SOC Ch.2 Research Methods.docx

SOC Ch.2 Research Methods Introduction Sociologists are dedicated to exploring the social world. Their goal is to comprehend the diversity of social groups, identify patterns, and describe the impact of social change on individuals, institutions, and the environment. Uncovering the intricacies of the social world is a complex task. While careful observation, such as people-watching in a coffee shop, can provide initial insights, these observations may be prone to bias. Bias, defined as systematic errors that can skew the conclusions drawn from observations, can result in inaccurate or imprecise knowledge. Therefore, sociologists strive to obtain insights that are both reliable and meaningful, truly representing the social world. Sociologists gain reliable insights through thorough observation and analysis, often conducted over an extended period. This approach involves deep engagement with the social world and self-reflection to overcome biases. By carefully examining social phenomena, researchers can provide in-depth, analytical accounts of social reality. For instance, the text mentions an analysis of how policing is portrayed in the media as an example. THEORY IN EVERYDAY LIFE 2.1 | Representations of Community Policing Human imperfection leads to intentional masking of realities, generating false impressions and misinformation. Language plays a crucial role in creating new realities and shaping societal interactions. Policing and police officers, though not always positively perceived, symbolize the state's authority to employ violence and force to impose societal will. Ideally, peace would be achieved through non-violent methods, but the police serve as a means of enforcing social order through coercive means. According to Klockars (1988), community policing is viewed as primarily a rhetorical tool, employing language to persuasively convey a specific message and influence perspectives. He argues that community policing serves to mask the genuine nature of the police role in society. Social media platforms are utilized by police to present a narrative of moving away from militarization and professionalism, adopting more appealing but potentially misleading aspects like decentralization and increased community interaction. Sociologists can study these rhetorical strategies through easily accessible and widely available technologies, such as Twitter or Facebook, enabling the observation of long-term trends and uncovering the actual social realities. Defining Research MethodsSocial research methods are tools used by sociologists to understand and contribute to social life. They serve five main purposes: Enumeration and Description: Collecting data to outline society’s basic characteristics, like a census. Prediction: Determining the effectiveness of strategies, such as policies for public health improvement. Accuracy is crucial as decisions are based on these predictions. Explanation: Creating theories about the world by finding out how variables influence each other, typically seen in scholarly journals. Debunking: Challenging popular beliefs or myths, for instance, stereotypes about unemployed people or welfare recipients. Social Justice: Understanding experiences of marginalized groups with the aim of achieving social change. The work of sociologists in research methodology is crucial for several reasons: Policy Development: Accurate, high-quality data is essential for creating effective social policies in areas such as welfare, policing, childcare, education, and health care. Inequality Reduction: Sociologists strive to identify, describe, and eliminate social inequalities. Knowledge Construction: The creation and dissemination of knowledge are social processes that can be studied and critiqued. Sociologists work to ensure this knowledge is reliable and unbiased. The Process of Research This section is about designing a research study from start to finish. It emphasizes the development of key research skills such as study design, data collection and analysis, interpretation of data and statistics, and understanding graphs and figures. These skills are highly valued in our data-driven society. Research is a complex process involving deep engagement with a topic, constant problem-solving, and adaptability to unexpected changes. Each research project has its own life cycle and challenges and can range from months to years. The process is nonlinear and iterative, often involving trial and error. It's not a smooth path but a journey of learning and discovery. Identifying an Area of Study The initial step in a research project involves identifying a broad area of interest. This is followed by establishing a specific focus within that area. The researcher then reviews existing studies related to this focus to understand the current state of knowledge, identify gaps in the research, and formulate meaningful research questions. Literature Review The literature review is a crucial part of any study. It serves two main purposes: Understanding Past Work: It helps researchers understand what has been studied before, enabling them to identify gaps in existing knowledge. This identification of research gaps is vital as it highlights areas where more research is needed. Clarifying Study Significance: The literature review helps clarify the importance of the study. It allows researchers to explain how their study will contribute to existing knowledge and fill a research gap. It also helps distinguish their work from previous similar studies. Research Question After identifying gaps in current knowledge through a literature review, a researcher formulates a research question. This question, which is about a specific behavior, event, or phenomenon, guides the research process. The formulation of a research question is guided by three principles: Clarity: The question should be clear and easy to understand. Specificity: The question should be specific and avoid vague language. Feasibility: The question should be answerable within a single project. The type of question formulated then helps the researcher decide how to design their study to best answer their question. Research Design The research design serves as the plan or blueprint for a study. It outlines the type of study, research question, variables, data collection methods, and analysis plan, aiming to integrate these elements. The research question and design are developed to guide the researcher throughout the research process. In constructing a research design, scholars must scrutinize their biases and evaluate essential research excellence criteria such as reliability, validity, social significance, ethical considerations, and potential knowledge contributions. Despite the advancements in science and technology offering new tools for data collection to visualization, our capacity to acquire new knowledge hinges on the clear articulation of a thorough and robust research design. An effective research design is easy to comprehend, encompasses all necessary sections, and seamlessly integrates these components. In research design, operationalizing key variables is crucial. Variables, measurable attributes, or characteristics are essential for sociological studies, particularly those focused on inequality and vulnerabilities. Sociologists examine individual variables like education, ethnicity, and income, while also exploring community-level variables such as the availability of healthcare professionals in a community. Operationalization involves the measurement and comparison of abstract theoretical concepts, and it is a significant challenge in sociological research. Concepts like prejudice, alienation, and loneliness are particularly difficult to define and measure accurately. While variables like the number of doctors in a community can be easily counted, subjective perceptions such as loneliness are more complex. Loneliness, for example, is not directly observable, and distinguishing between being alone and feelings of social isolation requires careful consideration. Researchers often rely on past studies to inform the operationalization of variables, underscoring the importance of meticulous research design. A sound research design is crucial, primarily in its justification of decisions regarding data collection methods, the targeted population, and data analysis, all while consistently considering ethical considerations. Collecting and