It is important to consider what kinds of data you need to achieve your research goals, as this can help you identify a methodologyMethodologyThe theoretical framework that informs how a researcher approaches their work and what methods are used to collect data. that is best suited. By thinking through the form the answers to your research questions will take, you can work backward to choose a methodology appropriate for your project and put a plan into practice. For the purposes of this lesson, we’ll explore three broad categories of research outcomes: explanation and prediction, exploration and understanding, and critique. Each type of outcomes described below includes examples of published literature.
(See Table 1 below for summary of research outcomes for different types of methods.)
You will likely notice that some potential methodologies appear in multiple categories of research outcomes. Methodologies are not static and prescriptive to-do lists but instead are collections of techniques for gathering and analyzing data based on a set of epistemological and ontological assumptions (Staller 2013). The researcher has the power to make methodological decisions that they believe will be accepted by the communities in which they will share their work. This power is a double-edged sword; as the researcher there are few singular answers about how to proceed; however, you’ll need to make, and explain, a series of choices that add up to a coherent methodological approach.
1. Research Outcome Category 1: Explanation and Prediction
Many research projects are intended to offer an explanation of the cause of a situation or the relationship between two or more concepts and to make predictions about what we can expect to happen in similar situations moving forward. This sort of outcome may be what you think of when you imagine science as taught in K-12 education and many academic disciplines.
Researchers working toward this type of outcome will often value objectivity and make efforts to limit the impact of their own position and situation on findingsResultsThe section of a research article where researchers share the results from the research. This section takes the results and directly connects them to the research questions or hypotheses posed at the start of the article. Also can be called “Findings.” , with an eye toward developing generalizable findings that apply beyond the site in which data is collected. While not always clearly stated, research produced using one of these methodologies is based on the assumption that a single knowable reality can be found through the application of proper data collection and analysis. This is known as positivism, though many scholars now subscribe to post-positivism, which acknowledges that our understanding of this truth is bound to be imperfect due to the imperfect and biased nature of human researchers. Researchers who make explanatory or predictive claims are often expected to share their research data so that other researchers or reviewers can assess the fit of the data and analysis techniques for the research outcomes. If you will be expected to share your data, your data managementData managementThe ways a researcher collects, organizes, stores, and accesses data they collect for research. Creating a data management plan allows a researcher to know what data they will be collecting and how they will store and organize it during the research project. plan for your research will include ensuring your data protects confidentiality (where applicable) and is formatted in a way that supports sharing through standard research formats.
Of course, the increased sharing of research data means that you may also be able to use other researchers’ existing data for your own research. Large scale and numeric data are widely available in data repositories. You may be able to identify data relevant to your research question through university or governmental data portals or data curation organizations like ICPSR and IMLS.
Using existing data for research limits the time spent in the stage of data collection but offers its own particular challenges. Your work is based on the research design and decision-making process of other scholars who may have different ethical and epistemological points of view. Shared data files are distilled products representing a complex, and likely messy, process of data collection and cleaning. As a secondary data researcher, you have limited access to this process and can only ask questions that comport with the data as it is provided.
Examples of Explanatory and Predictive Studies:
In their content analysis of 18 academic library systematic reviewSystematic reviewA type of scholarly work where all evidence/primary research on a certain topic or idea is identified, selected, and evaluated. Documentation is provided in order for other researchers to conduct the same search and see the same results. Often used in health science and medical disciplines and a librarian is a key contributor to this kind of scholarly collaboration. guides, Lee et al. (2021) counted which resources were included in the guides and to which stage of the systematic review process the guides referred. Outcomes for the study are statistics on the stages presented (Lee et al. 2021, 69). The findings offer an explanation for what aspects of the systematic review process librarians address when developing guides. Beth Wartman (2012) offers an example of a patron-use survey at a public library. Participants completed a survey with questions about why they had visited the library and the types of spaces they valued within the library building. Wartman reports frequencies and percentages for the quantitative survey questions, such as the number of other people who visited the library with each participant (11) and the most important reason for coming to the library (8). In reading this study, we are meant to see the findings as explaining why and how people come to the library (among other questions).
Common methodologies for explanatory and predictive outcomes:
Surveys
Statistical analysis of quantitative data (e.g. budgets, hiring, collections, etc.)
