Skip to main content

Currently Skimming:

H USING MOBILITY DATA TO DEVELOP OCCUPATIONAL CLASSIFICATIONS: EXPLORATORY EXERCISES
Pages 411-418

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 411...
... Occupational mobility data can contribute only a little, however, to the definition of occupations in terms of job tasks: for that, occupational analysis or some alternative methodology is needed. The most significant use of job mobility data is to suggest a suitable hierarchical organization of occupations, given a set of occupational definitions.
From page 412...
... Similarly, no data coded into the 12,099 DOT occupational titles are available, nor are any data available that give complete work histories or short-term transfers between jobs.2 More appropriate data are needed for future work in this area. We use the available census data for our exploratory purposes to illustrate how one might proceed in constructing a classification based on naturally occurring patterns of labor mobility.
From page 413...
... It also allows construction of new hierarchies by seeking groups G that make L as large as possible. Conceptually, the procedure is straightforward; computationally, it would be quite a chore to design iterative parameter estimates for a list data structure and to improve the hierarchy by moving jobs between groups.
From page 414...
... . The single linkage technique constructs clusters by linking together jobs for which the transfer rate exceeds some threshold; a cluster is made up of jobs linked together.
From page 415...
... They also show some absurd associations, such as dentist and flight engineer, which are due in part to single linkage chaining together a number of slightly related jobs and in part to the unreliability of transfer rates that (because diagonal terms are removed) may be rather high for jobs with high retention rates, from which people transfer to just a few other jobs.
From page 418...
... In particular, in developing classifications for job-worker matching, it is crucial to pay careful attention to activities before entry and after exit from the work force. In addition, computations should be carried out using list structures; a standard matrix representation is not feasible.


This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More information on Chapter Skim is available.