PPM 211 Social Science Research Methods Course Notes Part 1

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1 PPM 211 Social Science Research Methods Course Notes Part 1 A. The concept of social science research 1. Conceptual issues a) The foundations of social science Science and scientific research help us to understand the world A scientific understanding of the world must 1. Make sense (LOGIC) 2. Correspond with what we observe (OBSERVATION) Social science = Theory + Data Collection + Data analysis Theory deals with logic, it offers plausible explanations about relationships between concepts. Theories have to do with what is real, i.e. how things are, not with how things should be. Data collection involves observation. Data analysis deals with patterns in what is observed. Data collection and data analysis require methods Methodology = the science of finding out PATTERNS are important because we generally do not study individuals, we will be studying collectives: we want to study the aggregate or collective actions and situations of many individuals, we want to study social regularities That is why research where n (the number of subjects) = 1 is usually deemed unsatisfactory: it is descriptive rather than analytical it does not add much to our understanding of the social world. The pattern does not have to occur in each and every case but in a significant majority of cases. Even if one or a few cases do not fit the pattern, the general pattern still holds. Once we have discovered patterns we want to explain why they are so regular even if the individuals participating in them may change over time. b) Why do we do research? There are many reasons to do social research and many different ways of doing social research but in the end all research seeks to add to our understanding of the social world. Some do it because it is fun, others because it is a professional requirement. Sometimes we do research because we want to make the world a better place, sometimes because we are deeply curious about the world. Sometimes we do not need to do research but for professional reasons we do have to be able to read and make sense of research. 1

2 c) Basic concepts Term Meaning model An overall framework for looking at reality (behaviouralism, feminism ) concept An idea derived from a given model (e.g. stimulus-response, oppression ) theory A set of concepts used to define and/or explain some phenomenon hypothesis A testable proposition methodology A general approach to studying research topics method A specific method Relevance Usefulness Usefulness Usefulness Validity Usefulness Good fit with model Model or paradigm A fundamental frame of reference underlying social theories and inquiry. Paradigms provide logical frameworks within which concepts and theories are created. Some examples: Functionalism Behaviouralism Conflict Interactionism Ethnomethodology Postmodernism Critical social research Looking at the functions of social institutions Defining behaviour in terms of stimulus and response Looks at social behaviour as a process of conflict: the attempt to dominate others and to avoid being dominated Focusing on how we attach meanings to objects and interpersonal relationships Focusing on people s everyday ways of producing orderly social interaction No single or traditional ways of knowing, not one coherent, objective theory, rather a variety of competing perspectives Seeks to expose existing belief structures that restrict or limit human freedom and seeks to work towards human emancipation Some paradigms and subtypes explained Structural functionalism, also called social systems theory, divides social phenomena into parts, each of which serves a function for the operation of the whole. It can also be applied to study negative phenomena, not to justify them but to understand why they persist and how they can be eliminated. Symbolic interactionism rests on three premises: 1. Humans act towards things based on the meaning those things have for them 2. The meaning of things arouse out of social interaction 3. Meanings are created and changed through a process of interpretation. Our interpretations are not just individual creations. We are social creatures. Creating and interpreting reality are essentially social processes. This model suggests that researchers need to begin by examining the empirical world to understand how individuals construct and interpret social reality. There is no social reality apart 2