Analyzing Data In crafting a research design, it is important for the researcher to provide a detailed plan for both data collection and analysis. A strong alignment between the research problem, data collection, and analysis approach is crucial, considering that diverse research questions necessitate different types of data and methodologies. The nature of the social group under investigation plays a role in determining the most suitable methods for data collection and analysis. These methods are typically categorized into quantitative, qualitative, or mixed methods approaches. Quantitative Methods Quantitative approaches in research are defined by their dependence on numerical values, often gathered through surveys rather than interviews, images, or videos. This type of research focuses on examining the relationship between multiple variables and testing specific hypotheses about those relationships. A hypothesis is a prediction or informed assumption regarding the connection between two or more variables, illustrating the significance of hypotheses in the research process. In the quantitative approach, data is generated with the purpose of testing a hypothesis, following a deductive approach. The hypothesis typically revolves around determining whether two or more variables are correlated, meaning that changes in one variable are associated with changes in another. Correlation, a measure of association between two variables, can be either positive or negative. A positive correlation implies that an increase in one variable corresponds to an increase in the other, while a negative correlation indicates that an increase in one variable corresponds to a decrease in the other. In a study by Primack et al. (2017) examining social media use among millennials (aged 19–32), the researchers tested two hypotheses. They hypothesized that increased use of multiple social media platforms would be independently associated with both depression (Hypothesis 1) and anxiety (Hypothesis 2). To test these hypotheses, respondents ranked their answers to questions using a five-point scale, operationalizing variables such as loneliness and anxiety. For instance, a question in the study asked respondents to rate their agreement with the statement: "I feel that people are around me but not with me," with scaled responses ranging from 1 = "Never" to 5 = "Always." In the study by Primack et al. (2017), it was found that individuals who used social media extensively and checked their accounts frequently were more likely to report higher levels of social isolation compared to those who used it less frequently. The study established a correlation between the frequency of social media use and reported feelings of social isolation. Importantly, the study does not assert that social media use causes loneliness; it acknowledges the possibility that individuals experiencing loneliness may use social media to address their feelings. Nevertheless, the findings suggest that even though social media is intended to enhance social connectedness, it may not effectively counter feelings of social isolation. To establish the trustworthiness of research, scholars emphasize two crucial concepts: reliability and validity. Reliability pertains to the consistency and replicability of findings across comparable situations, while validity concerns the accuracy of how a concept, idea, or measure represents the real world. In quantitative approaches, data analysis heavily relies on statistics, which deal with large sets of numbers and provide mechanisms for collating, analyzing, interpreting, and presenting data. Statistical data plays a significant role in informing policies aimed at improving the well-being and health of individuals, families, and communities. For example, statistics on alcohol consumption among Canadians are used to shape policies. Around 80 percent of Canadian adults consume alcohol, and data on sales of alcoholic beverages reveal consumption patterns over time. Understanding such patterns is crucial for recognizing factors driving alcohol consumption and allows policymakers to provide necessary support for individuals needing to reduce alcohol-related harms. This knowledge contributes to the development of effective policies targeting high-risk drinkers. Quantitative analysis brings to light social patterns that might escape notice. For instance, an examination of Statistics Canada data reveals that, in comparison to other social groups in Canada, a higher proportion of the Indigenous population in the country are nondrinkers (Statistics Canada, 2015). Statistical data can highlight areas of interest that might be overlooked by decision-makers. As an example, one policy recommendation suggests raising alcohol pricing to mitigate alcohol-related harm. Despite initial skepticism about its effectiveness, research indicates that setting a minimum price for alcohol or pricing based on alcohol content reduces alcohol consumption across the population. Statistics not only help uncover valuable information but can also guide the development of more effective solutions for social issues. There are concerns regarding the use of quantitative research for drawing conclusions and shaping policies that impact government funding allocation. Critics, such as Walter and Andersen (2013), argue that quantitative methods have limitations as they often overlook the complexity of everyday life in favor of broad macro-level patterns, tendencies, and averages. Kukutai (2001) similarly criticizes this approach, emphasizing its focus on "statistical creations based on aggregated individual-level data" rather than considering the diversity of real-world concrete groups. Walter and Andersen (2013) highlight a significant drawback of current quantitative methods, pointing out that they often frame Indigenous Peoples through a lens of "difference, deficit, and dysfunction" instead of recognizing and appreciating the unique cultures and ways of life within these communities. They emphasize that this is a crucial issue because statistics play a pivotal role in influencing government decision-making processes. Qualitative Methods Qualitative research diverges from quantitative methods by focusing on characteristics that cannot be easily quantified. Rather than relying on numbers, graphs, and mathematical models, qualitative approaches involve diverse data sources such as interviews, images (photography or digital images on social media), videos, and narratives. Qualitative researchers aim to generate rich and detailed accounts by deeply engaging with the subject matter. Qualitative research aims not to test existing theories but, rather, to develop new theories from the gathered data, adopting an inductive approach. Trustworthiness and credibility of findings in qualitative research are achieved through saturation and triangulation. Saturation is the point when no new insights are gained from additional data analysis, and qualitative researchers carefully analyze their data to determine when saturation is reached. Triangulation involves comparing data from various sources, providing qualitative scholars with a method to make sense of their data. In qualitative research, data analysis aims to understand how people create and attribute meaning to their experiences. Qualitative scholars often use coding techniques to analyze interview transcripts, images, or textual data. They also engage in memoing, which involves adding extensive notes. For example, Schneider (2016) conducted a qualitative document analysis to investigate the strategies Canadian police use on Twitter. This analysis involved examining 105,801 tweets and placing their meaning in a social context. The study revealed that officers' tweets maintained a public professional appearance, avoiding political discussions, and used Twitter to foster interactive communication with the public, challenging traditional assumptions about policing. A tweet from the London Police Service congratulating a sergeant for preventing elder abuse is provided as an illustration in Figure 2.4. Mixed Methods There has been a growing interest in conducting mixed methods research because this approach combines the strengths of different data collection and analysis approaches (Johnson et al., 2007). Generally, a mixed methods approach is any combination of research methods. For example, Baker et al. (2015) examined how patients in Canada and Australia