Experiments
Case studies
Content analysis
Text data miningText data miningA methodology where high-quality information is found through analyzing a set of text. This data is analyzed to find patterns and come to new conclusions. Text data mining can be used to arrive at explanatory or predictive outcomes in a research project.
Research Outcome Category 2 : Exploration and contextual understanding
In many cases, research is used to help us develop a stronger understanding of complex experiences and situations. Researchers will often collect more in-depth data when their study involves a smaller number of subjects or cases in comparison to explanatory or predictive research; for instance, they may conduct in-depth interviews or engage in a series of observations within a relevant setting.
In fields that value exploratory/understanding knowledge, researchers are often expected to be reflexive about how their social position influences the process of data collection and analysis (Reyes 2020). This practice is based on the assumption that research can produce a version of reality from a particular point of view. Other researchers using the same methodological approach, or even the same data and analysis techniques, may come to different conclusions. This type of research is often described as interpretive and contrasted with the objective research produced by explanatory or predictive research.
Methodologies that are used to explore and understand phenomena frequently make use of qualitative data produced through interviews, focus groups, oral histories, or document analysis. Outside of highly structured interviews or open-ended survey data, researchers will be faced with the task of organizing this voluminous data in a way that facilitates analysis in the chosen methodology. For many projects, the use of standard office software (word processing documents and spreadsheets) will be sufficient, i.e., Ose (2016) . For projects that are larger in scale or use multiple types of data, researchers may decide to use programs developed specifically for qualitative analysis, such as NVivo or Taguette, that facilitate sophisticated coding and retrieval of data. These tools are powerful but can be expensive to acquire and time-consuming to learn and adapt to the project needs (O’Kane 2020).
Common methodologies for exploratory and contextual outcomes:
Thematic Analysis
(Participatory) Action Research
Phenomenology
(Auto) EthnographyEthnographyOriginating from the anthropology discipline, these qualitative research methods aim to understand thoughts, experiences, and actions of a culture through observation and interpretation.
Discourse Analysis
Narrative Analysis
Grounded Theory
Examples of exploratory and contextualizing studies
Maureen Babb (2021) conducted a thematic analysis of interviews with Canadian librarians and non-library faculty about the experiences of conducting research. Babb identified eight themes in the interview data that show the challenges faced by librarians conducting research and the potential for LISLibrary and Information ScienceAn interdisciplinary field that examines how physical and digital information is organized, accessed, collected, managed, disseminated and used, particularly in library settings. researchers to facilitate collaboration and connection with those outside the library.
Using a series of three interviews with 10 doctoral students, Moore and Singley (2019) identified three major themes in the doctoral students’ experiences using information, including the vital role of individual relationships for pointing students toward information vital to their research.
Research Outcome Category 3: Critique
Critical researchers use methodologies to identify oppressive systems and structures in society in pursuit of enacting change in those systems (Davis and Saunders 2022). The methodologies used will be similar to those used in both explanatory/predictive- and exploratory/understanding-based work but with an explicit ideological commitment to showing how relations of power shape access to resources and perpetuate oppression (Honma and Chu 2018; Schroeder 2014). Critical researchers may also turn their attention to the ways that their own work is shaped by and maintains oppressive structures of knowledge creation (Patin et al. 2021).
Data management considerations for critical research are similar to those for both explanatory/predictive and explanatory/understanding approaches, whether data is re-used or generated. Critical researchers may bring their ideological commitments to questions of data use and re-use and ask critical questions about how data is constructed and used within social systems and structures, e.g., Markham (2013).
Examples of Critique Studies
Anna Lundh (2021) uses several critical theories, including Critical Disabilities Studies and Critical Reading Studies, to conduct a discourse analysis of interviews with blind or vision-impaired individuals about the definition of reading. Lundh’s analysis shows how the construction of “real” reading often excludes the use of audio technology for reading, a presumption that blind and low-vision readers actively resist.
