This codebook.txt file was generated on 20210114 by Wanda Marsolek ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset: Data for Taking a diversity, equity, inclusion & accessiblity lens to engineering librairan job postings 2. Author Information Name:Joanna Thielen Institution:University of Michigan Address: Email:jethiele@umich.edu ORCID:0000-0002-2983-5402 Name: Wanda Marsolek Institution: University of Minnesota Address: Email:mars0215@umn.edu ORCID: 0000-0002-1771-3969 3. Date of data collection (single date, range, approximate date) 2018/01-2019/01 -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: CC 4.0 2. Links to publications that cite or use the data: 3. Links to other publicly accessible locations of the data: 4. Links/relationships to ancillary data sets: 5. Was data derived from another source? If yes, list source(s): 6. Recommended citation for the data: --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: Readme Short description: This document B. Filename: Codebook Short description: Includes variables and attributes used to code job postings C. Filename: Codebook_OperationalDefinitions Short description: Inludes variable definitions, when to use, when not to use, and how to use when coding job postings D. Filename: Codebook_VariableAndAttributeSources Short description: Includes sources of variables and attributes used to create Codebook E. Filename: Dataset Short description: Data compiled using variables and attributes from codebooks F. Filename: JobPostings_Metadata Short description: includes job posting metadata for this specific project including University Name, Postion Title, Carnegie Classification and posting date. 2. Relationship between files: Codebook and Codebook_OperationalDefinitions were used to develop the dataset. JobPostings_Metadata and Codebook_VariableAndAttributeSources and JobPostings_Metadata provide source information for Codebook and Dataset -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: We collected engineering librarian job postings that were posted from January 1, 2018 to December 31, 2019 from four sources and analyzed them via deductive thematic analysis. Sources: Association of College and Research Libraries Science & Technology Section Discussion List, Chemical Information Sources Discussion List, American Society for Engineering Education Engineering Libraries Division Discussion List, and Special Library Association Physics-Astronomy-Mathematics Division Discussion List. 2. Methods for processing the data: To determine if a job posting met our inclusion criteria, we first evaluated job postings based on the job titles. Titles that included words such as engineering, science, or STEM were saved for further analysis. We then reviewed each posting to ensure that it met the following three inclusion criteria: 1. Full time, permanent position 2. Located in a United States (US) academic library 3. Responsibilities include providing direct support to the curricular and/or research needs of engineering students, faculty and staff (i.e. an engineering discipline needed to be explicitly mentioned in the job posting). Supervisory or managerial positions were only included if they directly supported these needs. To determine patterns in the salary and qualifications related to education and academic or professional experience for engineering librarian positions, we took a confirmatory approach using deductive thematic analysis. A codebook of variables and attributes for each variable was created prior to analyzing the job positions. Each variable in the codebook was operationally defined in order to avoid ambiguity. Descriptions for when each variable should or should not be used were included. We coded all job postings independently to ensure consistency and reliability. Initially, we coded a small corpus of five job postings. After coding this small corpus, we refined the codebook to define variables more clearly, add additional variables, eliminate unneeded variables, and revise attributes. After these revisions, we coded the entire corpus of 47 job postings. Coding discrepancies were resolved through discussion. Coding reflected a high level of intercoder agreement; percent agreement was 82% ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: Dataset ----------------------------------------- 1. Number of variables: 23 2. Number of cases/rows: 51 3. Variable List A. University Name B. Job Title C. Posting Date (YYYY-MM) D. MLIS degree [Location in Job Posting] E. -- OR -- equivalent degree [Location in Job Posting] F. Equivalent degree level G. Equivalent degree discipline H. Academic library experience I. [Location in Job Posting] J. [Type of experience] K. Additional degree [Location in Job Posting] L. Additional degree level M. Additional degree discipline N. Additional degree [Location in Job Posting] O. Additional degree level P. Additional degree discipline Q. Additional experience [Location in Job Posting] R. Additional experience type S. Carnegie Classification of Institution T. [For doctoral institutions, what intensity level] U. Salary information [Descriptive word] V. Salary range or minimum (N/A for none listed) W. NOTES (optional; free text)