rate the quality of interactions with their doctors by combining questionnaire responses with accounts of positive and negative experiences. The rationale for using a mixed methods design was to capture patient perspectives in a more representative way. Mixed methods design, as suggested by Creswell (2013), is not necessary for all studies. It is deemed appropriate when either quantitative or qualitative methods alone cannot offer comprehensive insights into a research problem, and when there is a need for one of the following: To facilitate a more diverse understanding of a single phenomenon. To validate quantitative findings with qualitative data. To provide better context for quantitative instruments and measures. To combine small-scale and trend data. Mixed methods studies offer numerous merits, with data triangulation being commonly recognized as the most important. Data triangulation involves combining the strengths of different approaches to enhance the validity of findings. In mixed methods designs, the weaknesses of large-scale quantitative methods can be balanced by the advantages of observations and descriptions obtained from fieldwork. Additionally, statistics can add precision to qualitative narratives provided by participants. Overall, mixed methods studies allow for a more comprehensive understanding of a social phenomenon by leveraging the strengths of both quantitative and qualitative approaches. Mixed methods research presents several challenges. Firstly, it is time-consuming and complex, as it involves integrating different methods and potentially dealing with different populations or social groups. Secondly, conducting mixed methods research requires expertise in various aspects of data collection, analysis, visualization, interpretation, and writing. Given that quantitative and qualitative approaches are distinct, researchers undertaking mixed methods studies must be well-versed in both to effectively navigate the complexities of this approach. Write-Up, Scholarly Communication, and Critical Reflection After collecting data, scholars need to formalize their extensive notes before presenting their work at conferences or publishing it in journal articles or books. Prior to publication, scholarly work undergoes a peer review process, where experts in the field evaluate the research question, design, and provide feedback. Sociologists commonly present their work at conferences such as those organized by the International Sociological Association (ISA), the American Sociological Association (ASA), and the Canadian Sociological Association (CSA). Peer review serves to assess the merits of the research and contribute to the quality and credibility of sociological scholarship. While academic venues are crucial for sociologists to exchange ideas, scholarly communication extends beyond traditional channels. In the contemporary landscape, sociologists share their findings through various alternative forms such as blog posts and tweets. Public sociology, as described in Box 2.2, focuses on making sociology relevant to the public and leveraging sociological work to have an impact both locally and globally. This emphasizes the importance of reaching a broader audience and engaging with the public beyond the confines of academic circles. THINK GLOBALLY 2.2 | Call for a Global Public Sociology Sociology, as an academic discipline, is focused on studying and understanding the social world. Given this focus, sociologists consider engagement with the public to be a fundamental aspect of their work. The term "public sociology," popularized by Herbert Gans in 1989, emphasizes the critical importance of establishing stronger connections between the academic realm and the public. Public sociology has two main mandates: first, for sociologists to investigate questions that hold public relevance and directly impact people's lives, and second, for sociologists to actively engage with the public and widely disseminate their work. Global public sociology acknowledges that knowledge production and access are not evenly distributed worldwide. Sociologists working in regions with limited or underserviced libraries may face challenges in accessing essential learning resources, including journal articles, books, and reports. This unequal distribution of knowledge hinders scholars in staying current with developments in their field and actively contributing to scholarly discourse. Two recent initiatives aim to improve access to learning resources in underserviced regions. The first initiative involves the development of open educational resources, such as lectures, slides, articles, and books, which are made available online at no cost for educational purposes (UNESCO, 2002). The Organisation for Economic Co-operation and Development (OECD) recognizes open educational resources as crucial for unlocking the potential of universities in resource-limited areas by providing unlimited access to a diverse range of learning materials (Orr et al., 2015). In Canada, many sociologists contribute to this effort by sharing their work at no cost through platforms like YouTube videos, open-access journal publications, and articles posted in university library repositories. The second key development is the use of social media to reach a broad and global audience and directly engage in debate. Many sociologists have an online presence through a personal blog, Twitter, or an Academia.edu account. Theoretical Approaches to Research Methods In the upcoming section, we will explore various methodological approaches and evaluate their strengths and weaknesses in the context of a study. Research methods convey meaningful insights about the social world, and a notable example is the distinction between cross-sectional and longitudinal approaches. Cross-sectional approaches examine social phenomena at a single point in time without focusing on change. Conversely, longitudinal approaches recognize the dynamic nature of the social world, emphasizing the study of change. The discussion will delve into how different theories drive the selection of specific methods, and a summary of these theories is provided in Table 2.1. Conflict Theory Conflict theory aims to uncover and better understand inequalities in society related to access to resources, power, and privilege. A wide range of methodologies can help us better understand inequalities among social groups. Marx, recognizing the inequalities between workers and owners in industrial-era Europe, aimed to raise awareness among workers about these disparities. As part of his theoretical work, he developed "A Workers' Inquiry," a list of 100 questions designed to prompt reflection among workers and document the extent of worker exploitation. This reflective survey scrutinizes the day-to-day experiences of workers in their labor. An example question, like question 26, inquires about the legal obligations of employers to compensate workers or their families in case of accidents (Marx, 1938). Methodologies rooted in the conflict theory perspective emphasize the essential role of social justice in both research processes and outcomes (Brown & Strega, 2005). Scholars within this perspective prioritize the lived experiences of marginalized social groups and aim to avoid imposing the researcher's worldview. Conflict theory prompts a departure from preestablished notions of knowledge, leading to critical reflections on the research process and knowledge acquisition. Key features of methodologies in this tradition include: Position of researcher: Emphasis on describing and reflecting upon the relationship between the researcher, the researched, and the research topic. Attention is given to how researchers position themselves as authorities defining knowledge. Topic of inequality: Studies focus on marginalized social groups, highlighting societal inequalities and exploring mechanisms for social change. Critical reflection: Studies move away from conventional notions of knowledge, data, objectivity, and methodology, embracing deep understandings of critical, Indigenous, and anti-oppressive approaches (Brown & Strega, 2005). Feminism Feminism employs methodologies aimed at revealing inequalities among social groups in society. Large-scale studies, such as those discussed in subsequent chapters, can expose gendered imbalances in pay. Additionally, feminism adopts methodologies focused on describing the daily experiences of