Using multiple tenets of Critical Race TheoryCritical race theoryA theoretical framework that race is a social construct and is structurally embedded in our legal systems and policies. The term was coined by Kimberlé Crenshaw and comes out of scholarship in legal studies. , Kumasi and colleagues (2020) identified ways that titles in a discovery platform for young readers are classified and limits teachers’ and students’ ability to find titles that address race and ethnicity. For example, the teachers interviewed found few resultsResultsThe section of a research article where researchers share the results from the research. This section takes the results and directly connects them to the research questions or hypotheses posed at the start of the article. Also can be called “Findings.” when searching for concepts like race or racism, apparently based on the assumption that such language is not part of the language of middle grade students’ daily lives. In the study, the researchers propose additional ways of classifying titles that would facilitate discovery of works by authors from marginalized communities and that address topics like white privilege and racism.
Table 1: Types of research outcomes
Type of outcome
Explain or predict
Explore or understand
Critique in pursuit of change
What the outcome does
Explains relationships between concepts or predicts future actions
Provides insights into experience and phenomena in a particular context
Identifies how power and structures of oppression create and sustain phenomena
Assumed role of research and reality (ontology and epistemology — see IMG 1 or Staller (2013) for more)
Researcher seeks to find a knowable reality
Researcher constructs a version of reality while remaining cognizant of their partial viewpoint and that there are multiple potential realities
Research constructs a version of reality, with recognition that their viewpoint is partial and shaped by power and political structures
Potential data types
– Survey data – Experimental data – Budget or collections data – Large text data sets – Images or videos
– Interview or focus groupfocus groupA research method that takes a small group of people and has a focused discussion with them. This discussion revolves around a specific topic, the participants have something in common that brings them into the same space, and do not have any pre-existing relationships with one another. A focus group also has a moderator who helps to facilitate the discussion. recordings and transcripts – Field notes and observations – Oral history recordings or transcripts – Images or videos
Any type of data can be analyzed using a critical lens. In practice, data types and methodologies tend to overlap with exploratory or understanding-based outcomes
Potential methodologies
– Experiment Statistical analysis or modeling – Grounded Theory – Content Analysis
– Thematic Analysis (Participatory) Action Research – Phenomenology – Ethnography – Discourse Analysis – Grounded Theory – Narrative Analysis Interpretive and critical methodologies often share approaches to data collection and analysis, with critical approaches frequently drawing on critical social theories such as Critical Race Theory, Feminist Theory, or Queer Theory)
Created by Jessica Hagman for LibParlor Online Learning, 2023.
Topic 1 References
Babb, Maureen. “Faculty and Librarian Perceptions of Librarians as Researchers: Results from Semi-Structured Interviews.” Canadian Journal of Academic Librarianship 7 (2021): 1–19. doi.org/10.33137/cjalrcbu.v7.36874.
Davis, Bradley, and Daniel Saunders. “Critical Quantitative ResearchQuantitative researchResearch that collects and analyzes numerical data in order to test a hypothesis, discover correlations, or describe characteristics.
: Foreclosing Criticality within Education.” Critical Education 13, 2 (2022): 44–54. doi.org/10.14288/ce.v13i2.186601.
Honma, Todd M., and Clara M. Chu. “PositionalityPositionalityThe identity of us as a researcher as it relates to the social and political context of a research study. Our positionality is based on our past experiences and shapes how you approach the research process., Epistemology, and New Paradigms for LIS: A Critical Dialog with Clara M. Chu.” In Pushing the Margins: Women of Color and Intersectionality in LIS, edited by Rose L. Chou and Annie Pho, 447–65. Series on Critical Race Studies and Multiculturalism in LIS, no. 3. Sacramento, CA: Library Juice Press, 2018.
Karcher, Sebastian, Kirilova, Dessislava, Pagé, Christiane, and Nic Weber. “How Data Curation Enables Epistemically Responsible Reuse of Qualitative Data.” The Qualitative Report 26, 6 (2021): 1996–2010. doi.org/10.46743/2160-3715/2021.5012.
Kumasi, Kafi D., Jimes, Cynthia, Godwin, Amee Evans, Petrides, Lisa A., and Anastasia Karaglani. “A Preliminary Study Interrogating the Cataloging and Classification Schemes of a K-12 Book Discovery Platform through a Critical Race Theory Lens.” Open Information Science 4, 1 (2020): 106–21. doi.org/10.1515/opis-2020-0009.
Lee, Jennifer K., Hayden, Alix, Ganshorn, Heather, and Helen Pethrick. “A Content Analysis of Systematic Review Online Library Guides.” Evidence Based Library and Information Practice 16, 1 (2021): 60–77. oi.org/10.18438/eblip29819.
