ࡱ> # $                   ! " o X %` #bjbj kG̟̟(z/Adddt4$"\===h$>$H?&~7cleg(hhhpt|$v0111001Ib$dh9gTbvo|pvvbVVhhbpypypyvVhh0d.pyv0pypyGs:zhe pQ*=x:Lc07c҇gy:g0gvvpyvvvvvbbTyvvv7cvvvv~~~=~~~=RF  "xRVVV  Is VET vocational? The relevance of training to the occupations of vocational education and training graduates Tom Karmel Peter Mlotkowski Tomi Awodeyi ϲʿ¼ Please note: The graphs in this document have been produced in colour. For clarity, please print in colour. The views and opinions expressed in this document are those of ϲʿ¼ and do not necessarily reflect the views of the Australian Government or state and territory governments. Publishers note To find other material of interest, search VOCED (the UNESCO/ϲʿ¼ international database < HYPERLINK "http://www.voced.edu.au/" http://www.voced.edu.au>) using the following keywords: generic skill; graduate; industry; labour market; occupational qualification; outcome of education; relevance of education; skill; training package; training system Australian Government, 2008 This work has been produced by the ϲʿ¼ (ϲʿ¼) as a joint initiative of the Australian Government and state and territory governments, with funding provided through the Australian Department of Education, Employment and Workplace Relations. Apart from any use permitted under the Copyright Act 1968, no part of this publication may be reproduced by any process without written permission. Requests should be made to ϲʿ¼. The views and opinions expressed in this document are those of ϲʿ¼ and do not necessarily reflect the views of the Australian Government or state and territory governments. ISBN 978 1 921412 46 2 web edition TD/TNC 92.45 Published by ϲʿ¼ ABN 87 007 967 311 Level 11, 33 King William Street, Adelaide, SA 5000 PO Box 8288 Station Arcade, Adelaide SA 5000, Australia ph +61 8 8230 8400 fax +61 8 8212 3436 email ncver@ncver.edu.au About the research Is VET vocational? The relevance of training to the occupations of vocational education and training graduates by Tom Karmel, PeterMlotkowski and Tomi Awodeyi, ϲʿ¼ Australias vocational education and training (VET) system is characterised as being industry-led, with the content of courses based on the skills and competences specified by industry. VET courses have been packaged up into industry training packages developed by industry, with the aim of meeting the needs of an industry or a group of industries. This approach sits well with a view of VET as being about acquiring specific skills to be used in work. By contrast, we think of school and university education as having broader purposes, and often being ends in their own right. While university graduates tend to do well in the labour market, many have degrees which are generic in nature. Is vocational education and training as narrowly vocational as the standard description seems to imply? Is VET vocational? The relevance of training to the occupations of vocational education and training graduates aims to throw some light on this question through a comparison of what VET graduates study and the jobs they get. To do this it uses data from the Student Outcomes Survey. For those graduates whose destination occupation differs from the intended occupation (obtained by assigning an occupation to each course), the study investigates the skill level of the destination occupation and the extent to which the graduates view their training as being relevant. The idea is to distinguish between training that is generic (in the sense of being relevant to a wide range of destination occupations) and training that is wasted. (Physicists driving taxis is the popular example.) Key messages The match between what people study and the jobs they get is high for the technicians and trades group of occupations, but relatively low for most other courses. Most of the mismatch between intended and destination occupations reflects the generic aspect of vocational education and training. Graduates mostly report their training as relevant to their job, despite not ending up in the matched occupation. There is some skills wastage, however, with graduates reporting that their training is not relevantto the occupation in which they find themselves. The two courses with the highest skills wastage are those for arts and media professionals and sports and personal service workers. The study has three main implications. First, in thinking about the role of the VET system in addressing the needs of the labour market, it needs to be kept in mind that, with the exception of the trades, there is no neat match between courses and the occupations in which most people end up working. Second, those developing training packages need to be aware that many graduates will not work in their intended occupation. Finally, potential students need to be realistic about the likely occupation that a particular course will lead to. Tom Karmel Managing Director, ϲʿ¼ Contents TOC \o "1-2"  Tables and figures  PAGEREF _Toc74389441 \h 6 Introduction  PAGEREF _Toc74389442 \h 7 Occupational alignment between training and employment  PAGEREF _Toc74389443 \h 9 Skill levels  PAGEREF _Toc74389444 \h 14 Mismatch or generic training?  PAGEREF _Toc74389445 \h 16 Conclusion  PAGEREF _Toc74389446 \h 23 References  PAGEREF _Toc74389447 \h 24 Appendix  PAGEREF _Toc74389448 \h 25  Tables and figures  TOC \f F \t "tabletitle" \c Tables 1 Matches between intended and destination occupations for graduates who are employed, by selected ANZSCO, 2007  PAGEREF _Toc74389788 \h 10 2 Matches between intended and destination occupations for graduates who are employed and who undertook their training for employment-related reasons, by selected ANZSCO, 2007  PAGEREF _Toc74389789 \h 12 3 Matches between intended and destination occupations for apprentices and trainees who have completed their training and are employed, by selected ANZSCO, 2007  PAGEREF _Toc74389790 \h 13 4 Employment status, skill level and occupational match by intended occupation, 2007  PAGEREF _Toc74389791 \h 14 5 Employment status, skill level and occupational match, by intended occupation for young people, 2004  PAGEREF _Toc74389792 \h 15 6 Graduates reporting that their training was highly or somewhat relevant: graduates for whom intended and destination occupations match at the sub-major group level, by selected ANZSCO, 2007  PAGEREF _Toc74389793 \h 17 7 Top 10 destination occupations and percentage reporting training relevant: arts and media professionals  PAGEREF _Toc74389794 \h 18 8 Top 10 destination occupations and percentage reporting training relevant: educationprofessionals  PAGEREF _Toc74389795 \h 19 9 Training relevance by intended occupation: graduates for whom intended and destination occupations do not match at the sub-major group level, 2007  PAGEREF _Toc74389796 \h 19 10 Courses sorted by the proportion of graduates reporting that the training is of little or no relevance to their destination occupation: graduates for whom intended and destination occupations do not match at the sub-major group level, by selected ANZSCO, 2007  PAGEREF _Toc74389797 \h 21 A1 Skill level by ANZSCO  PAGEREF _Toc74389798 \h 25 A2 Top 10 destination occupations and percentage reporting training highly or somewhat relevant for intended occupations at the sub-major group level, by selected ANZSCO, 2007  PAGEREF _Toc74389799 \h 32 A3 Training relevance by intended occupation: graduates for whom intended and destination occupations do not match at the sub-major group level, by selected ANZSCO, 2007  PAGEREF _Toc74389800 \h 45 A4 Estimated populations of graduates by intended occupation, by selected ANZSCO, 2007  PAGEREF _Toc74389801 \h 47 TOC \t "Figuretitle,1" \c "Figure"  Figures 1 Courses ranked from most specific to most generic, by selected ANZSCO, 2007  PAGEREF _Toc74389829 \h 22  Introduction Vocational education and training (VET) is, by definition, vocational in intent. Its purpose is unashamedly instrumental; it is about acquiring skills to be used at work. This contrasts with the broader purposes of school education and university education, where education is often seen as an end in its own right. Of course, it would be quite wrong to characterise school education and university education as non-instrumental. The dominant paradigm guiding public policy for many years has been human capital theory, in which individuals acquire skillshuman capitaland then obtain a return on that investment through higher employment rates and higher-paying jobs. This model underpins the Higher Education Contribution Scheme (HECS), by which university students pay substantial tuition fees on a deferred, income-contingent basis. The idea is that students contribute to the cost of acquiring human capital and then repay the debt when their subsequent income reaches a threshold. However, the instrumental nature of university education is not as clear cut as in VET. Certainly, the professional fields of medicine, law, accounting, teacher education, nursing, and engineering are largely vocational in nature and there is an expectation that a high proportion of their students will become doctors, lawyers, accountants, nurses, teachers and engineers. Other fields by contrast are far less vocational in nature and provide a much more generic training, the most obvious examples being the humanities and pure sciences. The social sciences and the applied sciences fall somewhere in between. This is not to say that the non-vocational fields are not valuable preparation for work. For many years, an economics degree was the favoured background for Australian public servants engaged in policy work because it provided a certain way of analysing the world. Similarly, the British civil service was reputed to have favoured Oxbridge graduates with classics degrees. Perhaps VET should be seen in the same way, as providing not only specific vocational skills but also generic employment skills. Certainly, in recent years there has been increasing attention paid to employability skills: skills such as problem-solving, the ability to work in a team, communication skills and so on. However, the official rhetoric has been unambiguous in describing VET in terms of the skills and competences specified by industry. VET courses have been packaged up into industry training packages developed by the various industry skills councils and their antecedents. These industry packages outline a set of nationally endorsed standards, guidelines and qualifications for training, recognising and assessing peoples skills. They are developed by industry with the aim of meeting the needs of an industry or group of industries. The issue that this report explores is how VET is actually used in the labour market. In particular, we look at the match between what people study and the jobs they get. If the match is very good, then we would conclude that the VET system is performing its role in providing individuals with vocational skills. If the match is poor, then we need to think about whether the VET system is not as effective as it should be, or whether we should rethink the nature of vocational education. The classic example of a mismatch would be a physicist or electrician driving a taxi. In such cases, from the point of view of training for a skilled workforce, the education is totally wasted. Where the nature of matching is more problematic is a tradesman, for example, becoming a manager. Here it would not be reasonable to say that the vocational education is a waste, but it may suggest that