3 from how individuals construct it, and so the main research task is to interpret those constructions. The focus is on how given realities are produced. Postmodernism suggests that texts are always partial, limited and rooted within a particular viewpoint. If all knowledge is limited and socially constructed, then how do we evaluate and interpret social research? If there is no one reality, but merely a variety of perspectives, the traditional criteria for evaluating an interpreting social research become irrelevant. Feminism is part of critical social research. It is a paradigm that views and understands society through the experiences of women and/or examines the generally deprived status of women in society. It focuses on gender differences and how they relate to the rest of social organization. It draws attention to issues of oppression, not only of women but in society in general. Theories Social science is not only about the observation of patterns, we also need to offer logical explanations for such patterns. (1. what is happening? 2. why is it happening? ) Theories help us to provide such an explanation. They propose plausible relationships produced among concepts and/or sets of concepts that can define and/or explain a whole class of events in the social world. We all have our theories, even if we do not think of them as theorizing. We have theories about why some people go to university and others don t, about why some people make more money than others, about why people in our environment behave the way they do. Theories are necessary to see an individual issue in a larger context. Without a theory there is nothing to research. Theories perform three critical functions in research: 1. They prevent us from attaching too much importance to chance occurrences. If we cannot explain a pattern, there is a probability that it is just a chance occurrence. If we know why it has happened, however, we can anticipate whether it will occur again in the future. 2. Theories help us make sense of observed patterns in ways that can assist in addressing or preventing these patterns, in the case of undesirable ones, or in promoting their occurrence, in the case of positive ones. 3. Theories can shape and guide research efforts, pointing towards likely discoveries through empirical observation. d) Approaches to social science research Quantitative versus qualitative research The distinction refers to methodologies: general approaches to study research topics, the theory and analysis of how research should proceed. It involves making choices about cases to study, methods of data gathering, forms of data analysis etc. in planning and executing a research study. Quantitative research Quantitative researchers believe in scientific methods and believe that social scientists should do research in much the same way as natural scientists do. Quantitative research involves enumerating things, using numbers to describe relatively large groups of people (large-n). Examples are studies on the effect of gender on people s education or the statistically significant differences between men s and women s earnings. An often perceived shortcoming of quantitative social research is that when humans are studied in a symbolically reduced, statistically aggregated fashion there is a danger that conclusions although 3

4 mathematically precise may misrepresent the people or circumstances studied or they may conceal or fail to recognize heterogeneity. Such concerns may push large-n research in a small-n direction. Qualitative research Qualitative researches believe that research in social sciences is fundamentally different from natural sciences. They argue that social research is primarily a matter of interpretation. They try to understand social processes in context. Qualitative researchers try to understand the meaning of social phenomena, events, institutions, activities for those involved in them. Meaning is a key concept in qualitative research. The symbolic interactionist perspective in social research, for instance, focuses on how we attach symbolic meanings to objects and interpersonal relationships. Qualitative researchers pay attention to the subjective nature of human life. They consider the subjective experiences of those they are studying but also take into consideration the subjective experiences of the researchers themselves. Qualitative research is usually small-n research. It typically provides in-depth detailed stories (sometimes called thick descriptions ). Scope concerns may arise with this type of research as well when scholars ask whether the findings for the initial cases can be extended more generally. These concerns generally push case study or small-n research in a large-n direction. Qualitative research may appear easier because it does not involve statistics or mathematical formulas but interpretation is a complex issue, almost like an art. How to make sense of all the data gathered? How to identify larger social patterns? The researcher has to develop and deploy her or his analytical skills to be able to make the move from notes and observations to sociological analysis. Gathering data also usually takes longer in qualitative research and requires discrete methodological skills. Deductive versus inductive approach Deductive approach Starting with a theory and deducing logical extensions of it and then turning to the real empirical world to see if the theory is supported by the facts. This approach thus starts with why and moves to whether. From general idea/laws to particular idea/facts Deductive research is also called confirmatory research: research testing a priori hypotheses. Hypotheses are outcome predictions that are made before the observation phase begins. They are usually derived from a theory or the results of previous studies. In confirmatory research, one ideally aims to minimize the probability of falsely reporting a non-significant result as significant. Loosely speaking, if you know what you are looking for, you should be very confident when and where you will find it; accordingly, you only accept a result as significant if it is highly unlikely to have been observed merely by chance. Inductive approach A way of reasoning using known facts to produce general laws, from a set of specific observations to a pattern that represents some degree of order among all the given events. Note that the discovery of a pattern does not tell you why the pattern exists. You have only found that it is there. The inductive approach seeks to generate a posteriori hypotheses by examining a data-set and looking for potential relations between variables. It is also possible for a researcher to have some idea about a relation between variables but to lack knowledge of the direction and strength of the relation. The research will then be aimed at clarifying the relationship. 4

