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Archival Research
For the social scientist, archival research can be defined as the locating, evaluating, and systematic interpretation and analysis of sources found in archives.
Original source materials may be consulted and analyzed for purposes other than those for which they were originally collected—to ask new questions of old data, provide a comparison over time or between geographic areas, verify or challenge existing findings, or draw together evidence from disparate sources to provide a bigger picture.
For the social scientist, using archives may seem relatively unexciting compared to undertaking fieldwork, which is seen as fresh, vibrant, and essential for many researchers. Historical research methods and archival techniques may seem unfamiliar; for example, social scientists are not used to working with hand-break written sources that historians routinely consult. However, these methods should be viewed as complementary, not competing, and their advantages should be recognized for addressing certain research questions. Indeed, consulting archival sources enables the social scientist to both enhance and challenge the established methods of defining and collecting data.
What, then, are the types of sources to be found of interest to the social scientist? Archives contain official sources (such as government papers), organizational records, medical records, personal collections, and other contextual materials. Primary research data are also found, such as those created by the investigator during the research process, and include transcripts or tapes of interviews, field notes, personal diaries, observations, unpublished manuscripts, and associated correspondence. Many university repositories or special collections contain rich stocks of these materials. Archives also comprise the cultural and material residues of both institutional and theoretical or intellectual processes, for example, in the development of ideas within a key social science department.
However, archives are necessarily a product of sedimentation over the years—collections may be subject to erosion or fragmentation—by natural (e.g., accidental loss or damage) or manmade causes (e.g., purposive section or organizational disposal policies). Material is therefore subjectively judged to be worthy of preservation by either the depositor or archivist and therefore may not represent the original collection in its entirety. Storage space may also have had a big impact on what was initially acquired or kept from a collection that was offered to an archive.
Techniques for locating archival material are akin to excavation—what you can analyze depends on what you can find. Once located, a researcher is free to immerse himself or herself in the materials—to evaluate, review, and reclassify data; test out prior hypotheses; or discover emerging issues. Evaluating sources to establish their validity and reliability is an essential first step in preparing and analyzing archival data. A number of traditional social science analytic approaches can be used once the data sources are selected and assembled—for example, grounded theory to uncover patterns and themes in the data, biographical methods to document lives and ideas by verifying personal documentary sources, or content analysis to determine the presence of certain words or concepts within text.
Access to archives should not be taken for granted, and the researcher must typically make a prior appointment to consult materials and show proof of status. For some collections, specific approval must be gained in advance via the archivist.
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- Analysis of Variance
- Association and Correlation
- Association
- Association Model
- Asymmetric Measures
- Biserial Correlation
- Canonical Correlation Analysis
- Correlation
- Correspondence Analysis
- Intraclass Correlation
- Multiple Correlation
- Part Correlation
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- Pearson's Correlation Coefficient
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- Simple Correlation (Regression)
- Spearman Correlation Coefficient
- Strength of Association
- Symmetric Measures
- Basic Qualitative Research
- Basic Statistics
- F Ratio
- N(n)
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- X¯
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- Alternative Hypothesis
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- Data
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- Scaling
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- Time Series
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- Lag Structure
- Moving Average
- Periodicity
- Serial Correlation
- Spectral Analysis
- Time-Series Cross-Section (TSCS) Models
- Time-Series Data (Analysis/Design)
- Trend Analysis
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