques and procedures for empirical scientific investigation, along with the logic and conceptual foundations that tie scientific investigations together, and connect them with substantive theory. The topic of research methods clearly touches on many issues important to researchers in all natural- and social-science disciplines, including geography and environmental studies. Research methods concern which problem domains are studied; which specific ideas within the domain are investigated; what entities are studied; what is observed or measured about the entities; how they are observed; where, when, and how many observations are collected; how the observations are analyzed (including graphing, mapping, statistical analysis, or simple tallying); what patterns are in the observations and whether the patterns can be generalized to some larger population of entities, times, or places; what explains the patterns in the observations; and even what the observations say, if anything, about solving practical problems. This is an impressive list. What’s more, all of these issues are potentially relevant not only to how we carry out our own research but to how we interpret research carried out by others. The study of research methods is thus central to deciding what conclusions we can draw about the meaning of research, the contexts in which these conclusions hold, and the degree of confidence we have in these conclusions. In other words, you cannot competently carry out or critique scientific research without considerable knowledge of methods.

OVERVIEW OF THE LOGIC AND PHILOSOPHY OF SCIENCE

Let’s consider what makes an activity scientific research. What is a scientific approach? There is no precise answer to this question. Like art or cheeseburgers (does it count when the “meat” is soy protein?), science is a somewhat vague concept that includes clear central examples but also many examples that most people would agree are more-or-less scientific, rather than clearly and definitely examples of science or not. That said, we can start with this simple and fairly inclusive definition: Science is a personal and social human endeavor in which ideas and empirical evidence are logically applied to create and evaluate knowledge about reality. Let’s consider a few components of this definition. Science is a personal and social human endeavor because it is something humans do, as individuals and as social groups. Individual scientists learn from other scientists, work with colleagues and assistants, and act within various cultural and institutional contexts. Empirical² evidence is derived from systematic observation of the world via the senses, often aided by technology. The systematic nature of scientific empiricism crucially distinguishes it from the observations we all make informally every day. Because science aims for stable and publicly consensual truth, scientific empiricism strives to be repeatable, accumulable, and publicly observable. A necessary reliance on systematic empirical evaluation of the world is, to a large extent, the hallmark of scientific activity, as opposed to some other human enterprises that strive to understand the world (more on this below). It helps differentiate science from intuition, authority, anecdote, profitability, physical or political power, spiritual transcendence, the need for happy endings, and other approaches and motivations. Ideally, ideas and evidence are applied according to certain formal and informal logical principles in science. It is not possible to give a finite and complete list of these principles, but they certainly include such things as: (1) contradictions must be avoided; (2) our confidence in a phenomenon increases as our observations of it increase; and (3) past regularities will probably recur in the future.

The relationship in science between ideas and evidence deserves further comment. Ideas are used to design studies – units of focused observation or data collection – and to interpret their results. Scientists explain patterns in their empirical observations by reference to ideas about reality. But scientists also understand that any empirical observations can potentially be explained not just by ideas about reality but also by ideas about the way the observations were obtained or interpreted. That is, scientists consider that a pattern of observations may reflect such empirical factors as biased instruments, idiosyncratic testing environments, unusual samples, and so on – not just the phenomenon being studied. In our introductory example, John failed to think scientifically when he interpret his data only to reflect truth about the phenomena of dissociative institutions, community identity, and social cohesion, and did not consider limitations in his approach to conceptualizing and measuring these phenomena.

Notice that our definition does not restrict science to just the physical or biological world. Science is also concerned with the world of human activity, artifact, and institution. There are natural (biophysical) sciences and social (human) sciences. This is especially important to recognize in disciplines as broad as geography and environmental studies, which both involve both biophysical and human sciences; as we discuss below, they also involve humanities, arts, engineering, and craft as well. As the Preface in this and the previous edition explain, this text deals with scientific methodology for all of geography and environmental studies, including the biophysical and human domains. Therefore, we always use the generic term “science” inclusively in this text to mean both natural and social sciences.