Lundh, Anna. “‘I Can Read, I Just Can’t See’: A Disability Rights-Based Perspective on Reading by Listening.” Journal of Documentation 78, 7 (2021): 176–91. doi.org/10.1108/JD-10-2020-0169.
Markham, Annette N. “Undermining ‘Data’: A Critical Examination of a Core Term in Scientific Inquiry.” First Monday 18, 10 (2013). doi.org/10.5210/fm.v18i10.4868.
Moore, Monica, and Emily Singley. “Understanding the Information Behaviors of Doctoral Students: An Exploratory Study.” portal: Libraries and the Academy 19, 2 (2019): 279–93. doi.org/10.1353/pla.2019.0016.
O’Kane, Paula. “Demystifying CAQDAS: A Series of Dilemmas.” In Advancing Methodological Thought and Practice, edited by T. Russell Crook, Jane Lê, and Anne D Smith, Research Methodology in Strategy and Management. Emerald Publishing Limited. 12 (2020):133–52. doi.org/10.1108/S1479-838720200000012020.
Ose, Solveig Osborg. “Using Excel and Word to Structure Qualitative Data.” Journal of Applied Social Science 10, 2 (2016): 147–62. doi.org/10.1177/1936724416664948.
Patin, Beth, Oliphant, Tami, Allard, Danielle, Gray, LaVerne, Ivy Clarke, Rachel, Tacheva, Jasmina, and Kayla Lar-Son. “At the Margins of Epistemology: Amplifying Alternative Ways of Knowing in Library and Information ScienceLibrary and Information ScienceAn interdisciplinary field that examines how physical and digital information is organized, accessed, collected, managed, disseminated and used, particularly in library settings..” Proceedings of the Association for Information Science and Technology 58, 1 (2021): 630–33. doi.org/10.1002/pra2.515.
Reyes, Victoria. “Ethnographic Toolkit: Strategic Positionality and Researchers’ Visible and Invisible Tools in Field Research.” Ethnography 21, 2 (2020): 220–40. doi.org/10.1177/1466138118805121.
Schroeder, Robert. “Exploring Critical and Indigenous ResearchIndigenous researchAn approach to research that is grounded in Indigenous nations, communities, and knowledge systems. Indigenous research may also be conducted by Indigenous scholars. Methods with a Research Community: Part II – The Landing.” In the Library with the Lead Pipe, 1–30. December 3, 2014. https://www.inthelibrarywiththeleadpipe.org/2014/exploring-the-landing/
Staller, Karen M. “Epistemological Boot Camp: The Politics of Science and What Every Qualitative Researcher Needs to Know to Survive in the Academy.” Qualitative Social Work: Research and Practice 12, 4 (2013): 395–413. doi.org/10.1177/1473325012450483.
Wortman, Beth. “What Are They Doing and What Do They Want: The Library Spaces Customer Survey at Edmonton Public Library.” Partnership: The Canadian Journal of Library and Information Practice and Research 7, 2 (2012). doi.org/10.21083/partnership.v7i2.1967.
Identifying Research Outcomes
It is important to consider what kinds of data you need to achieve your research goals, as this can help you identify a methodologyMethodology The theoretical framework that informs how a researcher approaches their work and what methods are used to collect data. that is best suited. By thinking through the form the answers to your research questions will take, you can work backward to choose a methodology appropriate for your project and put a plan into practice. For the purposes of this lesson, we’ll explore three broad categories of research outcomes: explanation and prediction, exploration and understanding, and critique. Each type of outcomes described below includes examples of published literature.
(See Table 1 below for summary of research outcomes for different types of methods.)
You will likely notice that some potential methodologies appear in multiple categories of research outcomes. Methodologies are not static and prescriptive to-do lists but instead are collections of techniques for gathering and analyzing data based on a set of epistemological and ontological assumptions (Staller 2013). The researcher has the power to make methodological decisions that they believe will be accepted by the communities in which they will share their work. This power is a double-edged sword; as the researcher there are few singular answers about how to proceed; however, you’ll need to make, and explain, a series of choices that add up to a coherent methodological approach.
