Abstract
We can now begin to focus on the patterns of women’s occupations over time. How do women move between jobs over their lifetimes; if they do? As indicated earlier, most of the existing studies have examined women’s location in the occupational structure through cross-sectional information; that is using data on their current occupations. A cross-sectional picture of an occupational distribution will give an accurate picture of women’s positions if those positions never change. If women’s occupations change over their lifetime, however, the cross-sectional picture will not accurately reflect their lifetime occupational status. The occupational histories of women contained in the Women and Employment Survey (WES) provides the first extensive large scale British data through which to begin to tackle unanswered questions about the nature of women’s careers and occupational changes over their lifetime.1
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Notes and References
The National Training Survey preceded the Women and Employment Survey and contained information on women’s (and men’s) work histories over a ten-year period (see Elias and Main, 1982; Stewart and Greenhalgh, 1982, 1984). There are a number of longitudinal sources of women’s work history data in the USA, e.g. National Longitudinal Surveys (see Dex and Shaw, 1986).
Goldthorpe (1980, p. 140) says ‘It is true that our findings would suggest that certain relatively well-defined types of work life “trajectory” could be specified, but whether it would be possible to assimilate the mobility experience of the population at large to some manageable number of such types is a question which here at least we must leave in doubt’.
The instructions given to the interviewers on the classification of occupations was as follows: You should code the occupations of all women’s jobs recorded during the interview (i.e. Qns. 9(a), 10(a), 76, 108, 113, 147(b) and E on the work history), and the industry of jobs at Qns, 9(b), 10(b) and D on the work history. Do not attempt to code during the interview, but make sure you are familiar with the coding frames so that you collect the appropriate information to code during your checking time. If you are in doubt about how to code DO NOT ENTER A CODE IN THE BOX — leave it blank and make a note of possible code(s) at the side of the box. If an informant does a job which falls into more than one occupation code, code the occupation she spends most time on. Similarly if the organisation she works for falls into more than one industry code, code the main one. If the informant’s own occupation only relates to one industry code give priority to that code. (e.g. Informant works in a filling station which has a shop attached — if her work is mainly selling petrol, code 08 for industry; if she is mainly in the shop, code 05.) Note that anyone who is a trainee is coded to the same occupation as if they had completed the training.
In a few cases in this sample teachers were employed in agricultural and primary industries. The occupational profiles of these women differed from the ones described above for public sector (or professional and scientific industries) teachers. These agriculture teachers did not continue as teachers for very much of their work history, possibly because they were more vulnerable. Nurses were employed in the private sector to a greater extent, especially in their later work profile.
This percentage is based on the experience of older women only, who had completed most of their work histories.
‘Textiles’ here is used to represent the industrial category used in this survey which aggregated textiles, clothing, footwear and leather industries.
The article by Coyle (1982) contains information about the job histories of the women in her sample almost unconsciously; she says, ‘The industry employs a lot of married women but they tend to be women who have worked in the industry for many years’ (p. 17). I take this to mean that they have a semi-skilled factory profile over their working lives.
It is in cases like these where one suspects that the occupational classification may not be adequate to distinguish all types of occupational experience. The experience of clerical work in this profile is vastly different from in the clerical profile and it may be a different type of clerical work, unrecognisable because of the single occupational category. Occasionally, jobs in nursing and skilled work were found amidst jobs in the other categories. These are very infrequent and in the case of nursing it seems likely that these were the more semi-skilled nursing auxiliary jobs.
Coyle (1984, pp. 102–3) for example describes the occupational choices and advice received by two young women: ‘They kept asking you what you’d like to do and they kept saying wouldn’t you like to work in a factory, and I ended up in a factory’; ‘I thought of being a model. I was a beauty queen you see, but my mum wouldn’t let me. I’ll stay in tailoring now, the money’s good.’
McRae (1986) has begun to document the life-style and other characteristics of more extreme cases of women having higher occupations than their husbands, but there is a lot of work needed to be done on the less extreme cases in order to find out whether differences exist between the various categories of households. The ESRC Social and Economic Life Initiative will help to answer these questions.
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© 1987 Shirley Dex
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Dex, S. (1987). Occupational Profiles. In: Women’s Occupational Mobility. Palgrave Macmillan, London. https://doi.org/10.1007/978-1-349-18572-6_3
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DOI: https://doi.org/10.1007/978-1-349-18572-6_3
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