Our definition also avoids claiming that science restricts itself to one specific approach to logic. The history of debates about the proper way to do science includes numerous claims that, for instance, “real” science applies hypothetico-deductive reasoning, in which prior hypotheses are used to deduce observational consequences that can then be compared to empirical evidence. Others have claimed that science is inductive in nature, relying on initial observations to generate hypotheses about reality.³ But scientists use both deductive and inductive approaches⁴; we find it misleading to claim that one is generally more common or appropriate than the other. In fact, while our definition of science highlights logical thinking, it makes no claim that scientists think exclusively in a logical manner. Like artists and other nonscientists, scientists gain insights and create new ideas in any number of different ways that would not be considered strictly logical, including intuition, fantasy, inspiration, and the like (we discuss these further in Chapter 2 when we discuss generating research ideas). Clearly, scientists often come to understand a phenomenon through a process of insight, an inferential process that seems to leap from observations to explanatory conclusions with no conscious systematic reasoning plan. This form of reasoning is sometimes called abductive.

Finally, while our definition points out that science includes both an idea part and an empirical part, it does not claim that every individual scientist or laboratory must engage in both parts equally. While a science such as physics has become so specialized that some physicists describe themselves as “theoretical” and others as “empirical,” all physicists recognize that the full activity of physics includes both theory and empirical observation. For example, Albert Einstein’s theories of relativity in the early twentieth century made sense (at least to some people) logically and mathematically, but achieved much more acceptance over the ensuing decades as other scientists were able to generate empirical evidence for them, much of it after Einstein’s death. Scientists believe that empirical observations are produced in order to evaluate and generate ideas about reality, and they believe that the ultimate truth of ideas about reality needs to be empirically evaluated by someone, eventually. Looked at another way, ideas about reality suggest studies to conduct and ways to explain the observations that result from those studies. The “theoretical” scientist may not collect and analyze empirical observations, but he or she believes it is important that someone does. In other words, as we stated above, the dual components of science describe a social activity, not just an individual enterprise.

Characteristic Metaphysical Beliefs of Scientists

In addition to our short definition of science, we believe it is useful to identify a set of characteristic metaphysical beliefs or intellectual preferences held by most scientists. As we said above, it is probably impossible for anyone to give a strict definition of the scientific enterprise that everyone would agree actually succeeds at including all instances of scientific activity (past, present, future) while excluding all activities that are not scientific. Delimiting the meaning of a concept like science depends on the nature of human conceptualization and social relations (including financial and political relations), not just the actual reality to which the concept refers. Furthermore, the human activity called science has evolved over the centuries (if not longer) in a somewhat haphazard way – it was not defined and implemented by an overarching “creator of science.” Thus, over time fairly different activities have been considered better or worse examples of scientific activity. However, we believe that characteristic beliefs can be identified that help us understand what is more scientific than not, and when someone probably is or is not doing science. These are metaphysical because they concern beliefs about the ultimate nature of reality (ontology) and how scientists can know about it (epistemology). We think these beliefs are held by a majority of practicing scientists but don’t consider them essential to the definition of science. For example, we would not claim that a person who does not believe in the existence of a world independent of sentient minds could not be doing scientific research, but we do believe that such a scientist is rare. We also call these beliefs “preferences” because they are just that – personal or cultural preferences or intuitions. They have not been proven, nor are they likely to be provable, to be the best possible avenues to truth; that is, they are elements of faith!

1. Realist philosophy. Nearly all scientists at least implicitly accept a philosophy of realism. They believe the universe actually exists, independently of sentient (thinking, feeling) beings, as matter and energy patterned in space and time. The matter and energy coheres into meaningful pieces (entities and events) but is also organized into meaningful pieces by sentient beings, like us humans.
2. Only continuously connected and forward causality. This might be thought of as an extension of the belief in realism, but we find it valuable to note it separately. Scientis...

Table of contents

• Cover Page
• Title Page
• Copyright
• Dedication
• Contents
• About the author
• Preface
• Acknowledgement
• 1 Introduction: A Scientific Approach to Geography and Environmental Studies
• 2 Fundamental Research Concepts
• 3 Scientific Communication
• 4 Data Collection in Geography and Environmental Studies: Overview
• 5 Physical Measurements
• 6 Behavioral Observations and Archives
• 7 Explicit Reports: Surveys, Interviews, and Tests
• 8 Experimental and Nonexperimental Research Designs
• 9 Sampling
• 10 Statistical Data Analysis
• 11 Data Display: Tables, Graphs, Maps, Visualizations
• 12 Reliability and Validity
• 13 Information Technologies in Research
• 14 Ethics in Scientific Research
• Index