1. Research Outcome Category 1: Explanation and Prediction
Many research projects are intended to offer an explanation of the cause of a situation or the relationship between two or more concepts and to make predictions about what we can expect to happen in similar situations moving forward. This sort of outcome may be what you think of when you imagine science as taught in K-12 education and many academic disciplines.
Researchers working toward this type of outcome will often value objectivity and make efforts to limit the impact of their own position and situation on findingsResults The section of a research article where researchers share the results from the research. This section takes the results and directly connects them to the research questions or hypotheses posed at the start of the article. Also can be called “Findings.” , with an eye toward developing generalizable findings that apply beyond the site in which data is collected. While not always clearly stated, research produced using one of these methodologies is based on the assumption that a single knowable reality can be found through the application of proper data collection and analysis. This is known as positivism, though many scholars now subscribe to post-positivism, which acknowledges that our understanding of this truth is bound to be imperfect due to the imperfect and biased nature of human researchers. Researchers who make explanatory or predictive claims are often expected to share their research data so that other researchers or reviewers can assess the fit of the data and analysis techniques for the research outcomes. If you will be expected to share your data, your data managementData management The ways a researcher collects, organizes, stores, and accesses data they collect for research. Creating a data management plan allows a researcher to know what data they will be collecting and how they will store and organize it during the research project. plan for your research will include ensuring your data protects confidentiality (where applicable) and is formatted in a way that supports sharing through standard research formats.
Of course, the increased sharing of research data means that you may also be able to use other researchers’ existing data for your own research. Large scale and numeric data are widely available in data repositories. You may be able to identify data relevant to your research question through university or governmental data portals or data curation organizations like ICPSR and IMLS.
Using existing data for research limits the time spent in the stage of data collection but offers its own particular challenges. Your work is based on the research design and decision-making process of other scholars who may have different ethical and epistemological points of view. Shared data files are distilled products representing a complex, and likely messy, process of data collection and cleaning. As a secondary data researcher, you have limited access to this process and can only ask questions that comport with the data as it is provided.
Examples of Explanatory and Predictive Studies:
In their content analysis of 18 academic library systematic reviewSystematic review A type of scholarly work where all evidence/primary research on a certain topic or idea is identified, selected, and evaluated. Documentation is provided in order for other researchers to conduct the same search and see the same results. Often used in health science and medical disciplines and a librarian is a key contributor to this kind of scholarly collaboration. guides, Lee et al. (2021) counted which resources were included in the guides and to which stage of the systematic review process the guides referred. Outcomes for the study are statistics on the stages presented (Lee et al. 2021, 69). The findings offer an explanation for what aspects of the systematic review process librarians address when developing guides. Beth Wartman (2012) offers an example of a patron-use survey at a public library. Participants completed a survey with questions about why they had visited the library and the types of spaces they valued within the library building. Wartman reports frequencies and percentages for the quantitative survey questions, such as the number of other people who visited the library with each participant (11) and the most important reason for coming to the library (8). In reading this study, we are meant to see the findings as explaining why and how people come to the library (among other questions).
Common methodologies for explanatory and predictive outcomes:
Research Outcome Category 2 : Exploration and contextual understanding
In many cases, research is used to help us develop a stronger understanding of complex experiences and situations. Researchers will often collect more in-depth data when their study involves a smaller number of subjects or cases in comparison to explanatory or predictive research; for instance, they may conduct in-depth interviews or engage in a series of observations within a relevant setting.
In fields that value exploratory/understanding knowledge, researchers are often expected to be reflexive about how their social position influences the process of data collection and analysis (Reyes 2020). This practice is based on the assumption that research can produce a version of reality from a particular point of view. Other researchers using the same methodological approach, or even the same data and analysis techniques, may come to different conclusions. This type of research is often described as interpretive and contrasted with the objective research produced by explanatory or predictive research.
Methodologies that are used to explore and understand phenomena frequently make use of qualitative data produced through interviews, focus groups, oral histories, or document analysis. Outside of highly structured interviews or open-ended survey data, researchers will be faced with the task of organizing this voluminous data in a way that facilitates analysis in the chosen methodology. For many projects, the use of standard office software (word processing documents and spreadsheets) will be sufficient, i.e., Ose (2016) . For projects that are larger in scale or use multiple types of data, researchers may decide to use programs developed specifically for qualitative analysis, such as NVivo or Taguette, that facilitate sophisticated coding and retrieval of data. These tools are powerful but can be expensive to acquire and time-consuming to learn and adapt to the project needs (O’Kane 2020).