marginalized social groups, including but not limited to Black women, Indigenous women, or transgender individuals. Dorothy E. Smith, a Canadian sociologist, introduced institutional ethnography to uncover the processes, relations, and biases within an institution influencing the everyday experiences of individuals interacting with it. Inspired by her involvement in the women's movement of the 1970s, Smith aimed to address power imbalances between men and women. She observed that gender imbalances were inadvertently reinforced by research attempting to expose them. In response, Smith developed institutional ethnography as a method to investigate and explain the challenges faced by individuals and groups from their own perspectives. Standpoint theory, integral to her approach, posits that our view of the world is shaped by our social locations, including ethnic background, social status, class, and other demographic characteristics. In institutional ethnography, as explained by Smith (1990), sociologists conduct inquiry as insiders, functioning as practitioners within the organization. They elucidate and analyze the actual practices of the organization based on their firsthand knowledge and discoveries. Stemming from a necessity to comprehend marginalized social groups, particularly women, standpoint theory becomes instrumental in understanding diverse standpoints and their impact on institutions. For instance, Rankin and Campbell (2009) applied institutional ethnography to examine the social organization of health care from the perspective of nurses in Canada. Their study revealed that health-related administrative data were input and stored in computerized systems for efficient and standardized monitoring of patient care processes. This replaced the previously detailed and thoughtful handwritten notes of nurses. The way notes are taken and stored influences the activities and decisions of both nurses and doctors. Through this research, Rankin and Campbell offer insights for health-care reform and emphasize the significance of conducting institutional ethnography to unveil concealed issues in the system. Functionalism Functionalists examine how society is organized and the role of institutions in reinforcing social order. For instance, families are considered an important institution in society. The definition and composition of families are constantly under flux as society changes. Functionalists predominantly rely on quantitative data to depict changes in institutions and their compositions over time. Large-scale survey data and analyses are commonly employed to quantify and comprehend these changes. For example, Beaujot and Kerr (2004) investigated marriage trends in Canada, finding a shift in the median age at first marriage between the 1970s (ages 21 for brides and 23 for grooms) and 2001 (ages 28 and 30 for brides and grooms, respectively). They also observed that common-law unions were often delaying or replacing marriage, with 63 percent of first unions among women aged 20 to 29 in 2002 being common-law unions rather than marriages. Additionally, they noted that these common-law unions were twice as likely to end in separation compared to first marriages (Beaujot & Kerr, 2007). Symbolic Interactionism Symbolic interactionism examines how individuals comprehend the world through their interactions with one another. Central to this perspective is the exploration of how meaning is generated and contested in social interactions, with a focus on the role of symbols in the meaning-making process. A common method employed by symbolic interactionists to study this phenomenon is participant observation. In this qualitative approach, researchers both observe and actively participate in interactions with the group under study, allowing for a nuanced understanding of social dynamics. While various methods are employed to study social interaction, ethnomethodology is particularly associated with the symbolic interactionist approach. Harold Garfinkel laid the foundation for ethnomethodology with the publication of "Studies in Ethnomethodology" in 1967. This approach centers on people's accounts of situations, specifically the explanations individuals develop to understand and explain particular social situations. Ethnomethodology seeks to uncover the implicit rules and methods people employ to make sense of their social world. In the process of developing explanations, individuals draw upon what they perceive as everyday, "common-sense" rationales. Ethnomethodology, initially introduced by Garfinkel, has evolved over time, and its current understanding encompasses a diverse set of research techniques rather than being considered a singular approach (Maynard, 1991). Methods of Social ResearchSurvey Research Survey research aims to systematically collect information on a particular topic for the purpose of describing, explaining, or influencing a social phenomenon. This method employs structured interviews or questionnaires, with questionnaires being the more prevalent approach. Three key strengths distinguish survey research: standardization of questions minimizes bias, predetermined answer categories facilitate comparisons, and it enables the collection of data from many respondents. Survey research is suitable for studies that seek to describe trends, identify relationships between variables, or gain a comprehensive understanding of a phenomenon. An example is the study by Beaujot and Kerr (2007), where questionnaires were employed to assess the age at which Canadians choose to get married. The researchers used this method to compare the average age of marriage in the 1970s to that in the 2000s, providing insight into a changing trend over time. Survey research relies on collecting data on a specific population. A population describes the larger pool of individuals who all share a characteristic relevant to the study. As populations can be large, it is difficult to collect data from all members of a population. To make conclusions about a population, researchers select a subset known as the sample. The process, called sampling, involves choosing participants from within the larger population. Various sampling strategies exist, with the stratified random sample considered ideal. This strategy involves dividing the population into groups (strata) based on a common trait and selecting participants from each group. While effective, the stratified random sample can be expensive, leading researchers to opt for alternative strategies. The validity of research findings is closely tied to the quality of the chosen sampling strategy, making sampling a critical aspect of the research process. Survey research, while offering the advantage of collecting extensive data on a population, has notable drawbacks. Firstly, it restricts participants from expressing their opinions fully or in their own words, as responses are often constrained by standardized answers that may not accurately capture personal sentiments. Secondly, the method relies on direct questioning instead of natural observation, limiting the exploration of emerging topics or key research questions. Alternative methods like ethnography, involving researcher engagement in the field, allow for a more nuanced and flexible approach. Self-Administered Questionnaires A self-administered questionnaire is designed for respondents to answer a predetermined set of questions without direct involvement from a researcher. It can be administered on paper, by telephone with automated voice prompts, or online. Online surveys offer advantages such as versatility, wide reach, and improved data accuracy due to direct digital recording of responses. They overcome issues like poor response rates in mailed questionnaires. However, online surveys may face challenges related to data accuracy, with participants potentially completing the survey multiple times if incentivized. The Census of Population is a crucial survey in Canada due to its comprehensive coverage. It involves a short questionnaire collecting demographic information from all Canadians, including those abroad and Indigenous people within Canada, aiding in the planning of services like education and transportation. The census is mandatory for all Canadian residents to ensure the most accurate information. In recent years, online responses have been allowed to enhance accessibility. However, challenges exist in identifying and recruiting