trades education needs to be considered more broadly, rather than merely being the acquisition of trade skills for a particular occupation. The Student Outcomes Survey provides a mapping between the intended occupation of training activity and the occupation after training. Each qualification and module is coded to an occupation and it is a simple matter to match the intended occupation (based on the occupation code of the qualification) and the occupation after training. We can then look, by qualification, at how well the intended and destination occupations match. Preliminary research by Cully, Nguyen and John (2004) suggests that, with the exception of trade qualifications, the match between intended and destination occupations is poor, with matches in managerial and professional occupations being the lowest. As with any empirical work there are a range of issues that need to be taken into account. First, the gap between the end of training and the survey is about six months and so the matching process has only had a limited period of time to be effective. For a subset of the data (persons under the age of 25 years) we have follow-up data two years later. The level of classification also plays a part; by definition, the level of matching will be lower if a finer classification is used. Our analysis is based on the sub-major group level of the Australian and New Zealand Standard Classification of Occupations (ANZSCO). This provides 43 distinct occupations, including seven technician and trade occupations. The next section presents the results of the matching. We find that the level of matching is quite low at the sub-major occupation group level (36.6% for graduates). However, the rate of matching increases significantly if we restrict ourselves to graduates who undertook training for job-related reasons or graduates who had undertaken an apprenticeship or traineeship. Indeed, the overall match for the latter group is 60.7%, and four out of the seven technician and trade occupations have matches over 85%. There is considerable variability across occupations. The best matches are in the trades and the worst in managerial occupations. In addition to the extent of matching, our interest lies in the skill levels of the destination occupations, and this is the subject of the third section of the report. The main issue is the extent to which destination occupations are at a level commensurate with intended occupations. This analysis is built on the five levels of skill assigned to each four-digit occupation by the Australian Bureau of Statistics (ABS). Our results are largely positive, with around three-quarters of graduates working at a skill level equal or higher than that of the intended occupation. The following section takes a different angle by looking at qualitative data from the Student Outcomes Survey. Respondents are asked questions about the relevance of their training and whether the student achieved their main reason for studying. These answers can be classified by whether the intended and destination occupations match. If we find that qualifications are seen to be highly relevant when there is a match but not so relevant when there is no match, then we would conclude that the mismatching is an issue and that the training has largely been wasted. On the other hand, if the qualifications are seen to be relevant even when there is no match, then we would conclude that the qualifications are useful but are more generic in nature, in the sense that people working in a range of occupations have found the training relevant. One of the features of this section is the level of detail. For each intended occupation we have listed the important destination occupations and the level of the relevance of the training. Our main findings are: that wastage is an issue in relatively few courses (but is a real issue for courses with intended occupations of arts and media professionals, and sports and personal workers); and that VET as generic training (that is, relevant to a range of occupations) is the rule rather than the exception. In fact VET is highly specific only for some of the trades, carers and aides, and cleaners and laundry workers. We end with some conclusions. Occupational alignment between training and employment The intended occupation is derived from the Australian and New Zealand Standard Classification of Occupations (ANZSCO) assigned to training package qualifications. The destination occupation is the ANZSCO occupation corresponding to a students employment after training. A match at major group refers to equivalent codes when intended and destination occupations are compared at the single-digit occupational level, while a match at sub-major group refers to equivalent codes when those occupations are compared at the two-digit level. It is the latter that we primarily use. We restrict our sample to graduates; that is, those people who have completed a qualification. This is because we are less interested in the match for those who do not complete a full qualification. It would be unreasonable to conclude that the VET system is not providing relevant skills if the individual has not completed the full qualification. Some modules may equip an individual for a particular occupation, but the complete qualification could be expected to provide a better foundation. Table 1 provides the results of the initial tabulation. The table has two columns: match at major group and match at sub-major group. The two columns are best explained through a couple of examples. Take technicians and trades workers. The match at the major group is 66.7%, meaning that 66.7% of people with trades qualifications ended up in a trades occupation. The match at the sub-major group level is 60.6%, meaning that 60.6% of technicians and trades workers ended up in their intended occupation at the sub-major group level. For individual trades there are again two levels of matching. For example, 72.3% of graduates with an automotive and engineering qualification ended up in an automotive and engineering occupation (that is, matched at the sub-major group), but 80.7% ended up in a trades occupation (that is, matched at the major group). So 8.4% of these graduates ended up in a trades occupation, but not automotive and engineering. Table 1 Matches between intended and destination occupations for graduates who are employed, by selected ANZSCO, 2007 Intended occupation of training activityMatch at majorgroupMatch at sub-major group%%1 Managers 18.814.112 Farmers and farm managers 36.733.413 Specialist managers 14.68.314 Hospitality, retail and service managers 12.610.52 Professionals 35.421.521 Arts and media professionals 22.27.5* 22 Business, human resource and marketing professionals 16.915.023 Design, engineering, science and transport professionals 21.016.924 Education professionals 56.131.026 ICT professionals 28.016.1* 27 Legal, social and welfare professionals 29.928.23 Technicians and trades workers 66.760.631 Engineering, ICT and science technicians 29.920.632 Automotive and engineering trades workers 80.772.333 Construction trades workers 86.181.134 Electrotechnology and telecommunications trades workers 92.185.735 Food trades workers 77.876.436 Skilled animal and horticultural workers 46.643.639 Other technicians and trades workers 54.649.04 Community and personal service workers 53.343.841 Health and welfare support workers 61.333.042 Carers and aides 77.470.943 Hospitality workers 34.829.144 Protective service workers 41.334.945 Sports and personal service workers 35.026.45 Clerical and administrative workers 50.323.051 Office managers and program administrators 41.610.653 General clerical workers 50.921.154 Inquiry clerks and receptionists 54.041.355 Numerical clerks 64.942.159 Other clerical and administrative workers 41.818.76 Sales workers 51.645.261 Sales representatives and agents 49.640.162 Sales assistants and salespersons 52.046.17 Machinery operators and drivers 39.526.671 Machine and stationary plant operators 38.322.272 Mobile plant operators 32.122.173 Road and rail drivers 41.132.374 Storepersons 40.523.78 Labourers 33.625.581 Cleaners and laundry workers 88.884.882 Construction and mining labourers 24.018.383 Factory process workers43.331.984 Farm, forestry and garden workers36.426.385 Food preparation assistants23.113.789 Other labourers13.18.2Total47.836.6Notes: Base is all graduates, irrespective of reason for study, who were employed as at May 2007, excluding those from theadult and community education (ACE) sector and unknown intended ANZSCO. Some sub-major group level occupations are not presented due too few numbers in sample cells. * Relative standard error greater than 25%; estimate should be used with caution. Source: ϲʿ¼ Student Outcomes Survey, 2007. The table shows a high degree of variability. The match at the sub-major group level is 36.6%, with individual matches varying between 7.5% for arts and media professionals, to 85.7% for the electrotechnology and telecommunications trades. If the matching criterion is broadened to the major group level, then the matches rise to 22.2% for arts and media professionals and to 92.1% for the electrotechnology and telecommunications trades. Which level is more appropriate is a matter of judgement, but we concentrate on the sub-major group levelit seems to supply a reasonable level of differentiation. The matches are highest for the trades group. However, within this group the level of matching ismuch lower for engineering and science technicians, and skilled animal and horticultural workers. In relation to the other groups, matching is particularly poor for managers, labourers andprofessionals. Before exploring the nature of the so-defined mismatches, we note that the VET student population is very diverse, ranging from school leavers and new entrants, to people retraining or wishing to advance their careers. Background and motivation are likely to affect the level of matching. For example, if an individual is undertaking a course for personal development reasons, then there would be no reason to expect an occupational match. To throw some light on this we provide two additional tabulations. The first of these (table 2) restricts the sample to those who have indicated that their main reason for study is employment-related (77.7% of graduates in 2007) (ϲʿ¼ 2007). The second (table 3) restricts the sample to those who had undertaken an apprenticeship or traineeship (25.4% of graduates in 2007) (ϲʿ¼ 2007). The level of matching increases somewhat when the reason for study is employment-related and quite substantially for those who had undertaken an apprenticeship or traineeship. For those undertaking an apprenticeship or traineeship, the level of matching is particularly high for technician and trade occupations, with an overall match at the sub-major group level of 84.6%, and four out of the seven trade occupations had matches in excess of 85%. However, the level of matching is quite low outside the technicians and trades workers category. The only non-trades sub-major group occupations with matches over 70% are carers and aides (81.5%) and road and rail drivers (78.6%). Table 2 Matches between intended and destination occupations for graduates who are employed and who undertook their training for employment-related reasons, by selected ANZSCO, 2007 Intended occupation of training activityMatch at major groupMatch at sub-major group%%1 Managers 19.515.312 Farmers and farm managers 