5 The advantage of this type of research is that it is easier to make new discoveries due to the less stringent methodological restrictions. The researcher does not want to miss out on a potentially interesting relation and therefore aims to minimize the probability of a priori rejecting a real effect or relation. The inductive approach is more typical of qualitative research. Applied in the so-called grounded approach to social research = starting with examining the social world and developing a theory consistent with the patterns, themes and common categories that you are observing. The aim is to develop theories grounded in the empirical world. Descriptive, exploratory and explanatory Descriptive research Although descriptive research is sometimes dismissed as `simple description', good description is in fact essential to the research enterprise. Descriptive research has contributed greatly to our knowledge of the shape and nature of the social world. Much publically or collectively funded research constitutes descriptive research, such as the national population census, the collection of social indicators and economic information such as household expenditure patterns, employment and crime statistics etc. Descriptions can be concrete or abstract. A relatively concrete description might be to describe the ethnic mix of a community, the changing age profile of a population or the gender mix of a workplace. Examples of more abstract descriptions are questions such as `Is the level of social inequality increasing or declining?', or `How much poverty is there in this community?', or How much unemployment is there in this district?. Accurate descriptions of phenomena such as the level of inequality, unemployment or poverty can play a key role in policy reforms. By demonstrating and detailing the presence of social problems, competent description can challenge established assumptions about the way things are. In this way it can provoke further research as well as policy action. Good description can provoke the `why' questions that are tackled in explanatory research. If we discern a clear trend of greater social polarization over the last two decades (i.e. the rich are getting richer and the poor are getting poorer) we are forced to ask `Why is this happening?'. But before we develop elaborate theories as to why society might be becoming more polarized, we must be sure about the occurrence and the dimensions of the phenomenon of increasing polarization. If our basic premise is wrong (i.e. contrary to what we assume society is actually not becoming more polarized) then attempts to explain an imaginary phenomenon are pointless. Of course description can turn into mindless, inconsequential fact gathering. There are plenty of unfocused surveys and case studies that are being published which report inconsequential information and fail to provoke any `why' questions or provide any basis for generalization. However, this is a problem of failure to produce relevant descriptions rather than a problem with descriptive research itself. Explanatory research Explanatory research focuses on why- questions. Descriptive research describes the crime rate in a country, examines trends over time or compares the crime rates of different countries. Explanatory research develops explanations about why the crime rate is as high as it is, why some types of crime are on the increase or why some countries are affected by higher crime rates than others. 5

6 Answering the `why' questions typically involves developing causal explanations. Causal explanations argue that phenomenon x (for instance income level) is affected by factor y (for instance gender). Some causal explanations will be simple while others will be more complex. For example, we might argue that there is a direct effect of gender on income (i.e. simple gender discrimination). We might also argue for a causal chain, such as that gender affects choice of field of training which in turn affects occupational options, which are linked to opportunities for promotion, which in turn affect income level. Or we could posit a more complex model involving a number of interrelated causal chains. Some types of explanations: Idiographic and nomothemic explanations Idiographic explanations Idio = unique, separate, peculiar, distinct Idiographic exaplanations fully outline the causes of what happened in a particular instance (a single event). For instance, an explanation of why you chose to study at MSU. Idiographic explanations are more related to qualitative research. Nomothemic explanations Seek to explain a class of situations or events and seek to do so economically using one or a limited number of explanatory factors. For instance, an explanation of what factors determine which university students choose to pursue tertiary education Nomothemic explanantions often provide a partial rather than a full explanation. They are more frequently invoked in quantitative research. Necessary and sufficient causes A necessary cause represents a condition that must be present for the effect to follow. For instance, it is necessary for you to take university modules in order to get your degree. However, simply taking the modules is not enough for getting a degree. You must take the right ones, and, importantly, you must pass them. A sufficient cause represents a condition that if present, by itself guarantees the effect in question. For instance, skipping an exam is a sufficient cause for you to fail a module. There are, however, other ways of failing a module, such as failing the exam. The discovery of a cause that is both sufficient and necessary is a very satisfying outcome in a research project. However, it is rare to discover causes that are both absolutely necessary and absolutely sufficient. Idiographic analysis of single cases may lead to an in-depth of explanation from which it is reasonable to assume that things could not have turned out differently. In that case you have found sufficient causes for a particular result. However, there may be different causal paths to the same result. Therefore the idiographic causes are sufficient but not necessary. Exploratory research Exploratory research maps out a topic that may warrant further study in the future. Its conclusions are mostly suggestive rather than definitive. The goal is not to provide a complete picture but a first scientific impression of a topic. For instance, exploratory research can look into a new political or religious group that has not yet attracted much research attention. 6