Common methodologies for exploratory and contextual outcomes:
Examples of exploratory and contextualizing studies
Maureen Babb (2021) conducted a thematic analysis of interviews with Canadian librarians and non-library faculty about the experiences of conducting research. Babb identified eight themes in the interview data that show the challenges faced by librarians conducting research and the potential for LISLibrary and Information Science An interdisciplinary field that examines how physical and digital information is organized, accessed, collected, managed, disseminated and used, particularly in library settings. researchers to facilitate collaboration and connection with those outside the library.
Using a series of three interviews with 10 doctoral students, Moore and Singley (2019) identified three major themes in the doctoral students’ experiences using information, including the vital role of individual relationships for pointing students toward information vital to their research.
Research Outcome Category 3: Critique
Critical researchers use methodologies to identify oppressive systems and structures in society in pursuit of enacting change in those systems (Davis and Saunders 2022). The methodologies used will be similar to those used in both explanatory/predictive- and exploratory/understanding-based work but with an explicit ideological commitment to showing how relations of power shape access to resources and perpetuate oppression (Honma and Chu 2018; Schroeder 2014). Critical researchers may also turn their attention to the ways that their own work is shaped by and maintains oppressive structures of knowledge creation (Patin et al. 2021).
Data management considerations for critical research are similar to those for both explanatory/predictive and explanatory/understanding approaches, whether data is re-used or generated. Critical researchers may bring their ideological commitments to questions of data use and re-use and ask critical questions about how data is constructed and used within social systems and structures, e.g., Markham (2013).
Examples of Critique Studies
Anna Lundh (2021) uses several critical theories, including Critical Disabilities Studies and Critical Reading Studies, to conduct a discourse analysis of interviews with blind or vision-impaired individuals about the definition of reading. Lundh’s analysis shows how the construction of “real” reading often excludes the use of audio technology for reading, a presumption that blind and low-vision readers actively resist.
Using multiple tenets of Critical Race TheoryCritical race theory A theoretical framework that race is a social construct and is structurally embedded in our legal systems and policies. The term was coined by Kimberlé Crenshaw and comes out of scholarship in legal studies. , Kumasi and colleagues (2020) identified ways that titles in a discovery platform for young readers are classified and limits teachers’ and students’ ability to find titles that address race and ethnicity. For example, the teachers interviewed found few resultsResults The section of a research article where researchers share the results from the research. This section takes the results and directly connects them to the research questions or hypotheses posed at the start of the article. Also can be called “Findings.” when searching for concepts like race or racism, apparently based on the assumption that such language is not part of the language of middle grade students’ daily lives. In the study, the researchers propose additional ways of classifying titles that would facilitate discovery of works by authors from marginalized communities and that address topics like white privilege and racism.
Table 1: Types of research outcomes
– Experimental data
– Budget or collections data
– Large text data sets
– Images or videos
– Field notes and observations
– Oral history recordings or transcripts
– Images or videos
– Grounded Theory
– Content Analysis
– Phenomenology
– Ethnography
– Discourse Analysis
– Grounded Theory
– Narrative Analysis
Interpretive and critical methodologies often share approaches to data collection and analysis, with critical approaches frequently drawing on critical social theories such as Critical Race Theory, Feminist Theory, or Queer Theory)
Topic 1 References
Babb, Maureen. “Faculty and Librarian Perceptions of Librarians as Researchers: Results from Semi-Structured Interviews.” Canadian Journal of Academic Librarianship 7 (2021): 1–19. doi.org/10.33137/cjalrcbu.v7.36874.
Davis, Bradley, and Daniel Saunders. “Critical Quantitative ResearchQuantitative research Research that collects and analyzes numerical data in order to test a hypothesis, discover correlations, or describe characteristics. : Foreclosing Criticality within Education.” Critical Education 13, 2 (2022): 44–54. doi.org/10.14288/ce.v13i2.186601.