individuals from marginalized social groups, as discussed in Box 2.3, which highlights Statistics Canada's efforts to ensure full enumeration of dispersed Indigenous populations wary of participating in the census. DIGITAL DIVIDE 2.3 | Statistics Canada’s Strategy for Ensuring Full Enumeration of Indigenous People in Canada Statistics Canada is a governmental agency tasked with generating statistical information on the people, resources, economy, and cultures of Canada. While the census is a well-known survey conducted by Statistics Canada, the agency conducts around 350 other surveys on various topics such as health, labor markets, and digital connectivity. What distinguishes Statistics Canada's dataset is the substantial size of the sample from which it collects information. Surveys, like the 2016 census, may cover large populations, such as 35 million individuals. The agency employs random participant selection to ensure unbiased data that can be generalized to the entire population. To ensure survey completion, Statistics Canada employs various contact methods, including traditional mail surveys, phone calls, and emails. A significant challenge for the agency is achieving complete enumeration of Indigenous people within Canada. Factors such as poverty, lack of a permanent address, historical distrust of the government, and migration between locations contribute to nonparticipation, particularly in urban areas. Strategies to enhance accuracy include using multiple questions that address aspects like ancestry, Indian Status, self-identification, and First Nation membership to distinguish Indigenous participants. In 2016, households in First Nations, Inuit, and northern communities were enumerated using the long-form census questionnaire, administered in person by a canvasser. Indigenous people living off-reserve or outside these specific communities were accounted for through the same sampling structure as the general population. These measures help Statistics Canada gather more accurate data on hard-to-reach populations, ensuring the data better reflects the overall population. The agency has also focused on improving data-sharing practices to make the information more useful for the populations it reports on. The census program comprises two parts: a concise survey covering basic information and the National Household Survey, which involves a more detailed and lengthier questionnaire. The second part gathers information on demographic, social, and economic characteristics, along with details about people's locations within Canada. The collected data aid in program planning and delivery across all levels of government. Table 2.2 illustrates five Canadian datasets relevant to sociological inquiry. Scholars need to carefully assess data accuracy prior to commencing data analysis. One successful strategy consists of combining online surveys with paper-and-pencil surveys because this strategy does not exclude individuals who are not connected to the internet (Ilieva et al., 2002). Statistics Canada combines online, paper, and telephone surveys as part of its attempt to reach as many people as possible. Researcher-Administered Questionnaires Researcher-administered questionnaires involve a trained researcher contacting respondents to ask a set of carefully scripted questions, commonly used in political polling and opinion research. Using the telephone or occasionally in-person interviews, the interviewer reads questions and response options, prompting the respondent to choose the best answer. Open-ended questions may also be used, where respondents express their thoughts on various topics. Research assistants then code these responses, categorizing them and assigning numbers for easier data analysis. Most survey research utilizes computer analysis for increased accuracy and simplified application of statistical tests to identify patterns. Using a human interviewer generally increases the likelihood that a sampled person will respond to survey questions, especially those that are sensitive or personal. Human interviewers can also provide clarification if needed. However, careful selection and training of interviewers are essential to avoid unintentional influence on respondents' answers. Certain types of interviewers may be better suited for specific respondents or topics. It's important to recognize that interviews involve social interactions, and some respondents may respond in ways that exaggerate their success, popularity, intelligence, or determination. The primary drawback of in-person surveys is their cost, as interviewers must be compensated for their time. Surveys typically involve large samples, often in the hundreds or thousands, and a significant proportion of contacted individuals may refuse to participate. This refusal rate can be high, reaching 80-90 percent for external surveys. The cost of completing the necessary number of interviews becomes substantial. To mitigate expenses, researchers may consider reducing the sample size, but this compromises the ability to draw robust and significant conclusions. Interviews Interviews involve conversations with individuals from social groups of interest, allowing participants to express opinions in their own words. This method is particularly useful for projects aiming to comprehend social groups, gather information on opinions and attitudes, and uncover meaning and relevance. Two common types of interviews in sociological research are in-depth, unstructured interviews, and semi structured interviews. The choice between these types is typically guided by the nature of the research questions and the specific needs of the populations involved, according to Bernard (2013). Unstructured interviews provide the interviewer with complete freedom to take the interview in any direction. The advantage of this format is that it allows for an in-depth exploration of a topic with few external constraints imposed. Semi structured interviews integrate the benefits of structured interviews while also allowing the interviewer to follow new leads and prompts for clarification (Bernard, 2013). This technique allows the researcher to explore specific topics in depth and to tailor questions in response to a participant’s responses. Semistructured interviews utilize carefully crafted interview guides that outline essential topics, points, and sample questions to standardize and efficiently guide the interviews. For instance, in a study on how aging Canadians incorporate walking into their daily routines, researchers conducted one-on-one semistructured interviews with 14 participants aged 65 and over. They asked participants to bring pictures of places they walked in their neighborhood, using these visuals to inform and contextualize responses. The study revealed that high-quality and safe walking spaces encourage seniors to be more active. The combination of the structure provided by the interview guide and the flexibility to deviate if needed ensures the generation of reliable and comparable qualitative data, as noted by Bernard (2013). Field Research Field research is research done outside a laboratory (Palys & Atchinson, 2014). It involves careful observation of participants in their natural settings, for example, at schools, hospitals, or other social spaces. Data collection can include surveys, interviews, and focus groups (Sullivan, 2009). Field research is characterized by its non-restrictive nature, aiming to collect diverse data types from multiple sources. This approach facilitates the researcher in generalizing about social behavior based on the gathered data. The high validity of field research is attributed to the observation of people in their everyday lives. Additionally, field research can stimulate the emergence of new questions and identification of variables for further examination, enhancing its exploratory nature (Sullivan, 2009). These very same advantages can become detriments to the research if the field is unpredictable or if participants are hostile or argumentative toward the researcher (Sørnes et al., 2014). Also, preconceived notions and expectations of both the researcher and the participants can alter the observations (Sullivan, 2009). Participant Observation Participant observation is a strategy where the researcher observes an individual, a group, or a community to understand and become familiar with their customs and practices. Participant observation is a