The study that produced this corpus was conducted by a joint Task Force on Career Progression charged by the Association of University Presses and Society for Scholarly Publishing in January 2022, and strengthened by the addition of the Association of Learned Professional and Scholarly Publishers in 2023. The goal of the Career Progression Task Force’s job classification project was to develop a dataset of job descriptions that identify typical skills and responsibilities associated with various roles in publishing, analysing these descriptions to elucidate the skills and qualifications needed for the jobs and career advancement and disseminate the results in a way that is useful to employers and employees alike. The work of the Task Force was made possible by the doctoral internship program at the University of Michigan's Rackham Graduate School, which supported the involvement of Michelle Lam and Lauretta Cheng. The project also involved master’s degree students at George Washington University and the University of Michigan. and In total, the corpus contained 1089 unique job description texts. A wide range/variety of positions (n=666) across functional areas were represented in the corpus. The majority of the texts came from publicly available job postings. This form of text is created to advertise positions and is typically neither as detailed nor as objective as internal position descriptions, which were contributed either individually or as a group from a particular publisher.
Cheng, L., Heaney, K., Lam, M., Lord, J., Warren, J., Watkinson, C. (2024) Supporting Career Progression in Publishing through Systematic Analysis of Job Descriptions: A Cross-Industry Initiative, Learned Publishing
The database was constructed by using the archived monthly newsletters of SPA and SPD. Duplicate job ads (those in both data sets and those posted over multiple months) were eliminated. The comma delimited raw data files of the job postings and the compilation of the numbers by year and job type and provided. A summary of the results is deposited in Deep Blue Documents.
Scan of specimen ummz:mammals:124693 (Aotus azarae) - WholeBody. Reconstructed Dataset includes 1831 TIF images (each 1634 x 1453 x 1 voxel at 0.035184 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:124693 (Aotus azarae) - WholeBody. Raw Dataset includes 1601 TIF images (each 1634 x 1453 x 1 voxel at 0.03518376 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
Scan of specimen ummz:mammals:176889 (Cystophora cristata) - WholeBody. Raw Dataset includes 1601 TIF images (each 1352 x 1999 x 1 voxel at 0.1103929 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:176889 (Cystophora cristata) - WholeBody. Reconstructed Dataset includes 1113 TIF images (each 1352 x 1999 x 1 voxel at 0.110393 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
Scan of specimen ummz:mammals:170489 (Chrysocyon brachyurus) - WholeBody. Reconstructed Dataset includes 1495 TIF images (each 1908 x 1243 x 1 voxel at 0.121618 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:170489 (Chrysocyon brachyurus) - WholeBody. Raw Dataset includes 1601 TIF images (each 1908 x 1243 x 1 voxel at 0.1216177 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
Scan of specimen ummz:mammals:170469 (Addax nasomaculatus) - WholeBody. Raw Dataset includes 1601 TIF images (each 1172 x 980 x 1 voxel at 0.08671137 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:170469 (Addax nasomaculatus) - WholeBody. Reconstructed Dataset includes 1917 TIF images (each 1172 x 980 x 1 voxel at 0.086711 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
Scan of specimen ummz:mammals:163808 (Crocuta crocuta) - WholeBody. Raw Dataset includes 1601 TIF images (each 1931 x 1509 x 1 voxel at 0.1216165 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:163808 (Crocuta crocuta) - WholeBody. Reconstructed Dataset includes 1973 TIF images (each 1931 x 1509 x 1 voxel at 0.121617 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
Scan of specimen ummz:mammals:157158 (Conepatus humboldtii) - WholeBody. Reconstructed Dataset includes 1979 TIF images (each 984 x 1237 x 1 voxel at 0.037468 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:157158 (Conepatus humboldtii) - WholeBody. Raw Dataset includes 1601 TIF images (each 984 x 1237 x 1 voxel at 0.03746828 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
Scan of specimen ummz:mammals:114800 (Acinonyx jubatus) - WholeBody. Raw Dataset includes 1601 TIF images (each 1978 x 1688 x 1 voxel at 0.09413704 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:114800 (Acinonyx jubatus) - WholeBody. Reconstructed Dataset includes 1671 TIF images (each 1978 x 1688 x 1 voxel at 0.094137 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
Scan of specimen ummz:mammals:103553 (Cynictis penicillata) - WholeBody. Raw Dataset includes 1601 TIF images (each 1048 x 1049 x 1 voxel at 0.03995863 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:103553 (Cynictis penicillata) - WholeBody. Reconstructed Dataset includes 1946 TIF images (each 1048 x 1049 x 1 voxel at 0.039959 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.