39.037.113 Specialist managers 15.08.914 Hospitality, retail and service managers 11.510.32 Professionals 39.023.821 Arts and media professionals 20.75.6* 22 Business, human resource and marketing professionals 20.618.323 Design, engineering, science and transport professionals 21.718.124 Education professionals 57.231.226 ICT professionals 30.615.4* 27 Legal, social and welfare professionals 29.527.43 Technicians and trades workers 70.464.331 Engineering, ICT and science technicians 32.523.732 Automotive and engineering trades workers 83.574.833 Construction trades workers 86.380.934 Electrotechnology and telecommunications trades workers 92.285.835 Food trades workers 80.179.136 Skilled animal and horticultural workers 49.246.639 Other technicians and trades workers 60.254.64 Community and personal service workers 56.746.941 Health and welfare support workers 63.434.642 Carers and aides 79.573.243 Hospitality workers 36.930.744 Protective service workers 40.534.545 Sports and personal service workers 41.332.55 Clerical and administrative workers 54.826.151 Office managers and program administrators 41.211.453 General clerical workers 58.325.054 Inquiry clerks and receptionists 60.345.955 Numerical clerks 65.442.859 Other clerical and administrative workers 44.921.46 Sales workers 52.746.6 61 Sales representatives and agents 51.143.062 Sales assistants and salespersons 53.047.37 Machinery operators and drivers 42.929.0 71 Machine and stationary plant operators 38.422.272 Mobile plant operators 30.119.573 Road and rail drivers 53.242.774 Storepersons 38.722.38 Labourers 35.027.0 81 Cleaners and laundry workers 88.884.782 Construction and mining labourers 26.420.783 Factory process workers44.433.384 Farm, forestry and garden workers39.828.885 Food preparation assistants25.615.489 Other labourers12.98.6Total51.139.7Notes: Base is all graduates who indicated employment-related reasons for undertaking training and who were employed asat May 2007, excluding those from the ACE sector and unknown intended ANZSCO. Some sub-major group level occupations are not presented due too few numbers in sample cells. * Relative standard error greater than 25%; estimate should be used with caution. Source: ϲʿ¼ Student Outcomes Survey, 2007. Table 3 Matches between intended and destination occupations for apprentices and trainees who have completed their training and are employed, by selected ANZSCO, 2007 Intended occupation of training activityMatch at majorgroupMatch at sub-major group%%1 Managers 11.711.712 Farmers and farm managers 14.5* 14.5* 13 Specialist managers 8.8* 8.8* 2 Professionals 22.6* 21.9* 3 Technicians and trades workers 88.684.6 31 Engineering, ICT and science technicians 58.348.632 Automotive and engineering trades workers 92.187.033 Construction trades workers 90.187.734 Electrotechnology and telecommunications trades workers 94.789.535 Food trades workers 92.791.236 Skilled animal and horticultural workers 63.461.639 Other technicians and trades workers 86.682.14 Community and personal service workers 69.362.0 41 Health and welfare support workers 66.128.4* 42 Carers and aides 86.981.543 Hospitality workers 46.541.344 Protective service workers 73.868.245 Sports and personal service workers 39.735.05 Clerical and administrative workers 68.132.1 51 Office managers and program administrators 50.710.5* 53 General clerical workers 71.231.454 Inquiry clerks and receptionists 62.247.355 Numerical clerks 82.653.159 Other clerical and administrative workers 55.127.66 Sales workers 53.449.0 61 Sales representatives and agents 76.268.162 Sales assistants and salespersons 51.947.77 Machinery operators and drivers 57.647.0 71 Machine and stationary plant operators 49.633.472 Mobile plant operators 34.124.6* 73 Road and rail drivers 81.178.674 Storepersons 51.238.78 Labourers 48.239.3 81 Cleaners and laundry workers 83.278.682 Construction and mining labourers 19.2* 10.1* 83 Factory process workers58.048.584 Farm, forestry and garden workers53.740.485 Food preparation assistants42.6* 21.3* 89 Other labourers16.011.2Total70.860.7Notes: Base is all apprentice and trainee graduates who were employed as at May 2007, excluding those from the ACE sector and unknown intended ANZSCO. Some sub-major group level occupations are not presented due too few numbers in sample cells. * Relative standard error greater than 25%; estimate should be used with caution. Source: ϲʿ¼ Student Outcomes Survey, 2007. Skill levels We have established that the matching is pretty good in the trades but much poorer elsewhere. We now attempt to unpick the mismatch to find out whether it is more about the generic nature of qualifications or more that individuals cannot get a job commensurate with their qualifications. We provide an overall picture by distinguishing between occupations at a higher skill level and occupations at a lower skill level. Under the ANZSCO classification, skill levels are assigned to occupations at the four-digit level, from 1 (the highest) to 5 (the lowest). That is, not all managers are assigned the highest skill level, just as not all labourers have the lowest skill level (see appendix table A1). According to the Australian Bureau of Statistics, occupations at skill level 1 have a level of skill commensurate with a bachelor degree or higher qualification. Occupations at skill level 2 have a level of skill commensurate with an associate degree, advanced diploma or diploma. Occupations at the lowest skill level (skill level 5) have a level of skill commensurate with certificate 1 or compulsory secondary education (ABS 2005). Table 4 summarises changes in skill levels when graduates are not employed in the intended occupation of training. Table 4 Employment status, skill level and occupational match by intended occupation, 2007 Intended occupation of training activityNot employed in intended occupationEmployed in intended occupationEmployed at same or higher skill level(a)Employed at lower skill level(a)Employed at unknown skill level(a), (b)Occupation after training unknown%%%%%Managers 18.85.328.646.40.8Professionals 35.46.756.70.01.2*Technicians and trades workers 66.710.817.24.40.9Community and personal service workers 53.316.18.920.71.0Clerical and administrative workers 50.328.018.62.20.9Sales workers 51.643.64.40.00.3*Machinery operators and drivers 39.541.416.32.10.7Labourers 33.663.60.6* 0.41.9Total47.825.516.09.71.0Note: Base is all graduates, irrespective of reason for study, who were employed as at May 2007, excluding those from theACE sector and unknown intended ANZSCO. (a) Calculated at 4-digit ANZSCO level by comparing skill level of intended occupation and skill level of occupation after training. (b) The 'unknown' skill levels occur when occupations are coded to the 2-digit level, to which skill levels are not assigned. * Relative standard error greater than 25%; estimate should be used with caution. Source: ϲʿ¼ Student Outcomes Survey, 2007. The occupation group that does worst in this exercise is professionals. In this group a majority of VET graduates (56.7%) ends up in a job at a lower skill level, and the percentage employed in the intended occupation of their training is relatively low (35.4%). Technicians and trades workers are most likely to be employed in the intended occupation of their training, although 17.2% also end up in a job at a lower skill level. Sales workers do particularly well in this exercise, with 95.2% of graduates from this group either employed in their intended occupation or employed in a job at the same or higher skill level. As noted earlier, the Student Outcomes Survey occurs around six months after the completion of training. For young people (1524 years), we have data from the Down the Track survey, a further 24 months later. However, we must use the Australian Standard Classification of Occupations (ASCO) here rather than ANZSCO because the latter was only introduced after the Down the Track survey. This should not matter because our interest is in the relationship between the matches at six months and the matches at 30 months, rather than the level of matching itself. Table 5 indicates that, at the aggregate level, the matching rate actually declines over the period (43.1% to 40.5%), but the proportion moving into higher skill level occupations increases a little. By occupation the picture varies, with the matching increasing for managers and administrators (very modestly), professionals and associate professionals (appreciably), and intermediate production and transport workers (dramatically). Matching declines for the other occupational groups, suggesting attrition in these occupations. Thus the matching process takes some time for the higher skilled occupations. (The intermediate production and transport workers occupation group appears to be an anomaly.) Table 5 Employment status, skill level and occupational match, by intended occupation for young people, 2004 Intended occupation of training activityShort termMedium termEmployed in intended occupationEmployed at lower skill levelEmployed in intended occupationEmployed at lower skill level%%%%Managers and administrators6.284.57.470.9Professionals17.578.320.476.0Associate professionals19.564.323.754.4Tradespersons and related workers78.911.569.222.1Advanced clerical and service workers8.276.95.379.0Intermediate clerical, sales and service workers42.939.439.826.2Intermediate production and transport workers4.956.445.74.2Elementary clerical, sales and service workers34.10.031.90.0Labourers and related workers25.10.014.40.0Total43.139.740.536.4Notes: Base is all graduates, irrespective of reason for study, who were either employed as at May 2002 (short term) or as at September 2004 (medium term), excluding those with unknown intended occupations. Source: ϲʿ¼ Down the Track Survey, 2004. Mismatch or generic training? We have been tussling with the two competing explanations of the low level of matching in the majority of the occupations (trades being the obvious exception). Does it indicate that the training has been wasted or does it indicate that the qualifications are generic in nature with applicability to awide range of occupations? The Student Outcomes Survey has a question relating to the relevance to the current job of skills acquired in training. We tabulate the answer to this question in appendix table A2, showing the percentage who report their training as being highly or somewhat relevant forthe destination occupations of each intended occupation. We also list, in descending order, the percentage of graduates who end up in each destination occupation. The purpose of this table is to provide readers with a reference to data at a detailed level, in contrast to the largely general picture provided by earlier tables. What we are hoping to understand is the extent to which a mismatch indicates a waste of training (as measured by a low percentage of graduates in a destination occupation reporting the training as being relevant), or generic preparation (as measured by a high percentage reporting the training as being relevant, although they do not end up in the intended occupation). Before we move on to this issue of relevance among the mismatches, we first make sure that the matches report their training as relevantit would be rather worrying if this were not the case. Overall, 93.4% of those whose destination occupation is the same as their intended occupation report their training as being highly or somewhat relevant (table 6). At the