research strategy in which the researcher observes an individual, group, or community to gain insight into their customs and practices. This approach involves the observer actively participating in the group or community being studied, adding depth, and understanding to the research. However, complete immersion may lead to issues like those in ethnographic studies, where participants, aware of being observed, may adjust their behaviors, a phenomenon known as reactivity (Sullivan, 2009). Ethnography Ethnography is a research approach where researchers fully immerse themselves in a setting, observing participants over an extended period. What sets ethnography apart is the prolonged timeframe and the nature of the relationship between the researcher and participants. Various data collection methods, including field notes, interviews, and surveys, are employed by ethnographers to develop a personal understanding of the setting. Participant observation is a crucial aspect of gaining insight. Detailed field notes and analytical notes are instrumental in creating a coherent account of the observed phenomena. Ethnographies involve prolonged immersion, sometimes spanning years, during which scholars closely share the experiences of the participants to gain an in-depth understanding of their culture. Goffman's involvement in a low-income African American community in Chicago, starting in her sophomore years and continuing into her doctoral studies, exemplifies the extensive duration of such research. In contrast, Buffam's study of a drop-in recreational center in Edmonton, predominantly visited by Indigenous youth, lasted three months, illustrating that the time frame varies based on the research's scope and nature (Goffman, 2014; Buffam, 2011). Negotiating access is crucial for researchers, considering varying sensitivities among social groups about being subjects of research. Establishing relationships with communities and understanding their cultural sensitivities is essential for ethical research. The level of involvement a scholar should have in field immersion is a topic of discussion, as highlighted in Box 2.4, which explores the debate around Alice Goffman's level of involvement with the subjects of her study and the methodological soundness of her approach. SPOTLIGHT ON 2.4 | Alice Goffman’s Ethnographic Work in Chicago Goffman’s (2014) research topic was the impact of mass incarceration and policing on low-income African American inner-city communities (Lewis-Kraus, 2016). Goffman integrated herself for about six years into a low-income community by befriending a group of young African American men who were members of a gang. Goffman employed a highly personal research strategy, establishing friendships with her research participants to represent the perspectives of an oppressed group. However, the approach of studying a gang from the inside raises concerns. By predominantly focusing on the perspective of the young men in the gang and giving less weight to the viewpoint of the "other side," such as police officers, Goffman faced challenges in adequately validating facts. This limitation raised the possibility that rumors or myths could be perceived as truth in her research (Lubet, 2015). Moreover, Goffman's minimal acknowledgment of her position as a white, middle-class woman in a predominantly African American community raised concerns. As she adopted behaviors associated with the community, she obscured her role as a researcher and her sense of positionality. The most controversial aspect of her strategy was her willingness to be a passive witness or even a coparticipant in a crime committed by those she was studying. Critics were unimpressed with her perceived inability to establish clear ethical boundaries in her research (Lubet, 2015). Goffman's (2014) research was conducted overtly, with participants giving explicit consent. In contrast, researchers can adopt a covert role, where participants are unaware of the researcher's intent and perceive them as a community member. However, a disadvantage of a covert role is the potential for deception, leading participants to feel betrayed when they discover they are being observed without permission. Covert studies are carefully designed following research ethics guidelines to minimize harm to those being observed. Participatory Action Research (PAR) Participatory action research (PAR) is considered a highly suitable methodology for researching marginalized or oppressed communities. What sets PAR apart is the active involvement of participants as collaborators in the research process. Participants contribute to formulating meaningful research questions and provide input on data collection methods. PAR benefits from the insider perspective of collaborators and gains community buy-in. The blurring of boundaries between researchers and community members, along with power-sharing, fosters a sense of involvement and empowerment among participants. PAR is not a single method but a diverse "family of practices of living inquiry" with varying approaches, shaped by the active role of participants in defining research questions and design (LeCompte, 1995; Reason & Bradbury, 2008). The goal of Participatory Action Research (PAR) is to bring about social change, either by increasing awareness or implementing new social practices. Unlike traditional research, PAR goes beyond generating findings; it actively informs policy, practice, or the community's self-perception. The process, described by Kemmis and McTaggart (2008), is dynamic and responsive—a spiral of cycles involving self-reflection, planning for change, action and observation, reflection on key processes and consequences, and then initiating a new cycle through replanning. PAR is characterized by its iterative and engaged nature, emphasizing ongoing collaboration and impact on the communities involved (Brydon-Miller, 2001; Kemmis & McTaggart, 2008). Participatory Action Research (PAR) was employed to study the Aamjiwnaang First Nation Reserve situated in a heavily polluted area near Sarnia, Ontario. The research focused on the conflicts between the reserve residents and the provincial Ministry of Environment, responsible for regulating pollution in the area. Wiebe (2016) conducted the study using field immersion, participant observation, and 35 in-depth interviews to explore the ongoing impact of pollutants on the health and habitat of the residents. PAR facilitated active collaboration between the researcher and the community, allowing for a more engaged and impactful research process. Through her engagement with the community, Wiebe discovered that residents express a sense of community belonging that is both embodied and territorial. Drawing on the words of Anishinabek elder Mike Plain, Wiebe shares firsthand accounts of the experiences of those residing in the polluted area. Despite the toxic surroundings, residents convey a resilient spirit, as expressed by Mike Plain's statement: "I will continue to survive... in the midst of toxic surroundings, that touch my being.... I still feel vibrant and full of life... with contaminations that invade my space.... I still feel vibrant and full of life" (Wiebe, 2016, p. 29). This insight highlights the complex relationship residents have with their environment and the resilience they demonstrate in the face of adversity. When conducting research with Indigenous communities, ethical considerations are paramount, necessitating a historical understanding and cultural sensitivity. Due to the impact of colonization, Indigenous populations continue to face challenges, and employing standard research approaches without consideration for their culture and concerns can have serious negative implications. Such approaches may result in a disconnection from their culture, harm their relationship with the land, and damage family relations. Indigenous researchers advocate for more accurate and ethical methods that align with their cultures, such as storytelling. Storytelling is valued for linking Indigenous worldviews, shaping research approaches, theoretical frameworks, and epistemology, as it is seen as an integral part of Indigenous people's everyday experiences. In this context, storytelling serves as a political tool and decolonizing methodology, allowing a revisit of history from the viewpoint of Indigenous communities rather than the settler's perspective. Indigenous methodologies, including