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The role of gender in the decision to cancel the apprenticeship training contract Bernard Trendle, Alexandra Winter and Sophia Maalsen Training and Skills Research Unit, DET and Office for Women Background • Apprenticeship is an important pathway for young people. • The introduction of traineeships has provided a new form of on-the-job training in female dominated industries. • This research presents an analysis of cancellation rates from apprenticeship, focussing on the role of gender. • Techniques from duration modelling are used to explore differences in completion rates. Background • While there are numerous studies of the issue of drop-outs from education, studies of apprenticeship cancellation are rare. • Women have much lower levels of participation in apprenticeship pathways. • Over 80% of Queensland’s apprentice commencements are male. Background - General • Completion of apprenticeships is influenced by: Age; level of schooling; Indigenous status; Location; level of qualification, and; the type of employer. Background - General • Gender has also been identified as a demographic variable influencing outcomes, but these findings can be variable: some find that women have significantly higher completion rates or, that women have lower completion rates than males or, that there is no real difference in noncompletion between males and females Background - General • Apprenticeship combines work and training. – The training wage paid is an incentive for employers to employ someone not yet qualified. • A 2008 survey found that, both completers and non-completers were dissatisfied with the training wage. • In addition to low training wages, increased knowledge of wages and conditions may influence the completion decision of apprentices. Background – Impact of gender • Key themes of impact of gender include: attitudes towards “appropriate” work for men and women; social stereotypes; perceptions of traditional trades and employer attitudes about the “employability” of women. • It has also been argued that the women are required to adapt to the culture of the trade. Background – Impact of gender • Some analysis suggests that outcomes from apprenticeship training are gendered. For example: VET study tends to benefit young men (particularly Indigenous, and regional/rural). The financial outcomes from apprenticeships have been found to be lesser for females than males. Background – Impact of gender • Similarly, LSAY data has revealed that males who complete apprenticeships experience the best labour market outcomes of VET participants. Full-time employment among former apprentices is high, at more than 90.0%, and their earnings are higher than those reported by other VET participants. Full-time employment outcomes were highest for apprenticeships, followed by traineeships, and non-apprenticeship courses. Female apprenticeship completers, experience less favourable outcomes (higher part-time employment and unemployment, lower wages) than their male counterparts. Preliminary Analysis • Analysis here makes use of data from the DELTA database. • Statistical tools from the field of Survival analysis or Duration modelling are used. • 2001 is the base year for the analysis. • The base data unit is the training contract Kaplan-Meier curve for male and female apprenticeship completion Demographics a: Indigenouspersons, bygender c: Personsfromanon-Englishspeakingbackground, bygender b: Disabledpersons, bygender Education a: Year 9 b: Year 10 c: Year 11 d: Year 12 Occupation a: ASCO41-44(Traditional trades) c: ASCO49(Other trades) b: ASCO45(Thefoodtrades) Specific occupations a: ASCO4512, Pastrycooks c: ASCO4931, Hairdressers b: ASCO4512, Cooks Multivariate analysis of cancellation • While the techniques conducted in the preceding section are flexible and easy to interpret, they have a number of limitations. • Chief among these is the fact that univariate techniques limit analysis to the stratification by one variable at a time. • A better approach is to use multivariate techniques, and we estimate a model using CPH. Multivariate analysis of cancellation Table 10: Cox proportional hazard model of cancellation with gender interaction terms coef exp(coef) se(coef) age 0.006 1.006 0.004 atsi 0.259 1.295 0.089 disability 0.092 1.097 0.066 language 0.482 1.619 0.131 year10 -0.230 0.795 0.079 year11 -0.336 0.714 0.086 year12 -0.552 0.576 0.079 asco41 -0.400 0.670 0.110 asco42 -0.517 0.597 0.061 asco43 0.038 1.039 0.129 asco44 -0.109 0.897 0.091 asco49 -0.615 0.541 0.072 empgto 0.064 1.066 0.042 trainrto 0.191 1.211 0.044 trainclosed 1.476 4.377 0.062 trainpublic -0.819 0.441 0.135 lincome -3.667 0.026 0.514 Rsquare = 0.169 Likelihood ratio test = 1472 on 34 df, p = 0 Wald test = 1640 on 34 df, p = 0 Score (logrank) test = 1869 on 34 df, p = 0 Gender interaction terms coef exp(coef) p -0.029 0.971 0.000 -0.247 0.781 0.250 -0.092 0.912 0.610 -1.155 0.315 0.001 0.304 1.355 0.140 0.516 1.675 0.021 0.457 1.580 0.027 0.011 1.011 0.980 0.204 1.226 0.490 -0.839 0.432 0.240 -0.003 0.997 0.990 0.122 1.130 0.270 -0.073 0.929 0.520 -0.131 0.877 0.150 -0.449 0.638 0.000 -0.595 0.551 0.420 0.137 1.147 0.180 Reasons for cancellation T raining Employment Recognit ion Part y is Not Locat able - S61 T raining Recognit ion Council T raining Cont ract Approval Revoked Employer Has Financial Difficult y Apprent ice Has Relocat ed Incompat ibilit y T raining Cont ract Not Approved St at e T raining Council Decision No Off-t he-Job T raining Available Ot her or Unknown Reason Part y is Not Locat able Personal or Medical Reasons Inadequat e Wage Apprent ice Has Anot her Job Apprent ice Misconduct Employer Closure or Sale of Business Difficult ies Off-t he-Job Difficult ies On-t he-Job Employer Cannot Provide T raining Mut ual Consent Deceased 0.0 Female Male 10.0 20.0 % Contribution by reason 30.0 Reasons for cancellation Figure 16a: Age profile of individuals who cancelled for Personal or medical reasons Figure 16b: Highest year of schooling of individuals who cancelled for Personal or medical reasons 60.0 40.0 Male Male 30.0 25.0 20.0 15.0 10.0 Female 50.0 Female %of commencements % of commencements 35.0 40.0 30.0 20.0 10.0 5.0 0.0 0.0 15 - 17 18 - 19 20 - 24 25 - 34 Age cohort 35 - 44 45 + year 9 70.0 %of commencements 60.0 Female 50.0 40.0 30.0 20.0 10.0 0.0 ASCO41 ASCO42 ASCO43 ASCO44 Age cohort year 11 Highest year of schooling Figure 16c: ASCO second division occupation of employment for individuals who cancelled for Personal or medical reasons Male year 10 ASCO45 ASCO49 year 12 Key issues • Higher non-completion by females for personal or medical reasons. • Higher cancellation rates for women with higher levels of education. • Mature age women are more likely to complete an apprenticeship. • Public sector training appears to be linked with higher completion rates for females. Implications Policy to minimise the differences in the rate of completion across gender has several options. Firstly, wages and conditions vary across occupation, and some trades have an expected lifetime income below not acquiring a post-school qualification. These low wages imply a relatively low opportunity cost in cancellation. Encouraging female entry into higher paying trades appears to support apprenticeship completion rates. Implications • Research suggests that social stereotyping, perceptions and a workplace culture that has deeply entrenched norms and values can act as barriers to women entering trades. • Such research may identify cultural or workplace issues associated with the traditional trade model. • Therefore, policy may need to seek to effect longer term cultural change.