sub-major group level, all occupations report relevance levels of over 80%, with the exception of hospitality, retail and service managers (78.4%) and arts and media professionals (69.9%). Table 6 Graduates reporting that their training was highly or somewhat relevant: graduates for whom intended and destination occupations match at the sub-major group level, by selected ANZSCO, 2007 Intended occupation of training activity%1 Managers92.012 Farmers and farm managers 94.613 Specialist managers 94.514 Hospitality, retail and service managers 78.42 Professionals 90.521 Arts and media professionals 69.922 Business, human resource and marketing professionals 97.023 Design, engineering, science and transport professionals 85.224 Education professionals 89.526 ICT professionals 100.027 Legal, social and welfare professionals 100.03 Technicians and trades workers 96.531 Engineering, ICT and science technicians 93.132 Automotive and engineering trades workers 97.633 Construction trades workers 95.734 Electrotechnology and telecommunications trades workers 95.235 Food trades workers 97.236 Skilled animal and horticultural workers 96.139 Other technicians and trades workers 97.54 Community and personal service workers 95.141 Health and welfare support workers 94.142 Carers and aides 97.343 Hospitality workers 91.444 Protective service workers 92.845 Sports and personal service workers 92.95 Clerical and administrative workers 90.451 Office managers and program administrators 95.253 General clerical workers 90.354 Inquiry clerks and receptionists 88.355 Numerical clerks 89.159 Other clerical and administrative workers 93.76 Sales workers88.261 Sales representatives and agents 96.962 Sales assistants and salespersons 86.87 Machinery operators and drivers 89.371 Machine and stationary plant operators 91.472 Mobile plant operators 84.873 Road and rail drivers 86.374 Storepersons 95.88 Labourers88.881 Cleaners and laundry workers 90.182 Construction and mining labourers 96.483 Factory process workers88.284 Farm, forestry and garden workers89.185 Food preparation assistants88.689 Other labourers83.1Total93.4Notes: Base is all graduates, irrespective of reason for study, who were employed as at May 2007, excluding those from theACE sector and unknown intended ANZSCO. Some sub-major group level occupations are not presented due too few numbers in sample cells. Source: ϲʿ¼ Student Outcomes Survey, 2007. We now get back to the main business of this section. We select two sub-major groups to illustrate the detailed data in table A2: arts and media professional (table 7), and education professionals (table 8). Table 7 Top 10 destination occupations and percentage reporting training relevant: arts and media professionals Destination occupation%Cumulative %% reporting training was highly or somewhat relevant62 Sales assistants and salespersons 21.218.021 Arts and media professionals 7.528.769.943 Hospitality workers 7.135.85.224 Education professionals 7.042.895.589 Other labourers 5.448.2n/a39 Other technicians and trades workers 4.452.658.763 Sales support workers 4.256.826.442 Carers and aides 3.760.527.313 Specialist managers 3.263.732.622 Business, human resource and marketing professionals 3.066.730.5Note: Total number of respondents: 224. Source: Table A2. The match with destination occupations is very poor for the graduates of courses with the intended occupation of arts and media professionals: only 7.5% of graduates end up in the intended occupation, while 21.2% end up as sales assistants and salespersons. Of the latter group, only 18.0% report the training as being highly or somewhat relevant. Here there is no doubt that the training is a waste. However, 7.0% of arts and media professionals also end up as education professionals, and 95.5% of this group report the training as being relevant. So for those arts and media professionals who end up as salespersons the training is a waste, and for those who end up as education professionals the training offers a generic preparation. The latter suggests that course designers need to be aware that education occupations are likely to be prized occupations for their graduates. We contrast this occupation with one where the match between intended and destination occupation is low, but training relevance is high in the non-matched destination occupations. The intended occupation of education professionals (table 8) is one such example. While the match here is only 31.0%, those graduates ending up in other occupations report high levels of training relevance. Thus courses for education professionals are largely generic in nature, in the sense that there are large numbers of graduates who do work as educational professionals but still judge the training as relevant to their work. Table 8 Top 10 destination occupations and percentage reporting training relevant: educationprofessionals Destination occupation%Cumulative %% reporting training was highly or somewhat relevant24 Education professionals 31.089.522 Business, human resource and marketing professionals 15.946.996.525 Health professionals 5.352.289.513 Specialist managers 5.257.489.051 Office managers and program administrators 4.862.294.231 Engineering, ICT and science technicians 3.065.286.041 Health and welfare support workers 3.068.281.144 Protective service workers 2.871.084.153 General clerical workers 2.773.771.071 Machine and stationary plant operators 2.676.395.0Note: Total number of respondents: 1072. Source: Table A2. Readers interested in the relevance of individual destination occupations for each intended occupation are referred to table A2 in the appendix. To get an overall perspective we consider graduates classified by their intended occupation. For the graduates who are not employed in their intended occupation, we show the percentage who report the training as being highly or somewhat relevant, and the percentage who report the training as having very little or no relevance. Table 9 present the results of this exercise summarised at the major group level (noting that the arithmetic is at the sub-major group level). Table 9 Training relevance by intended occupation: graduates for whom intended and destination occupations do not match at the sub-major group level, 2007 Not employed in intended occupationIntended occupation (2-digit ANZSCO within these major groups)Employed in intended occupationTraining is highly or somewhat relevantTraining has very little or no relevanceTraining relevance unknownOccupation after training unknown%%%%%Managers14.165.919.10.1* 0.8Professionals 21.552.624.40.3** 1.2*Technicians and trades workers 60.624.214.20.1* 0.9Community and personal service workers 43.829.425.60.2* 1.0Clerical and administrative workers 23.053.722.30.1* 0.9Sales workers45.237.317.10.1** 0.3*Machinery operators and drivers 26.647.724.70.2* 0.7Labourers25.549.922.50.3* 1.9Total36.641.221.10.21.0Notes: Base is all graduates, irrespective of reason for study, who were employed as at May 2007, excluding those from theACE sector and unknown intended ANZSCO; matching between intended and destination occupation occurs at the sub-major group level. * Relative standard error greater than 25%; estimate should be used with caution. ** Fewer than 5 respondents in cell. Source: Table A3. The columns to focus on are the first three (numeric) columns. The sum of the first two reflects the usefulness of the course, and the third reflects the wastage. According to this way of looking at the data, overall, 21.1% of graduates had completed courses that were wasted. The lowest wastage rate is among technicians and trades workers, at 14.2%. The courses with the highest wastage rates are those for community and personal service workers (25.6%), machinery operators and drivers (24.7%), and professionals (24.4%). While these wastage rates are not excessive, a number of sub-major group courses have much higher rates. Table A3 replicates table 9 at the sub-major group level, and we extract the third numeric column from this table to further pursue the wastage issue. Table 10 sorts the courses on the basis of the number of graduates not employed in the intended occupation and reporting that they found the training to be of little or no relevance to their destination occupation. From this table, we conclude that wastage is a real issue for courses designed for arts and media professionals and sports and personal service workers. It is also an issue, but to a lesser extent, for a number of other courses. For all of these courses, students should be made aware of the limited available job opportunities, and policy-makers need to be concerned about the apparent level of over-provision. While the number of graduates in these courses is modest, it is also not insignificant: 3240 arts and media professionals and 15 360 sports and personal service workers, out of an estimated number of graduates of just under 400 000 in 2007. We now move from the issue of wastage to the balance between specific and generic training. To obtain an overall view of this issue we categorise courses on a specific to generic scale. We look at the number of graduates in the intended occupation compared with a related occupation (by which we mean a job where the training is highly or somewhat relevant, although not in the intended occupation). Courses classified by the intended occupation are listed, from those which are highly specific (a very high level of matching between the intended and destination occupations), to those which are highly generic (a high number of graduates reporting training relevance in other destination occupations) (figure 1). We can see that the highly specific courses are dominated by some (but not all) of the trades. Courses for carers and aides are also highly specific. Other occupational areas tend to be much more generic in nature, and course designers need to be aware of the wide range of contexts which make use of thetraining. Table 10 Courses sorted by the proportion of graduates reporting that the training is of little or no relevance to their destination occupation: graduates for whom intended and destination occupations do not match at the sub-major group level, by selected ANZSCO, 2007 Intended occupation of training activity%21 Arts and media professionals63.645 Sports and personal service workers45.026 ICT professionals36.773 Road and rail drivers35.343 Hospitality workers34.031 Engineering, ICT and science technicians31.285 Food preparation assistants29.759 Other clerical and administrative workers28.684 Farm, forestry and garden workers27.222 Business, human resource and marketing professionals27.161 Sales representatives and agents26.014 Hospitality, retail and service managers25.953 General clerical workers25.939 Other technicians and trades workers24.123 Design, engineering, science and transport professionals23.1*83 Factory process workers22.589 Other labourers21.782 Construction and mining labourers21.254 Inquiry clerks and receptionists21.236 Skilled animal and horticultural workers20.774 Storepersons20.112 Farmers and farm managers20.055 Numerical clerks19.256 Clerical and office support workers18.1*41 Health and welfare support workers17.727 Legal, social and welfare professionals16.9*13 Specialist managers16.271 Machine and stationary plant operators16.072 Mobile plant operators15.862 Sales assistants and salespersons15.544 Protective service workers14.751 Office managers and program administrators13.842 Carers and aides13.524 Education