storytelling, provide a counternarrative to the Canadian state's notion of reconciliation (Datta, 2018; Corntassel et al., 2009; Smith, 2013). The Nuu-chah-nulth peoples, an Indigenous group in Canada, have a unique way of passing down their history and culture to future generations. They use haa-huu-pah, which are teaching stories or sacred living histories. These are not just entertaining tales or fairy tales for children. Instead, they are lived values that form the basis for Indigenous governance and regeneration. Archibald (2008b) outlined the four Rs of Indigenous research, reflecting traditional values and teachings guiding both the storyteller and the listener in Indigenous storywork. The four Rs are central to the research process and demand careful examination and reflection. Figure 2.5 provides a list of the four Rs and elucidates how each contributes to the Indigenous research context. The ability to incorporate and embody the principles of Indigenous research methods is what makes PAR a good choice among a diverse set of methods for research with Indigenous communities. Photovoice Photovoice is a participatory research approach that allows researchers to understand the lived experiences of marginalized social groups through the participants' own expression of those experiences. Participants use cameras to take control of the stories they want to share with researchers and how they frame those stories. This method provides participants with the opportunity to depict how they perceive themselves and their surroundings. For instance, in a study on Tibetan refugees in Canada and their settlement experiences, Logan and Murdie (2016) employed photovoice to examine the experiences of 11 women living in high-rise apartments in Parkdale, a Toronto neighborhood. Participants were invited to capture images of significant aspects in their surroundings and inside their apartments to illustrate what creating a new home in Toronto meant to them. Analysis of the photovoice data from the study on Tibetan refugees in Toronto revealed four central concerns among the women settling in the city. First, their priority was to create a comfortable home in their apartments. Second, they identified places, such as parks, where they could connect with nature. Third, it was crucial for them to celebrate their own culture and spirituality. Lastly, they established new connections with neighbors and community services. In a photovoice project, the purpose of the images is to stimulate dialogue and discussion about key themes depicted in the photographs. These images offer scholars a fresh perspective, allowing them to see the world from the standpoint of the participants (Wang et al., 1996). When conducting a photovoice study, researchers also need to be aware of several challenges. While it is easy to take large numbers of photos with digital cameras, the analysis of those photos is complex and involved (Logan & Murdie, 2016). Photographs provide rich data with multiple meanings, making it difficult for researchers to synthesize this information into a coherent narrative that remains accurate to the original photographs and conversations about the meaning of the images for the participants. Secondary Data Analysis Secondary data analysis involves the analysis and interpretation of existing data, which may have been previously collected by other scholars, institutions, or generated online by a global digital public. This data can take written or visual forms, and the authors may be individuals or institutions. Examples include diaries, letters, and photographs, which offer firsthand accounts of past events and can provide direct insight into social relations and phenomena. Institutional Data Secondary data analysis can involve institutional documents, such as government documents, which offer insights into the operations of institutions and their impact on social life. Canadian sociologists often rely on government documents stored by Library and Archives Canada, including procedures, ministerial emails, and parliamentary debates. For instance, the final report of the National Inquiry on Missing and Murdered Indigenous Women and Girls, titled "Reclaiming Power and Place," can be analyzed further. The report, released in 2019, comprises 2,380 interviews and highlights persistent human and Indigenous rights violations as the root cause of violence against Indigenous women, girls, and 2SLGBTQQIA people. The term "2S" in the report emphasizes Indigenous sexuality and gender identities, representing "two-spirited," an umbrella term encompassing diverse sexualities and gender identities in Indigenous nations across the Americas (Pukall, 2020). The report serves as a basis for exploring various sociological questions, including issues of police bias, neglect in investigations, and the crafting of the report itself. Secondary data analysis encompasses various types, including the examination of existing datasets generated by institutions like Statistics Canada. While Statistics Canada provides comprehensive datasets, such as the census, for further analysis, these datasets have limitations. They rely on preexisting questions or content, potentially lacking the specific data required to address a particular research question. Table 2.3 offers a summary of the advantages and disadvantages of secondary data analysis. Big Data While data from individuals have historically been limited or time-consuming to gather, the internet has opened new avenues for data created by individuals. What happens in an internet minute? According to Lewis (2020), 4.1 million queries are posed on Google, 4.7 million videos viewed on YouTube, 59 million messages are exchanged on WhatsApp and Facebook Messenger, and 2.5 million snaps are created on Snapchat. User-generated content is just one aspect of the vast amount of data compiled by third parties, including automatic credit ratings and location data. This extensive collection of "big and broad data" provides a unique opportunity for understanding the social world. Social media research offers advantages over traditional methods, allowing researchers real-time access to global data. This enables insights into ongoing debates, public opinion, social activism, and evolving political attitudes. Unlike traditional research, social media data are not limited by geography and are produced in a naturalistic setting, reducing influences from study participation, such as reactivity (Quan-Haase & Sloan, 2017). Analysis based on social media data also presents new challenges for researchers with data preparation and interpretation. Determining the accuracy of data is no easy task and often data sets are incomplete, lacking critical demographic information such as a user’s real name, age, country of origin, and so on. This makes meaningful analysis tedious and complex. The study of social media data encompasses various quantitative and qualitative approaches (Sloan & Quan-Haase, 2017). In a specific investigation of online engagement, Yang et al. (2016) focused on the unfolding Twitter debate surrounding the European Court of Justice's ruling on the right to be forgotten. This ruling allows citizens to request removal of personal information from search engine result pages. The researchers collected 30,894 relevant tweets from 18,959 user accounts, visualizing interactions through graphs and key topics. The study revealed that the Twitter debate predominantly centered around the impact of the ruling on Google's operations, particularly how Google would implement the right to be forgotten. While the ruling empowered citizens with more self-determination, it also posed challenges for search engines in terms of operation and the information they provide to individuals searching the web. The Ethics of Conducting Research Ethical standards guide the conduct of research in all disciplines because scholars aim to minimize the potential risks to human participants associated with a study; these include physical and psychological harm. Sociologists have learned from past experiences to carefully evaluate potential harm to research participants. In the 1960s, Milgram conducted experiments on obedience to authority figures. Participants, acting as "teachers," were instructed to administer electric shocks to a confederate labeled as the "learner," ranging from 15 to 450 volts. Despite expressing initial reluctance, many participants followed