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  • Writer's pictureKeidra Navaroli

Week 8 Notes

Personal Connections and Reflections:

Archival research represents one of the main types of main of research I will likely employ as a doctoral student. I appreciate Vogt et al's ever consistent breakdown of the research methods and examples. However, the chapters largely qualifies text-based records and information. As an art historian, I felt that outside of a brief mention of photography in chapter 5 of When to Use What Research Design, visual art (and other forms of qualitative expression) is ignored.


Citation

Vogt, W. Paul et al. When to Use What Research Design. New York: The Guilford Press, 2012.


Chapter 5 – When to Use Archival Designs

Key Points and Terms:

Archival or secondary data analysis refers to the review of data generated by other researchers or available sources. Archives are not neutral and reflect the interpretation of their makers. As a result, they are limited, incomplete, and biased.


If you cannot generate data useful for your own research, you select data generated by others.


There are five categories of archival research:

· Reviews of research literature, research synthesis, and meta analysis

o Can be conducted as an introductory review (most simplistic), systemic review (most common), research synthesis, or meta analysis (most complicated)

· Database archives

o Made available from public and semi-public statistical archives

o Can contain both quantitative and qualitative data

o Don't use irrelevant data or data that is too old (without contextualizing it)

· Organizational records

o Requires a high level of specificity

· Textual studies of documents

o Can be used to study three broad (overlapping) subjects: phenomena, texts, and context

· New media (internet resources)


Chapter 11 - Sampling from Archival Sources

Key Points and Quotes:

In archival research the researcher does the searching and the sampling


When collecting qualitative data, whether from archives or in other ways, researchers often refer to reaching the saturation point as the moment when it is no longer useful to collect data. It is the criterion for when you should stop collecting data.


There five categories of archival research correspond to different sampling techniques:

· Reviews of research literature, research synthesis, and meta analysis

o Always use more than one electronic database for searches

· Database archives

o Try to use this as much as possible and select variables and cases that are relevant to the research question

· Organizational records

o Use when the research question requires a selection of records rather than a study of all of them

· Textual studies of documents

o Use when source archives are very large or when studying a particular phenomenon

o Use computer assisted searching and sampling whenever possible and when you can compare software selection to those produced without software

· New media (internet resources)

o Researchers will use this most of the time now after a process of searching and narrowing the field of potential data sources


Sampling in archival research differs from other design methods in the following ways:

1) people do not have to be recruited, persuaded, or paid to participate in the study—as is not uncommon in survey, interview, and experimental research. Archival researchers need not seek permission from observational sites, survey respondents, interviewees, and experimental participants. Instead, the archival researcher usually downloads data from a website. 2) much archival research is inconceivable without computer- assisted searching for cases, whether the object of the search is research studies, variables in databases, organizational records, documents, or websites. 3) the number of cases is usually vastly greater in archival research. The sampling problem is not one of encouraging a sufficient number of interviewees, respondents, or participants to join and persist in the study. Rather, it is devising an appropriate rationale for selecting among many thousands of cases and hundreds of variables.


Chapter 17 - Ethics in Archival Research

Key Points and Quotes:

archival research tends to be less likely to be directly harmful to research participants. Often there is no human subject.


Ethical issues arise in each of the five categories of archival research:

· Reviews of research literature, research synthesis, and meta analysis

o Permission can be an issue

o There could be ethical dilemmas surrounding the collection of research using unethical methods

o Your research review could damage the article's reputation and you may have to decide whether and when you should become a whistle- blower when you discover plagiarized or other faulty sources.

· Database archives

o Most people involved in the primary research will be anonymous so risk of harm or privacy is minimal. Permission as consent will likely be needed.

· Organizational records

o while pseudonyms often work well to disguise the identity of individuals, it is more difficult to achieve anonymity and confidentiality in the case of institutions.

o accountability and freedom of information on the one side may clash with privacy on the other, particularly for those organizations that are private or that have some of the same rights as do “persons,” such as corporations.

Textual studies of documents

o Permission to use documents can be an issue

· New media (internet resources)

o Although internet info can be public, copyright can be an issue for researchers. Social media can also be problematic regarding privacy.


In archival research, the three most common gray areas are: when to blow the whistle on flawed or deceptive data documents or files; when to use ostensibly good data from a tainted source; and when to withhold an accurate and honest report because some interested parties think that the knowledge contained therein could do more harm than good.



Citation

Vogt, W. Paul et al. Selecting the Right Analysis for Your Data. New York: The Guilford Press, 2014.


Chapter 5 - Coding Archival Data

Key Points, Terms, and Quotes:

Coding archival data is almost always recoding or reclassifying

Types of archival research:

· (1) reviewing the research literature.

o Reviewing the research literature on a topic partly involves discovering a network of interrelated research sources, and those networks are increasingly Web based. Pooling the results of a set of research articles increases the power of conclusions by expanding the amount of data from which they are drawn.

o Systematic review is used frequently to refer to evidence- based practical applications, whereas research synthesis more often refers to basic research that is not necessarily tied to practical applications. They are similar in that the chief feature of both is that the researcher states in advance the procedures for finding, selecting, coding, and analyzing the data. Meta- analyses are a subtype: Meta-analyses are reviews/ syntheses that use quantitative methods to summarize and analyze quantitative data.

o the traditional/narrative review persists and remains influential. One reason is that obtaining broad knowledge of a field through traditional reading and thinking is usually a necessary preamble to conducting a meta- analysis or systematic review.

o Most commonly the theoretical review is a version of a traditional or narrative review, but with the specific purpose either of synthesizing previous theories or of generating new ones. Two types of theoretical reviews: The first focuses on understanding, synthesizing, and critiquing other theories, as when a social or political theorist reviews the works of other theorists. The second type involves reviewing empirical studies on a topic with the goal of identifying and devising a new explanation (theory) of empirical phenomena.

o Features of good coding include: relevance, redundancy, role, quality, and diversity.

· (2) using big data, including textual data and database archives

o Big data is “an amount of information impossible for one individual to code and analyze in less than a year without computer help.”

o Surveys (archives and tests) are an example of older big data. Most popular example: the Census (and a number of government associated organizations).

· (3) mining the new media, especially Web sources.

o Types include network analysis, blogs, and online social networks (OSNs)

o Studying a network starts with two basic kinds of data that have to be coded: nodes (or vertices) and links (a.k.a. ties, lines, or edges) that connect pairs of nodes.

o OSNs are "moving targets" that change. One advantage of studying OSNs is that, despite their changeability, it is comparatively easier to capture OSN data


Archival research is not exempt from interaction with the participants, but there can be a kind of delayed interaction between the users of OSNs and the researchers who study them. What each group does and learns can influence what the other does and learns.

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