professionals12.035 Food trades workers8.332 Automotive and engineering trades workers7.881 Cleaners and laundry workers5.4*33 Construction trades workers3.534 Electrotechnology and telecommunications trades workers3.2*Notes: Base is all graduates, irrespective of reason for study, who were employed as at May 2007, excluding those from theACE sector and unknown intended ANZSCO; matching between intended and destination occupation occurs at the sub-major group level. Some sub-major group level occupations are not presented due too few numbers in sample cells. * Relative standard error greater than 25%; estimate should be used with caution. Source: Table A3. Figure 1 Courses ranked from most specific to most generic, by selected ANZSCO, 2007 Note: The figure presents, for each intended occupation, the number of graduates in the intended occupation relative to the number of graduates in other jobs who report that the training is relevant. Source: Derived from table A3. Conclusion We began this paper with the statement that vocational education and training was vocational in intentits purpose, unashamedly instrumental, being about providing skills to be used in work. We said that school and university education, by contrast, were less instrumental in nature, often being seen as ends in their own right. The question now is does this view stand up to scrutiny, or should we start to rethink the nature of vocational education? We began by looking at the match between what people study and the jobs they get. Here we found that the match was pretty poor in most occupational groupstechnicians and trades workers being the exception rather than the rule. We tried to understand this mismatch by looking at the changes in skill level for the graduates not employed in their intended occupation. For some occupations, most notably professionals, a high percentage of graduates were employed at a lower skill level. By contrast, relatively few community and personal service workers and sales workers were employed at a lower skill level. Finally, we came to the crux of the issue: whether the low level of matching in the majority of occupations meant a waste of training, or whether the training was being used as a generic preparation? It appears that a narrow view of VET is appropriate only for a few courses. There are a number of trade courses (plus a couple of others) where it makes sense to design the course around a particular occupational setting. These courses would appear to fit very naturally into the world of training packages developed by industry skills councils. However, the majority of courses do not fit into this pattern, and the majority of graduates do not end up in the occupation which is the intended occupation for the course. Most of VET is generic in this sense. This does not imply that the industry focus of VET is wrong, but it does imply that course designers need to be very wary of the range of contexts in which graduates are likely to use the skills they have acquired. It also implies that planners need to be very wary of trying to match training to particular occupations. This view is supported by the finding that the distribution of employment after completion of vocational training bears closer correspondence to the overall workforce distribution of employment than it does to the intended areas of training. This, according to Cully et al. (2006), suggests that labour demand holds sway over supply and that the generic skills delivered through VET are valuable to employers. While our conclusion overall is that the mismatch reflects the generic nature of VET rather than wastage, this is an overall conclusion not a universal one. There are clear examples of wastage in the sector, where graduates do not end up in jobs where the training is relevant. This must be of concern to planners and to potential students. The obvious example here is courses for arts and media professionals. They may be very good courses and provide sound technical training, but they are clear examples of wasted training effortif training is focused on the needs of the labour market. However, such courses are very much in the minority, and the relevance of VET training to the labour market is the positive conclusion from this analysis. References ABS (Australian Bureau of Statistics) 2005, Information paperAustralian and New Zealand Standard Classification of Occupations, cat.no.1221.0, ABS, Canberra. Cully, M, Nguyen, N & John, D 2004, Training for what? Occupational destinations of VET students, ϲʿ¼, Adelaide. Cully, M, Delaney, M, Ong, K & Stanwick, J 2006, Matching skill development to employment opportunities in New South Wales, commissioned paper for the Independent Pricing and Regulatory Tribunal of New South Wales, ϲʿ¼, Adelaide. ϲʿ¼ (ϲʿ¼) 2007, Student outcomes 2007Summary, ϲʿ¼, Adelaide. Appendix Table A1 Skill level by ANZSCO ANZSCO 4-digitDescriptionSkill level1111Chief executives and managing directors11112General managers11113Legislators11211Aquaculture farmers11212Crop farmers11213Livestock farmers11214Mixed crop and livestock farmers11311Advertising and sales managers11321Corporate services managers11322Finance managers11323Human resource managers11324Policy and planning managers11325Research and development managers11331Construction managers11332Engineering managers11333Importers, exporters and wholesalers11334Manufacturers11335Production managers11336Supply and distribution managers11341Child care centre managers11342Health and welfare services managers11343School principals11344Other education managers11351ICT managers11391Commissioned officers (management)11392Senior non-commissioned defence force members11399Other specialist managers11411Cafe and restaurant managers21412Caravan park and camping ground managers21413Hotel and motel managers21414Licensed club managers21419Other accommodation and hospitality managers21421Retail managers21491Amusement, fitness and sports centre managers21492Call or contact centre and customer service managers21493Conference and event organisers21494Transport services managers21499Other hospitality, retail and service managers22111Actors, dancers and other entertainers12112Music professionals12113Photographers12114Visual arts and crafts professionals12121Artistic directors, and media producers and presenters12122Authors, and book and script editors12123Film, television, radio and stage directors12124Journalists and other writers12211Accountants12212Auditors, company secretaries and corporate treasurers12221Financial brokers22222Financial dealers12223Financial investment advisers and managers12231Human resource professionals12232ICT trainers12233Training and development professionals12241Actuaries, mathematicians and statisticians12242Archivists, curators and records managers12243Economists12244Intelligence and policy analysts12245Land economists and valuers12246Librarians12247Management and organisation analysts12249Other information and organisation professionals12251Advertising and marketing professionals12252ICT sales professionals12253Public relations professionals12254Technical sales representatives12311Air transport professionals12312Marine transport professionals12321Architects and landscape architects12322Cartographers and surveyors12323Fashion, industrial and jewellery designers12324Graphic and web designers, and illustrators12325Interior designers12326Urban and regional planners12331Chemical and materials engineers12332Civil engineering professionals12333Electrical engineers12334Electronics engineers12335Industrial, mechanical and production engineers12336Mining engineers12339Other engineering professionals12341Agricultural and forestry scientists12342Chemists, and food and wine scientists12343Environmental scientists12344Geologists and geophysicists12345Life scientists12346Medical laboratory scientists12347Veterinarians12349Other natural and physical science professionals12411Early childhood (pre-primary school) teachers12412Primary school teachers12413Middle school teachers (Aus) / intermediate school teachers (NZ)12414Secondary school teachers12415Special education teachers12421University lecturers and tutors12422Vocational education teachers (Aus)/polytechnic teachers (NZ)12491Education advisers and reviewers12492Private tutors and teachers12493Teachers of English to speakers of other languages12511Dieticians12512Medical imaging professionals12513Occupational and environmental health professionals12514Optometrists and orthoptists12515Pharmacists12519Other health diagnostic and promotion professionals12521Chiropractors and osteopaths12522Complementary health therapists12523Dental practitioners12524Occupational therapists12525Physiotherapists12526Podiatrists12527Speech professionals and audiologists12531Generalist medical practitioners12532Anaesthetists12533Internal medicine specialists12534Psychiatrists12535Surgeons12539Other medical practitioners12541Midwives12542Nurse educators and researchers12543Nurse managers12544Registered nurses12611ICT business and systems analysts12612Multimedia specialists and web developers12613Software and applications programmers12621Database and systems administrators, and ICT security specialists12631Computer network professionals12632ICT support and test engineers12633Telecommunications engineering professionals12711Barristers12712Judicial and other legal professionals12713Solicitors12721Counsellors12722Ministers of religion12723Psychologists12724Social professionals12725Social workers12726Welfare, recreation and community arts workers13111Agricultural technicians23112Medical technicians23113Primary products inspectors23114Science technicians23121Architectural, building and surveying technicians23122Civil engineering draftspersons and technicians23123Electrical engineering draftspersons and technicians23124Electronic engineering draftspersons and technicians23125Mechanical engineering draftspersons and technicians23126Safety inspectors23129Other building and engineering technicians23131ICT support technicians23132Telecommunications technical specialists23211Automotive electricians33212Motor mechanics33221Metal casting, forging and finishing trades workers33222Sheetmetal trades workers33223Structural steel and welding trades workers33231Aircraft maintenance engineers33232Metal fitters and machinists33233Precision metal trades workers33234Toolmakers and engineering patternmakers33241Panelbeaters33242Vehicle body builders and trimmers33243Vehicle painters33311Bricklayers and stonemasons33312Carpenters and joiners33321Floor finishers33322Painting trades workers33331Glaziers33332Plasterers33333Roof tilers33334Wall and floor tilers33341Plumbers33411Electricians33421Airconditioning and refrigeration mechanics33422Electrical distribution trades workers33423Electronics trades workers33424Telecommunications trades workers33511Bakers and pastrycooks33512Butchers and smallgoods makers33513Chefs23514Cooks33611Animal attendants and trainers33612Shearers33613Veterinary nurses33621Florists33622Gardeners33623Greenkeepers33624Nurserypersons33911Hairdressers33921Binders, finishers and screen printers33922Graphic pre-press trades workers33923Printers33931Canvas and leather goods makers33932Clothing trades workers33933Upholsterers33941Cabinetmakers33942Wood machinists and other wood trades workers33991Boat builders and shipwrights33992Chemical, gas, petroleum and power generation plant operators33993Gallery, library and museum technicians23994Jewellers33995Performing arts