orders to administer high-voltage shocks when instructed by an authority figure in a white lab coat. No shocks were given, and the learner, a confederate named Mr. Wallace, only pretended to be in pain as part of the research deception. The Milgram experiments, while yielding famous findings, came at a significant cost to the participants who agreed to take part. The experiments breached the trust of participants by deceiving them into thinking they had administered potentially harmful electric shocks to another person. This deception led to distress and anxiety among many participants. Trust is deemed essential in research, and Figure 2.7 outlines key motivations emphasizing the importance of trust in the participant-researcher relationship. In Canadian higher education institutions, it is standard practice for studies involving human participants to undergo careful ethical scrutiny. As part of this process, participants are provided with a letter of information before the study begins, detailing the study's purpose, procedures, and any potential risks. This information allows participants to make an informed decision about whether to participate, and this decision-making process is known as informed consent. Informed consent requires potential participants to comprehend the research topic, their role, and their rights. They must also be aware of potential risks associated with participation. Voluntary participation is crucial to avoid coercion, defined as the use of persuasion or force to convince someone to participate in the study. Coercion may involve hidden forms of persuasion or threats. Debriefing is a crucial component of ethical research practices. In certain studies, participants may not be fully informed about the nature of the study beforehand to prevent alterations in their behavior. This withholding of information aims to avoid reactivity. However, after the study is completed, scholars are obligated to inform participants about the true nature of the study and any deception that occurred. Debriefing is essential as it helps participants understand what happened during the study. The vast amounts of data generated daily by internet and mobile device users present new research opportunities. This data revolution necessitates a reevaluation of how sociologists engage with human participants, especially as traditional ethical barriers no longer fully apply to data collection from social media platforms like Twitter, Instagram, and YouTube. The text highlights a 2014 study (Goel, 2014) described in Box 2.5, which breached ethical standards, prompting a call for further discussions on the ethical expectations of research involving social media data. SOCIOLOGY 2.0 2.5 | The Facebook Experiment: Do Researchers Need to Ask for Consent to Study Facebook Interactions? The Facebook experiment, conducted by Kramer et al. in 2014, raised ethical concerns regarding research in a digital society. The experiments aimed to challenge the notion that Facebook use is associated with negative mental health outcomes. Previous research had suggested that social comparison played a role in the relationship between Facebook use and depressive symptoms, indicating that observing friends having a good time on Facebook could contribute to feelings of inadequacy and low self-esteem. The week-long Facebook experiment conducted from January 11 to 18, 2012, manipulated the exposure of users to positive (condition 1) and negative (condition 2) emotions in their news feed, without their awareness of the manipulation. While the study aimed to challenge the connection between Facebook content and negative emotions, ethical concerns were raised within the research community and media regarding the study design. Notably, three standard ethical research practices were violated: participants were not provided with an information letter explaining the study's purpose and nature, there was no informed consent from participants, and no debriefing occurred about the experimental design and its intended effect after the study's completion. The Facebook experiment has received much criticism because it ignored ethical practices that are standard in research. This led to an outcry in the media regarding the ethical practices of big data analytics and a call for increased transparency, greater communication with research participants, and more care in the design of large-scale experiments (Sloan & Quan-Haase, 2017). --- Research Ethics Boards (REB) A crucial oversight institution for research involving human participants is the research ethics board or ethics review board (REB/ERB). These boards aim to ensure that research studies adhere to the guidelines set forth in the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans. This statement is a collaborative policy developed by Canada's three major federal research agencies, outlining the standards for research in Canada. The policy serves to safeguard individuals in Canada from potential harms and risks arising from research activities. Every study conducted at higher education institutions, including those as part of class exercises, undergoes review by a Research Ethics Board (REB). The REB, comprised of experts, meticulously assesses the research design for its ethical integrity. Essential components of all ethics protocols include a letter of information, informed consent, details about the research design, an assessment of potential risks and benefits to participants, and information emphasizing voluntary participation. Research guidelines and best practices play a crucial role in safeguarding vulnerable populations like children, pregnant women, and prisoners. Researchers planning projects that involve data collection from individuals must be well-versed in the pertinent guidelines. For instance, studies involving Indigenous people should adhere to ethical guidelines that encompass intellectual, physical, emotional, and spiritual dimensions of knowledge in interconnected relationships with people, places, and the natural environment. List of Key Terms Bias-Any opinion, characteristic, or attitude of a researcher that can influence any part of the research process, such as interpretation of the data. Census-A recurring and official count of a particular population, used to systematically gather and record information about the members of the population. Computational Social Sciences-The use of approaches such as machine learning to collect and analyze research data with unprecedented breadth, depth, and scale. Correlation-A statistical technique that assesses how strongly pairs of variables are linearly associated and whether the association is positive or negative. Informed Consent-Permission from participants to take part in a research study after they have received details about it, obtained prior to their involvement in the study. Population-The complete group of units to which the results of a study are to be generalized. Units can be anything from individuals, animals, or objects to businesses or websites. Reactivity-People under observation changing their usual or typical behaviour because they know that they are being observed. Reliability-The degree to which findings can be replicated. In qualitative work, reliability is often expressed in terms of trustworthiness and authenticity. Research design-The blueprint of the study, which includes the study type, research question, hypotheses, variables, data collection methods, and statistical analysis plan. Sample-A subset of the population of interest in a study, in which the number of participants is reduced to a manageable size. Saturation-A method used to confirm that sufficient and valuable data have been collected to support the findings of a study. Social research methods-A wide range of techniques for and approaches to learning about the social world following a plan or research design. Standpoint theory-The theory that individuals view society from different social locations depending on their past experiences and their status and position. Statistics-A branch of mathematics concerned with the collection, analysis, interpretation, and representation of numerical data. Triangulation-A technique used by researchers to determine validity in their studies by gathering data from multiple sources. Validity-The extent to which findings are an accurate reflection of the social world.

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