7 Pure and applied research Pure research is the generating of knowledge for its own sake. Applied research attempts to have a real-world effect. It wants to make a difference. It for instance wants to see new knowledge put into action in order to make society a better place. It may also be put into practice in more ordinary ways, for example to be used in product marketing. Cross-sectional and longitudinal studies Cross-sectional studies are based on observations representing a single point in time. Exploratory and descriptive studies are often cross-sectional. While many explanatory studies are cross-sectional, they have an inherent problem: their observations are made at only one time but they aim to understand causal processes that occurred over time. It is as if you are using a snapshot to make generalizations about social life. Longitudinal studies involve data collected at different points in time in order to study phenomena over an extended period. They require more substantial investments in terms of time and money than cross-sectional studies There are three common types of longitudinal studies: Trend studies are a type of longitudinal study that examines changes within a population over time. Cohort studies examine specific populations or cohorts as they change over time. A cohort can be an age group, or people from a certain generation, or people who all achieved a certain milestone at a certain time. Although the specific set of people studied at each interval would differ, each sample would represent the same cohort with the same characteristics. Panel studies examine the same set of people (the panel or sample) at several points in time. B. The linkages between method, theory and data 1. Method and theory There are crucial links between theory and method. Methods are not atheoretical. Methods involve certain assumptions and impose certain perspectives on reality. For instance, content analysis of important speeches generally relies on the assumption that the people who gave the speeches write or at least endorse the words. Analysis of news articles in the study of key social events relies on the assumption that key events are represented with descriptive accuracy in the news. Every method is a line of sight directed towards the same point. By combining several lines of sight, we can obtain a better, more substantive picture of reality. The use of multiple lines of sight is called triangulation. We can apply multiple theoretical perspectives, multiple analysis techniques (methods) and multiple data-collection techniques (methods). 2. Theory and data Sometimes researchers move back and forth between inductive and deductive reasoning. In fact it is an important goal of research to extend and improve existing theories based on an awareness of features of the empirical world that aren t explainable by current theories. If we find things that puzzle us, we should not interpret these puzzles as a failure of the theories but instead use these failures to improve our theories. 7

8 3. Data and method Quantitative data: numerical Qualitative data: non-numerical C. Basic elements in research 1. Research problem You don t just need a general topic to research on. You need a problem, a research question to focus on. Clearly to outline, can be quite specific and should not necessarily cover all aspects of a problem. 2. Variable Variables are logical sets of attributes. For instance, sex or gender are variables, male and female are attributes The variable occupation is composed of attributes such as farmer, medical doctor, teacher, policewoman etc. Examples of variables and their possible attributes: Age Sex Profession Social class Religion Political views Young, middle-aged, old Female, male Plumber, lawyer, teacher Blue-collar, white-collar... Lower class, middle class, upper class Christian, Muslim, Buddhist, Hindu, atheist Liberal, conservative The relationship between variable and attributes forms the heart of both description and explanation in social science. Theories are written in the language of variables. 3. Relation Theories describe the relationships we might logically expect between two variables. Often the expectation involves the idea of causation. That is a person s attributes on a variable are expected to cause, predispose or encourage a particular attribute on another variable. We distinguish between independent variables and dependent variables. Independent variable: the cause: a variable with values that are not problematical in an analysis but are simply taken as given. Dependent variable: the effect: a variable assumed to depend on or be caused by another, i.e. the independent variable. Any variable might be treated as independent in one part of an analysis and dependent in another part of it. E.g.: Women are more religious than men. More religious people commit fewer crimes. 8