technicians33996Signwriters33999Other miscellaneous technicians and trades workers34111Ambulance officers and paramedics24112Dental hygienists, technicians and therapists24113Diversional therapists34114Enrolled and mothercraft nurses24115Indigenous health workers24116Massage therapists24117Welfare support workers24211Child carers44221Education aides44231Aged and disabled carers44232Dental assistants44233Nursing support and personal care workers44234Special care workers44311Bar attendants and baristas44312Cafe workers54313Gaming workers44314Hotel service managers34315Waiters44319Other hospitality workers54411Defence force members other ranks34412Fire and emergency workers34413Police24421Prison officers44422Security officers and guards54511Beauty therapists44512Driving instructors34513Funeral workers24514Gallery, museum and tour guides44515Personal care consultants44516Tourism and travel advisers44517Travel attendants34518Other personal service workers54521Fitness instructors44522Outdoor adventure guides44523Sports coaches, instructors and officials34524Sportspersons35111Contract, program and project administrators25121Office managers25122Practice managers25211Personal assistants35212Secretaries35311General clerks45321Keyboard operators45411Call or contact centre workers45412Inquiry clerks45421Receptionists45511Accounting clerks45512Bookkeepers45513Payroll clerks45521Bank workers45522Credit and loans officers45523Insurance, money market and statistical clerks45611Betting clerks55612Couriers and postal deliverers55613Filing and registry clerks55614Mail sorters55615Survey interviewers55616Switchboard operators55619Other clerical and office support workers55911Purchasing and supply logistics clerks45912Transport and despatch clerks45991Conveyancers and legal executives25992Court and legal clerks35993Debt collectors45994Human resource clerks45995Inspectors and regulatory officers45996Insurance investigators, loss adjusters and risk surveyors35997Library assistants45999Other miscellaneous clerical and administrative workers46111Auctioneers, and stock and station agents36112Insurance agents36113Sales representatives46121Real estate sales agents36211Sales assistants (general)56212ICT sales assistants56213Motor vehicle and vehicle parts salespersons46214Pharmacy sales assistants56215Retail supervisors46216Service station attendants56217Street vendors and related salespersons56219Other sales assistants and salespersons56311Checkout operators and office cashiers56391Models and sales demonstrators56392Retail and wool buyers36393Telemarketers56394Ticket salespersons56395Visual merchandisers46399Other sales support workers57111Clay, concrete, glass and stone processing machine operators47112Industrial spraypainters47113Paper and wood processing machine operators47114Photographic developers and printers47115Plastics and rubber production machine operators47116Sewing machinists47117Textile and footwear production machine operators47119Other machine operators47121Crane, hoist and lift operators47122Drillers, miners and shot firers47123Engineering production systems workers47129Other stationary plant operators47211Agricultural, forestry and horticultural plant operators47212Earthmoving plant operators47213Forklift drivers47219Other mobile plant operators47311Automobile drivers47312Bus and coach drivers47313Train and tram drivers47321Delivery drivers47331Truck drivers47411Storepersons48111Car detailers58112Commercial cleaners58113Domestic cleaners58114Housekeepers58115Laundry workers58116Other cleaners58211Building and plumbing labourers58212Concreters58213Fencers48214Insulation and home improvement installers48215Paving and surfacing labourers58216Railway track workers48217Structural steel construction workers48219Other construction and mining labourers58311Food and drink factory workers58312Meat boners and slicers, and slaughterers48313Meat, poultry and seafood process workers58321Packers58322Product assemblers58391Metal engineering process workers58392Plastics and rubber factory workers58393Product quality controllers48394Timber and wood process workers58399Other factory process workers58411Aquaculture workers58412Crop farm workers58413Forestry and logging workers48414Garden and nursery labourers58415Livestock farm workers58416Mixed crop and livestock farm workers58419Other farm, forestry and garden workers58511Fast food cooks58512Food trades assistants58513Kitchenhands58911Freight and furniture handlers58912Shelf fillers58991Caretakers58992Deck and fishing hands48993Handypersons58994Motor vehicle parts and accessories fitters48995Printing assistants and table workers48996Recycling and rubbish collectors58997Vending machine attendants58999Other miscellaneous labourers5Source: ABS (2005). Table A2 Top 10 destination occupations and percentage reporting training highly or somewhat relevant for intended occupations at the sub-major group level, by selected ANZSCO, 2007 Managers Destination occupationFarmers and farm managers%Cumulative %% reporting training was highly or somewhat relevantFarmers and farm managers 33.494.6Farm, forestry and garden workers 22.455.888.2Engineering, ICT and science technicians 5.661.486.7Skilled animal and horticultural workers 3.865.282.7Other labourers 2.567.742.9Mobile plant operators 2.470.169.0Automotive and engineering trades workers 2.372.418.2Factory process workers 2.374.771.4Design, engineering, science and transport professionals 2.276.961.0Office managers and program administrators 2.279.187.1Note: Total number of respondents: 558. Destination occupationSpecialist managers%Cumulative %% reporting training was highly or somewhat relevantCarers and aides 17.596.2Specialist managers 8.325.894.5Business, human resource and marketing professionals 7.633.492.5Sales assistants and salespersons 7.540.956.1General clerical workers 6.347.280.9Office managers and program administrators 6.153.391.5Hospitality, retail and service managers 4.657.996.2Education professionals 2.860.781.9Other clerical and administrative workers 2.863.585.4Engineering, ICT and science technicians 2.465.983.3Note: Total number of respondents: 1638. Destination occupationHospitality, retail and service managers%Cumulative %% reporting training was highly or somewhat relevantHospitality workers 23.684.2Sales assistants and salespersons 11.134.750.6Sports and personal service workers 10.945.694.9Hospitality, retail and service managers 10.556.178.4Inquiry clerks and receptionists 7.063.179.6Sales support workers 4.567.656.5Office managers and program administrators 3.671.284.1General clerical workers 3.574.752.2Food trades workers 3.277.986.8Business, human resource and marketing professionals 1.879.757.7Note: Total number of respondents: 531. Professionals Destination occupationArts and media professionals%Cumulative %% reporting training was highly or somewhat relevantSales assistants and salespersons 21.218.0Arts and media professionals 7.528.769.9Hospitality workers 7.135.85.2Education professionals 7.042.895.5Other labourers 5.448.2n/aOther technicians and trades workers 4.452.658.7Sales support workers 4.256.826.4Carers and aides 3.760.527.3Specialist managers 3.263.732.6Business, human resource and marketing professionals 3.066.730.5Note: Total number of respondents: 224. Destination occupationBusiness, human resource and marketingprofessionals%Cumulative %% reporting training was highly or somewhat relevantNumerical clerks 22.993.9Business, human resource and marketing professionals 15.037.997.0Sales assistants and salespersons 9.447.328.2General clerical workers 6.253.585.0Specialist managers 5.258.789.7Other clerical and administrative workers 4.963.675.0Hospitality, retail and service managers 3.867.483.9Inquiry clerks and receptionists 3.871.247.1Hospitality workers 3.774.914.8Office managers and program administrators 3.077.988.7Note: Total number of respondents: 537. Destination occupationDesign, engineering, science and transportprofessionals%Cumulative %% reporting training was highly or somewhat relevantDesign, engineering, science and transport professionals 16.985.2Farm, forestry and garden workers 15.732.696.8Farmers and farm managers 11.544.195.9Mobile plant operators 7.2**51.33.8Skilled animal and horticultural workers 5.356.666.7Protective service workers 4.861.489.3Other labourers 4.065.487.4Other clerical and administrative workers 3.068.489.3Specialist managers 2.871.275.5General clerical workers 2.573.750.1Notes: Total number of respondents: 197. ** Fewer than 5 respondents in cell. Destination occupationEducation professionals%Cumulative %% reporting training was highly or somewhat relevantEducation professionals 31.089.5Business, human resource and marketing professionals 15.946.996.5Health professionals 5.352.289.5Specialist managers 5.257.489.0Office managers and program administrators 4.862.294.2Engineering, ICT and science technicians 3.065.286.0Health and welfare support workers 3.068.281.1Protective service workers 2.871.084.1General clerical workers 2.773.771.0Machine and stationary plant operators 2.676.395.0Note: Total number of respondents: 1072. Destination occupationICT professionals%Cumulative %% reporting training was highly or somewhat relevantEngineering, ICT and science technicians 21.885.4ICT professionals 16.137.9100.0Electrotechnology and telecommunications trades workers 8.6**46.5100.0Sales support workers 7.1**53.6n/aOther labourers 6.4**60.0n/aFood preparation assistants 4.9**64.9n/aDesign, engineering, science and transport professionals 4.369.2100.0Education professionals 3.9**73.181.6Hospitality workers 3.7**76.8n/aStorepersons 3.7**80.5n/aNotes: Total number of respondents: 65. ** Fewer than 5 respondents in cell. Destination occupationLegal, social and welfare professionals%Cumulative %% reporting training was highly or somewhat relevantLegal, social and welfare professionals 28.2100.0Health and welfare support workers 28.056.275.0Carers and aides 22.078.287.7Hospitality workers 4.3**82.5n/aSpecialist managers 3.8**86.3100.0Office managers and program administrators 3.8**90.1100.0Protective service workers 3.2**93.3100.0Other clerical and administrative workers 2.1**95.4100.0Education professionals 1.7**97.1100.0Sales assistants and salespersons 1.5**98.6n/aNotes: Total number of respondents: 57. ** Fewer than 5 respondents in cell. Technicians and trades workers Destination occupationEngineering, ICT and science technicians%Cumulative %% reporting training was highly or somewhat relevantEngineering, ICT and science technicians 20.693.1ICT professionals 8.028.693.5Education professionals 7.135.787.7Sales assistants and salespersons 6.241.915.7Health professionals 4.546.492.8Specialist managers 3.650.094.5Design, engineering, science and transport professionals 3.653.689.2Business, human resource and marketing professionals 3.356.972.8Food preparation assistants 2.859.712.7Automotive and engineering trades workers 2.762.483.2Note: Total number of respondents: 895. Destination occupationAutomotive and engineering trades workers%Cumulative %% reporting training was highly or somewhat relevantAutomotive and engineering trades workers 72.397.6Electrotechnology and telecommunications trades workers 3.675.998.7Engineering, ICT and science technicians 2.178.069.1Construction and mining labourers 1.979.974.1Factory process workers 1.781.643.7Design, engineering, science and transport professionals 1.683.279.0Machine and stationary plant operators 1.584.786.9Other labourers 1.486.143.0Other technicians