Linking Digital Archive Files to Create Analytical Files

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By merging and aggregating the four primary files described (manuscript file, author file, review file, and person file) researchers can create a variety of different analytical files at the level of the individual (as author or reviewer), the level of the manuscript (final result or individual versions), or the level of the review.

The DA team has created several analysis files as examples, but researchers may create their own analytical files that are tailored to their particular research agenda.

Example 1

In the first example, we aggregate all versions of manuscripts at the manuscript level to track trajectories of particular types of manuscripts. Information for each manuscript is then added to the record for each author.  Finally author characteristics are added in from the person file.

  1. What type of topics are most likely to be accepted at ASR? Use titles to develop topic codes. How has this changed over time?
  2. What type of authors are most successful?
  3. What does the average submission to final decision process for manuscripts look like?

Example 2

In the second example, we analyze reviewing behavior of individual reviewers by aggregating reviewer file and then adding in reviewer characteristics and author information from sociologist file and aggregated manuscript information.

  1. Do reviewers favor particular types of authors (For example do viewers with certain demographic or institutional characteristics more generous to authors with similar characteristics)?
  2. What types of reviewers are most generous or stingy with acceptances or R&Rs?

Example 3

In the third example, we match data from the person file to the author file, and then aggregate information from the manuscript file to determine the review outcome for each version.

  1. Are the acceptance rates for initial versions of manuscripts different for men and women?
  2. Do acceptance rates vary with the age of the author?