9 Correlation: an empirical relationship between two variables such that a) Changes in one are associated with changes in the other b) Particular attributes of one variable are associated with particular attributes of the other. 4. Hypothesis A testable proposition based on a theory (but sometimes based on hunches), often framed in causal language: x causes y, x affects y, the more of x, the less of y Part of deductive research In many studies there is no specific hypothesis at the outset. Instead hypotheses are produced or induced during the early stages of research. In any event, unlike theories, hypotheses can, and should, be tested. Therefore, we assess a hypothesis by its validity or truth. Research questions ask what relationships exist between the different variables in the study, while the hypothesis predicts the relationship between variables. 5 characteristics of a good hypothesis 1. A good hypothesis is stated in declarative form and not as a question. 2. A goods hypothesis posits an expected relationship between variable. 3. A good hypothesis reflects the theory or literature on which it built. A good hypothesis thus has a substantive link to existing literature and theory. 4. A good hypothesis should be brief and to the point. It should describe the relationship between variables as direct and explicit as possible. It should be clear, forceful and easily understood. A god hypothesis provides a clear indication as to the general purpose of the research and how it will be conducted. 5. A good hypothesis is a testable hypothesis. This means that you can actually carry out the intent of the question reflected by the hypothesis. Stating a hypothesis A is related to B : usually insufficient as it does not say how the two variables are related. A correct hypothesis would rather be: A is related to B, with [attribute of A] being more supportive than [attribute of A]. For instance, age is related to support for women s liberalization, with younger adults being more supportive than older adults. This hypothesis can also be stated as: Age is negatively related to support for women s liberalization. A is negatively related to B can be used because both variables are quantifiable variables. Should one of the variables not be quantifiable (for instance sex), you need to state the hypothesis differently. For instance, you cannot write: Women are positively related to support for women s liberalization. Instead, you should write: Gender is related to support for women s liberalization, with women being more supportive than men (or with men being less supportive than women ). Operationalizing a hypothesis 9

10 To test any hypothesis, we must specify the meaning of all the variables involved in it, in observational terms. We need to define our variables. For instance, our hypothesis is that delinquency is inversely related to social class. That is, as social class goes up, delinquency goes down. We need to define what we mean by delinquency and what we mean by social class. Then we need to specify how we will measure them (e.g. by asking whether someone has ever stolen something and by defining income categories). Operationalization goes beyond conceptualization. It is the process of developing operational definitions or specifying the exact operations involved in measuring a variable. STEPS IN A RESEARCH PROCESS CONCEPTUALIZATION OPERATIONALIZATION OBSERVATION developing theoretical clarity and expectations hypothesis creating a strategy for looking sampling looking at the way things actually appear, testing your hypothesis 5. Sampling The process of selecting observation, taking place between operationalization and observation 6. Research design A research design is a systematic step-by-step plan to study a scientific problem. The design of a study defines the study type (e.g. descriptive) and sub-type (e.g., descriptive-longitudinal case study), research question, hypotheses, independent and dependent variables, experimental design, and, if applicable, data collection methods and a data analysis plan. Research design refers to the structure of an enquiry: it is a logical matter rather than a logistical one. A central function of research design is to minimize the chance of drawing incorrect causal extrapolations from data. Research design is undertaken to ensure that the evidence collected enables us to answer questions or to test theories as unambiguously as possible. When designing research it is therefore essential that we identify the type of evidence required to answer the research question in a convincing way. This means that we must not simply collect evidence that is consistent with a particular theory or explanation. Research needs to be structured in such a way that the evidence also relates to alternative, competing explanations. This enables us to identify which of the rival explanations is most compelling empirically. It also means that we must not simply look for evidence that supports our preferred theory. It is the researcher s obligation to also look for evidence that has the potential to disprove our favourite explanations. a) Simplified research design for a deductive approach 10