and trades workers 1.287.3100.0Road and rail drivers 1.288.556.5Note: Total number of respondents: 1374. Destination occupationConstruction trades workers%Cumulative %% reporting training was highly or somewhat relevantConstruction trades workers 81.195.7Specialist managers 2.483.590.5Automotive and engineering trades workers 2.085.582.5Other technicians and trades workers 2.087.5100.0Construction and mining labourers 1.789.263.3Protective service workers 1.5**90.7100.0Machine and stationary plant operators 1.392.092.9Other labourers 1.293.295.1Factory process workers 1.194.350.7Unknown destination occupation0.8**95.1n/aNotes: Total number of respondents: 687. ** Fewer than 5 respondents in cell. Destination occupationElectrotechnology and telecommunications trades workers%Cumulative %% reporting training was highly or somewhat relevantElectrotechnology and telecommunications trades workers 85.795.2Engineering, ICT and science technicians 2.888.5100.0Automotive and engineering trades workers 2.490.987.1Other labourers 2.1**93.0100.0Other technicians and trades workers 1.394.3100.0Specialist managers 0.6**94.9100.0Sales assistants and salespersons 0.6**95.527.0Clerical and office support workers 0.5**96.0n/aFactory process workers 0.5**96.564.4Design, engineering, science and transport professionals 0.4**96.9100.0Notes: Total number of respondents: 457. ** Fewer than 5 respondents in cell. Destination occupationFood trades workers%Cumulative %% reporting training was highly or somewhat relevantFood trades workers 76.497.2Food preparation assistants 4.080.463.9Hospitality, retail and service managers 3.483.896.5Sales assistants and salespersons 2.185.978.2Unknown destination occupation1.487.345.1Carers and aides 1.288.556.8Factory process workers 1.289.791.9Education professionals 0.990.688.9Sales representatives and agents 0.9**91.564.4Farmers and farm managers 0.8**92.333.5Notes: Total number of respondents: 480. ** Fewer than 5 respondents in cell. Destination occupationSkilled animal and horticultural workers%Cumulative %% reporting training was highly or somewhat relevantSkilled animal and horticultural workers 43.696.1Farm, forestry and garden workers 14.558.188.5Sales assistants and salespersons 5.463.549.2Farmers and farm managers 4.768.295.2Mobile plant operators 2.871.086.5Other labourers 2.673.662.5Hospitality, retail and service managers 2.275.853.7General clerical workers 2.278.014.8Design, engineering, science and transport professionals 2.180.196.7Factory process workers 1.581.651.9Note: Total number of respondents: 741. Destination occupationOther technicians and trades workers%Cumulative %% reporting training was highly or somewhat relevantOther technicians and trades workers 49.097.5Sales assistants and salespersons 6.655.630.7Arts and media professionals 2.958.584.7Other clerical and administrative workers 2.460.982.9Automotive and engineering trades workers 2.363.294.1Factory process workers 2.365.550.1Farmers and farm managers 2.167.682.7Hospitality workers 2.169.74.6Other labourers 2.071.733.7Business, human resource and marketing professionals 1.973.658.2Note: Total number of respondents: 902. Community and personal service workers Destination occupationHealth and welfare support workers%Cumulative %% reporting training was highly or somewhat relevantHealth and welfare support workers 33.094.1Carers and aides 24.157.193.0Legal, social and welfare professionals 7.965.098.5Sales assistants and salespersons 5.870.816.2Office managers and program administrators 3.274.070.5General clerical workers 2.876.868.9Business, human resource and marketing professionals 2.379.193.7Inquiry clerks and receptionists 2.381.468.7Education professionals 1.983.378.6Sports and personal service workers 1.985.289.6Note: Total number of respondents: 1131. Destination occupationCarers and aides%Cumulative %% reporting training was highly or somewhat relevantCarers and aides 70.997.3Health and welfare support workers 4.775.697.3Sales assistants and salespersons 4.079.69.8Cleaners and laundry workers 2.682.258.5Hospitality workers 1.583.77.4General clerical workers 1.485.140.6Food preparation assistants 1.386.456.3Specialist managers 1.187.5100.0Sales support workers 1.088.52.8Inquiry clerks and receptionists 0.989.431.9Note: Total number of respondents: 3093. Destination occupationHospitality workers%Cumulative %% reporting training was highly or somewhat relevantHospitality workers 29.191.4Sales assistants and salespersons 13.943.052.3Food preparation assistants 9.152.182.9Hospitality, retail and service managers 5.958.084.4Food trades workers 5.363.390.1Carers and aides 2.766.044.3General clerical workers 2.668.620.4Inquiry clerks and receptionists 2.571.135.2Sales support workers 2.573.634.7Education professionals 2.476.064.0Note: Total number of respondents: 1903. Destination occupationProtective service workers%Cumulative %% reporting training was highly or somewhat relevantProtective service workers 34.992.8Business, human resource and marketing professionals 5.640.592.3Automotive and engineering trades workers 4.344.878.0Engineering, ICT and science technicians 3.648.481.8Sports and personal service workers 3.3**51.7100.0Office managers and program administrators 3.154.881.3Design, engineering, science and transport professionals 3.057.880.2Hospitality, retail and service managers 2.860.665.6Food trades workers 2.863.486.7Health and welfare support workers 2.565.976.5Notes: Total number of respondents: 316. ** Fewer than 5 respondents in cell. Destination occupationSports and personal service workers%Cumulative %% reporting training was highly or somewhat relevantSports and personal service workers 26.492.9Sales assistants and salespersons 14.340.728.2Other technicians and trades workers 6.647.391.0General clerical workers 4.251.529.7Inquiry clerks and receptionists 4.155.644.0Sales support workers 4.059.620.5Hospitality workers 3.863.418.8Farmers and farm managers 3.266.69.7Carers and aides 3.069.652.8Hospitality, retail and service managers 2.572.165.5Note: Total number of respondents: 1181. Clerical and administrative workers Destination occupationOffice managers and program administrators%Cumulative %% reporting training was highly or somewhat relevantGeneral clerical workers 13.689.9Office managers and program administrators 10.624.295.2Hospitality, retail and service managers 7.131.395.8Business, human resource and marketing professionals 5.536.895.3Specialist managers 4.941.794.2Numerical clerks 4.946.683.7Other clerical and administrative workers 4.751.396.3Inquiry clerks and receptionists 4.455.793.7Engineering, ICT and science technicians 4.059.794.4Sales assistants and salespersons 4.063.750.9Note: Total number of respondents: 1095. Destination occupationGeneral clerical workers%Cumulative %% reporting training was highly or somewhat relevantGeneral clerical workers 21.190.3Inquiry clerks and receptionists 14.235.390.2Sales assistants and salespersons 8.944.241.5Numerical clerks 5.850.084.7Carers and aides 3.553.549.9Personal assistants and secretaries 3.356.893.5Sales support workers 3.260.038.2Business, human resource and marketing professionals 2.662.669.7Education professionals 2.465.081.7Other clerical and administrative workers 2.367.373.6Note: Total number of respondents: 2912. Destination occupationInquiry clerks and receptionists%Cumulative %% reporting training was highly or somewhat relevantInquiry clerks and receptionists 41.388.3Engineering, ICT and science technicians 8.750.088.8General clerical workers 6.456.478.1Sales support workers 6.462.884.8Sales assistants and salespersons 4.267.024.5Sports and personal service workers 3.070.047.6Food preparation assistants 3.073.053.1Numerical clerks 2.775.765.1Specialist managers 2.277.973.9Other labourers 2.280.152.8Note: Total number of respondents: 317. Destination occupationNumerical clerks%Cumulative %% reporting training was highly or somewhat relevantNumerical clerks 42.189.1Business, human resource and marketing professionals 10.953.091.6General clerical workers 9.162.182.1Sales assistants and salespersons 5.367.445.3Inquiry clerks and receptionists 5.272.669.8Other clerical and administrative workers 4.577.153.6Hospitality, retail and service managers 2.980.088.5Sales support workers 2.282.215.5Hospitality workers 2.084.251.2Office managers and program administrators 2.086.284.6Note: Total number of respondents: 581. Destination occupationOther clerical and administrative workers%Cumulative %% reporting training was highly or somewhat relevantOther clerical and administrative workers 18.793.7Sales assistants and salespersons 10.829.522.1General clerical workers 6.636.188.2Office managers and program administrators 6.442.589.9Storepersons 5.047.578.5Business, human resource and marketing professionals 4.652.189.3Personal assistants and secretaries 4.556.673.3Inquiry clerks and receptionists 3.460.079.3Hospitality workers 3.063.017.5Hospitality, retail and service managers 2.765.773.9Note: Total number of respondents: 290. Sales workers Destination occupationSales representatives and agents%Cumulative %% reporting training was highly or somewhat relevantSales representatives and agents 40.196.9Sales assistants and salespersons 6.947.02.4Business, human resource and marketing professionals 5.752.787.1Inquiry clerks and receptionists 5.658.354.2General clerical workers 4.362.681.3Other clerical and administrative workers 3.265.889.7Hospitality, retail and service managers 2.668.458.1Sales support workers 2.6**71.019.6Personal assistants and secretaries 2.573.5100.0Numerical clerks 2.576.075.8Notes: Total number of respondents: 272. ** Fewer than 5 respondents in cell. Destination occupationSales assistants and salespersons%Cumulative %% reporting training was highly or somewhat relevantSales assistants and salespersons 46.186.8Food preparation assistants 8.654.785.6Hospitality, retail and service managers 7.362.094.3Sales support workers 4.766.793.5Hospitality workers 4.270.972.2Inquiry clerks and receptionists 3.073.961.2Carers and aides 2.576.434.1General clerical workers 1.978.357.0Storepersons 1.579.882.6Automotive and engineering trades workers 1.281.051.1Note: Total number of respondents: 1669. Machinery operators and drivers Destination occupationMachine and stationary plant operators%Cumulative %% reporting training was highly or somewhat relevantMachine and stationary plant operators 22.291.4Automotive and engineering trades workers 12.935.184.4Mobile plant operators 10.345.477.5Construction and mining labourers 7.753.187.5Factory process workers 7.060.183.2Road and rail drivers 4.965.081.0Design, engineering, science and transport professionals 4.169.189.1Other labourers 3.772.874.3Engineering, ICT and science technicians 3.175.975.1Electrotechnology and telecommunications trades workers 3.078.989.4Note: Total number of respondents: 733. Destination occupationMobile plant operators%Cumulative %% reporting training was highly or somewhat relevantMobile plant operators 22.184.8Construction and mining labourers 11.733.886.6Electrotechnology and telecommunications trades workers 8.742.590.1Automotive and engineering trades workers 6.949.466.7Road and rail drivers 6.355.7100.0Other labourers 6.061.7100.0Construction trades workers 4.766.481.7Skilled animal and horticultural workers 4.671.077.1Engineering, ICT and science technicians 3.874.888.9Machine and stationary plant operators 3.778.576.4Note: Total number of respondents: 174. Destination