Honma, Todd M., and Clara M. Chu. “PositionalityPositionality The identity of us as a researcher as it relates to the social and political context of a research study. Our positionality is based on our past experiences and shapes how you approach the research process., Epistemology, and New Paradigms for LIS: A Critical Dialog with Clara M. Chu.” In Pushing the Margins: Women of Color and Intersectionality in LIS, edited by Rose L. Chou and Annie Pho, 447–65. Series on Critical Race Studies and Multiculturalism in LIS, no. 3. Sacramento, CA: Library Juice Press, 2018.
Karcher, Sebastian, Kirilova, Dessislava, Pagé, Christiane, and Nic Weber. “How Data Curation Enables Epistemically Responsible Reuse of Qualitative Data.” The Qualitative Report 26, 6 (2021): 1996–2010. doi.org/10.46743/2160-3715/2021.5012.
Kumasi, Kafi D., Jimes, Cynthia, Godwin, Amee Evans, Petrides, Lisa A., and Anastasia Karaglani. “A Preliminary Study Interrogating the Cataloging and Classification Schemes of a K-12 Book Discovery Platform through a Critical Race Theory Lens.” Open Information Science 4, 1 (2020): 106–21. doi.org/10.1515/opis-2020-0009.
Lee, Jennifer K., Hayden, Alix, Ganshorn, Heather, and Helen Pethrick. “A Content Analysis of Systematic Review Online Library Guides.” Evidence Based Library and Information Practice 16, 1 (2021): 60–77. oi.org/10.18438/eblip29819.
Lundh, Anna. “‘I Can Read, I Just Can’t See’: A Disability Rights-Based Perspective on Reading by Listening.” Journal of Documentation 78, 7 (2021): 176–91. doi.org/10.1108/JD-10-2020-0169.
Markham, Annette N. “Undermining ‘Data’: A Critical Examination of a Core Term in Scientific Inquiry.” First Monday 18, 10 (2013). doi.org/10.5210/fm.v18i10.4868.
Moore, Monica, and Emily Singley. “Understanding the Information Behaviors of Doctoral Students: An Exploratory Study.” portal: Libraries and the Academy 19, 2 (2019): 279–93. doi.org/10.1353/pla.2019.0016.
O’Kane, Paula. “Demystifying CAQDAS: A Series of Dilemmas.” In Advancing Methodological Thought and Practice, edited by T. Russell Crook, Jane Lê, and Anne D Smith, Research Methodology in Strategy and Management. Emerald Publishing Limited. 12 (2020):133–52. doi.org/10.1108/S1479-838720200000012020.
Ose, Solveig Osborg. “Using Excel and Word to Structure Qualitative Data.” Journal of Applied Social Science 10, 2 (2016): 147–62. doi.org/10.1177/1936724416664948.
Patin, Beth, Oliphant, Tami, Allard, Danielle, Gray, LaVerne, Ivy Clarke, Rachel, Tacheva, Jasmina, and Kayla Lar-Son. “At the Margins of Epistemology: Amplifying Alternative Ways of Knowing in Library and Information ScienceLibrary and Information Science An interdisciplinary field that examines how physical and digital information is organized, accessed, collected, managed, disseminated and used, particularly in library settings..” Proceedings of the Association for Information Science and Technology 58, 1 (2021): 630–33. doi.org/10.1002/pra2.515.
Reyes, Victoria. “Ethnographic Toolkit: Strategic Positionality and Researchers’ Visible and Invisible Tools in Field Research.” Ethnography 21, 2 (2020): 220–40. doi.org/10.1177/1466138118805121.
Schroeder, Robert. “Exploring Critical and Indigenous ResearchIndigenous research An approach to research that is grounded in Indigenous nations, communities, and knowledge systems. Indigenous research may also be conducted by Indigenous scholars. Methods with a Research Community: Part II – The Landing.” In the Library with the Lead Pipe, 1–30. December 3, 2014. https://www.inthelibrarywiththeleadpipe.org/2014/exploring-the-landing/
Staller, Karen M. “Epistemological Boot Camp: The Politics of Science and What Every Qualitative Researcher Needs to Know to Survive in the Academy.” Qualitative Social Work: Research and Practice 12, 4 (2013): 395–413. doi.org/10.1177/1473325012450483.
Wortman, Beth. “What Are They Doing and What Do They Want: The Library Spaces Customer Survey at Edmonton Public Library.” Partnership: The Canadian Journal of Library and Information Practice and Research 7, 2 (2012). doi.org/10.21083/partnership.v7i2.1967.