11 b) Simplified research design for an inductive approach 11

12 7. Research proposal Research proposals have to be persuasive: they are often created for the purpose of getting funding, getting permission to carry out the research project, getting a place at a conference, getting a scholarship etc. A research proposal introduces the problem, purpose, and significance of a study as well as the researcher s research question and hypothesis. It also gives a brief explanation of the theory guiding the study, a review of relevant literature pertaining to the theory, and the procedure for the research. Key elements of a research proposal are: a) Problem or objective What do you want to study? Why is this topic worth studying? What is the relevance or significance of the proposed research? Explain the central question or problem of your research. Are there certain sources that have been neglected? Is there an unfounded common or dominant opinion that you would like to contest? Is there a methodological problem with current research? Has a new phenomenon popped up that appears to contradict the current scientific consensus? Explain your research question clearly. b) Literature review The literature review provides the background for the research problem and illustrates to the reader that the researcher is knowledgeable about the scope of the theory. It will usually also highlight a shortcoming or gap in the literature that the proposed study will seek to address. Question to be answered in the literature review: What have others said about the topic? What are the dominant views, debates, questions? What theories have been applied to the subject? Are there consistent findings in prior research or do past studies disagree? Are there flaws in the existing body of research or gaps in our understanding? When searching for literature, focus both on your research topic and on the data collection method you intend to use in your study. The purpose of your literature review is to introduce the reader to your topic. Explain in a logical manner what has already been written on the topic by other researchers and then leading up to some of the holes, gaps, disagreements or inconsistencies in our knowledge of the topic, which you propose to remedy with your study. Sources that you will consult: Journal articles: read the abstract carefully, read summary and conclusions, skim through the article, then read the whole article carefully. Read in an active, engaged manner, taking notes along the way. Research monographs: read preface and opening chapter carefully before proceeding onto reading other parts of the book Use the Internet wisely. Ask yourself o Who is the author of the website (are there risks of bias or sloppiness?) o Is the site advocating a particular point of view? o Does the site give accurate and complete references? o Are the data up to date? o Are the data official? o Is it a university research site? 12

13 o Do the data seem consistent with data from other sites? Cross-check data wherever possible. c) Subjects for study Whom or what will you study in order to collect data? Identify the subject in more general theoretical terms and in more specific concrete terms. Will you use sampling? d) Elements from your research design Measurement What are the key variables in your study? How will you define and measure them? Data collection methods How will you collect your data for your study? Will you conduct an experiment or a survey? Analysis Spell out the purpose and logic of your analysis Are you interested in precise description? Do you want to explain why things are the way they are? Do you want to account for variations in some quality? For example, why are some students more supportive of a certain phenomenon than others? e) Schedule Providing a timetable for the various stages of your research is often appropriate. f) Budget If you are applying for funding, you will need to provide a budget that explains on what items the money will be spent. Even if you ll be paying for your research yourself, spend some time thinking about potential expenses and whether they are bearable for you. g) Ethical concerns If your study can raise any problems or concerns, make sure to mention them and explain how you will avoid or address them. h) References Remember to include a reference list at the end of your proposal of all the sources used. i) Lay out Organize your proposal nicely, using clear and descriptive section and subsection headings. j) Clarity Make an effort to clearly define your concepts and methods. Do not take it for granted that your reader is a specialist in these areas. Make sure to demonstrate the relevance of your study. You can also attach a letter of support from an organization to proof institutional buy-in. 13