occupationRoad and rail drivers%Cumulative %% reporting training was highly or somewhat relevantRoad and rail drivers 32.386.3Automotive and engineering trades workers 6.338.644.0Mobile plant operators 4.142.754.4Electrotechnology and telecommunications trades workers 3.346.074.2Specialist managers 2.848.846.1Machine and stationary plant operators 2.751.562.4Education professionals 2.654.165.2Protective service workers 2.656.753.0Business, human resource and marketing professionals 2.559.245.8Engineering, ICT and science technicians 2.561.737.5Note: Total number of respondents: 895. Destination occupationStorepersons%Cumulative %% reporting training was highly or somewhat relevantStorepersons 23.795.8Other clerical and administrative workers 12.936.699.3Mobile plant operators 8.044.693.8Sales assistants and salespersons 6.951.561.3Factory process workers 6.558.055.3Other labourers 5.163.166.6Road and rail drivers 5.068.178.1Automotive and engineering trades workers 4.372.480.8Machine and stationary plant operators 3.776.183.9Electrotechnology and telecommunications trades workers 2.578.616.6Note: Total number of respondents: 405. Labourers Destination occupationCleaners and laundry workers%Cumulative %% reporting training was highly or somewhat relevantCleaners and laundry workers 84.890.1Sales assistants and salespersons 2.387.129.3Unknown destination occupation2.0**89.1100.0Other labourers 1.490.563.3Factory process workers 1.2**91.762.1Food preparation assistants 1.1**92.8100.0Carers and aides 0.8**93.647.8Hospitality, retail and service managers 0.7**94.379.5Automotive and engineering trades workers 0.6**94.922.4Sales support workers 0.6**95.5100.0Notes: Total number of respondents: 409. ** Fewer than 5 respondents in cell. Destination occupationConstruction and mining labourers%Cumulative %% reporting training was highly or somewhat relevantConstruction trades workers 26.491.6Construction and mining labourers 18.344.796.4Machine and stationary plant operators 7.552.279.8Automotive and engineering trades workers 6.859.063.7Education professionals 5.364.3100.0Other technicians and trades workers 4.068.377.8Sales assistants and salespersons 3.972.217.1Mobile plant operators 3.976.192.6Other labourers 3.679.755.3Storepersons 3.082.722.1Note: Total number of respondents: 228. Destination occupationFactory process workers%Cumulative %% reporting training was highly or somewhat relevantFactory process workers 31.988.2Automotive and engineering trades workers 12.144.086.4Electrotechnology and telecommunications trades workers 6.350.386.4Construction trades workers 4.755.074.8Machine and stationary plant operators 4.159.176.4Farm, forestry and garden workers 3.562.668.5Mobile plant operators 2.865.458.3Sales assistants and salespersons 2.668.051.8Storepersons 2.470.483.9Other labourers 2.472.834.2Note: Total number of respondents: 952. Destination occupationFarm, forestry and garden workers%Cumulative %% reporting training was highly or somewhat relevantFarm, forestry and garden workers 26.389.1Skilled animal and horticultural workers 9.836.195.9Farmers and farm managers 5.942.084.3Mobile plant operators 4.546.563.8Automotive and engineering trades workers 3.750.253.5Road and rail drivers 3.653.839.9Other labourers 3.257.063.0Unknown destination occupation3.260.267.2Sales assistants and salespersons 3.063.228.3Education professionals 2.966.178.9Note: Total number of respondents: 958. Destination occupationFood preparation assistants%Cumulative %% reporting training was highly or somewhat relevantFood trades workers 21.378.5Food preparation assistants 13.735.088.6Hospitality workers 8.643.684.0Sales assistants and salespersons 8.652.259.8Hospitality, retail and service managers 6.959.184.2Cleaners and laundry workers 4.663.78.3Education professionals 4.468.184.5Sales support workers 3.972.031.5Carers and aides 3.575.582.8General clerical workers 3.579.025.9Note: Total number of respondents: 250. Destination occupationOther labourers%Cumulative %% reporting training was highly or somewhat relevantAutomotive and engineering trades workers 38.0  90.1 Electrotechnology and telecommunications trades workers 11.0 49.0  90.2 Other labourers 8.2  57.2  83.1 Design, engineering, science and transport professionals 4.7  61.9  91.7 Sales assistants and salespersons 3.3  65.2 38.1 Protective service workers 2.7  67.9  69.6 Engineering, ICT and science technicians 2.4 70.3  69.4 Education professionals 2.0 72.3  94.1 Other technicians and trades workers 1.9 74.2  56.1 Sports and personal service workers 1.8 76.0 72.0 Note: Total number of respondents: 1339. Source: ϲʿ¼ Student Outcomes Survey, 2007. Table A3 Training relevance by intended occupation: graduates for whom intended and destination occupations do not match at the sub-major group level, by selected ANZSCO, 2007 Intended occupationNot employed in intended occupationEmployed in intended occupationTraining is highly or somewhat relevantTraining has very little or no relevanceTraining relevance unknownOccupation after training unknown%%%%%1 Managers14.165.919.10.1* 0.812 Farmers and farm managers 33.445.220.00.01.3*13 Specialist managers 8.374.516.20.2** 0.7*14 Hospitality, retail and service managers 10.563.125.90.1** 0.4**2 Professionals 21.552.624.40.3** 1.2*21 Arts and media professionals 7.5* 26.463.60.02.5*22 Business, human resource and marketing professionals 15.055.927.10.6** 1.4*23 Design, engineering, science and transport professionals 16.959.123.1* 0.00.9**24 Education professionals 31.055.712.00.3** 1*26 ICT professionals 16.1* 47.136.70.00.027 Legal, social and welfare professionals 28.254.916.9* 0.00.03 Technicians and trades workers 60.624.214.20.1* 0.931 Engineering, ICT and science technicians 20.647.631.20.00.6*32 Automotive and engineering trades workers 72.318.67.80.1** 1.1*33 Construction trades workers 81.114.63.50.00.8**34 Electrotechnology and telecommunications trades workers 85.710.93.2* 0.00.2**35 Food trades workers 76.413.88.30.1** 1.4*36 Skilled animal and horticultural workers 43.634.320.70.1** 1.3*39 Other technicians and trades workers 49.026.124.10.2** 0.6*4 Community and personal service workers 43.829.425.60.2* 1.041 Health and welfare support workers 33.047.717.70.4** 1.2*42 Carers and aides 70.914.913.50.1** 0.6*43 Hospitality workers 29.135.434.00.3* 1.344 Protective service workers 34.948.214.70.1** 2*45 Sports and personal service workers 26.427.445.00.01.1*5 Clerical and administrative workers 23.053.722.30.1* 0.951 Office managers and program administrators 10.675.013.80** 0.6*53 General clerical workers 21.151.525.90.2* 1.354 Inquiry clerks and receptionists 41.337.021.20.00.5**55 Numerical clerks 42.138.119.20.00.6*56 Clerical and office support workers 0.075.718.1* 6.2** 0.059 Other clerical and administrative workers 18.752.228.60.00.4**6 Sales workers45.237.317.10.1** 0.3*61 Sales representatives and agents 40.133.426.00.00.5**62 Sales assistants and salespersons 46.138.015.50.1** 0.3*7 Machinery operators and drivers 26.647.724.70.2* 0.771 Machine and stationary plant operators 22.260.816.00.2** 0.8*72 Mobile plant operators 22.161.615.80.00.5**73 Road and rail drivers 32.331.635.30.1** 0.7*74 Storepersons 23.755.020.10.5** 0.7**8 Labourers25.549.922.50.3* 1.981 Cleaners and laundry workers 84.87.75.4* 0.1** 2**82 Construction and mining labourers 18.359.621.20.4** 0.5**83 Factory process workers31.944.322.50** 1.2*84 Farm, forestry and garden workers26.343.127.20.2** 3.285 Food preparation assistants13.753.329.70.4** 2.9*89 Other labourers8.268.421.70.5* 1.2*Total36.641.221.10.21.0Notes: Base is all graduates, irrespective of reason for study, who were employed as at May 2007, excluding those from theACE sector and unknown intended ANZSCO; matching between intended and destination occupation occurs at the sub-major group level. Some sub-major group level occupations are not presented due too few numbers in sample cells. * Relative standard error greater than 25%; estimate should be used with caution. ** Fewer than 5 respondents in cell. Source: ϲʿ¼ Student Outcomes Survey, 2007. Table A4 Estimated populations of graduates by intended occupation, by selected ANZSCO, 2007 Intended occupation of training activityNumber of graduates1 Managers28 34012 Farmers and farm managers5 80013 Specialist managers16 44014 Hospitality, retail and service managers6 1002 Professionals25 61021 Arts and media professionals3 24022 Business, human resource and marketing professionals8 13023 Design, engineering, science and transport professionals2 88024 Education professionals9 76026 ICT professionals1 24027 Legal, social and welfare professionals3403 Technicians and trades workers75 43031 Engineering, ICT and science technicians12 84032 Automotive and engineering trades workers18 71033 Construction trades workers9 47034 Electrotechnology and telecommunications trades workers6 22035 Food trades workers6 92036 Skilled animal and horticultural workers9 67039 Other technicians and trades workers11 6004 Community and personal service workers93 70041 Health and welfare support workers11 47042 Carers and aides32 62043 Hospitality workers29 97044 Protective service workers4 28045 Sports and personal service workers15 3605 Clerical and administrative workers67 95051 Office managers and program administrators10 67053 General clerical workers41 49054 Inquiry clerks and receptionists4 79055 Numerical clerks7 34056 Clerical and office support workers20059 Other clerical and administrative workers3 4606 Sales workers24 68061 Sales representatives and agents3 64062 Sales assistants and salespersons21 0307 Machinery operators and drivers30 55071 Machine and stationary plant operators9 89072 Mobile plant operators2 11073 Road and rail drivers12 44074 Storepersons6 1108 Labourers52 01081 Cleaners and laundry workers3 70082 Construction and mining labourers2 74083 Factory process workers12 37084 Farm, forestry and garden workers14 11085 Food preparation assistants4 32089 Other labourers14 770Total398 270Note: Some sub-major group level occupations are not presented do due too few numbers in sample cells. Source: ϲʿ¼ Student Outcomes Survey, 2007.  ANZSCO replaced the Australian Standard Classification of Occupations (ASCO) classification in 2006. In this paper we use the more up-to-date classification where possible. The rate of matching is not independent of the classification. A comparison of table 1 with Cully, Nguyen and John (2004) suggests that the rate of matching is higher under ANZSCO than ASCO (36.6% compared with 22.8% at the sub-major group level).  Appendix table A4 provides the estimated number of graduates from the Student Outcomes Survey for all sub-major group level courses.      PAGE 46 Is VET vocational? 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alm$$Ifl!vh5+5#v+#v:V<l t5+5/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t5+5n52/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52/ alm$$Ifl!vh5+5#v+#v:V<l t5+5/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t5+5n52/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52/ alm$$Ifl!vh5+5#v+#v:V<l t5+5/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t5+5n52/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52/ alm$$Ifl!vh5+5#v+#v:V<l t5+5/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t5+5n52/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t,5+5n52/ alm$$Ifl!vh5+5#v+#v:V<l t5+5/ al$$Ifl!vh5+5n5n52#v+#vn#v2:V<l t5+5n52/ 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