Abstract
Abstract This paper focuses on shifts in perceived job content among two occupational panels (office technology workers and machine operators) during the first year of their professional career. A shortened version of Fine's Functional Job Analysis is used to measure perceived job content, and at each of the two time stages (i.e. stage T1 and stage T2) the data related to the three domains of People, Things, and Data are optimally scaled and then recoded to a categorical indicator of job content complexity. Shifts in perceived job content are studied by application of log-linear analysis to the multidimensional contingency table obtained by the cross-tabulation of the T1 and the T2 data. The results indicate that there is no general progress or decline in job content activities over time, except for the Things domain. The findings also suggest that there is a substantial symmetry between job progression and degression, and that the bulk of content switches is to adjacent levels of complexity.
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