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.

• 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

Background - General

• Completion of apprenticeships is influenced by:Age;level of schooling;Indigenous status;Location;level of qualification, and;the type of employer.

• 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 ratesor, that women have lower completion rates

than males or, that there is no real difference in non-

completion 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 - General

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.

• 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.

Background – Impact of gender

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

Demographicsa: Indigenous persons, by gender b: Disabled persons, by gender

c: Persons from a non-English speaking background, by gender

Educationa: Year 9 b: Year 10

c: Year 11 d: Year 12

Occupationa: ASCO 41-44 (Traditional trades) b: ASCO 45 (The food trades)

c: ASCO 49 (Other trades)

Specific occupationsa: ASCO 4512, Pastry cooks b: ASCO 4512, Cooks

c: ASCO 4931, Hairdressers

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.

c o e f e x p (c o e f ) pa g e 0 .0 0 6 1 .0 0 6 0 .0 0 0a t s i 0 .2 5 9 1 .2 9 5 0 .2 5 0d i s a b i l i t y 0 .0 9 2 1 .0 9 7 0 .6 1 0l a n g u a g e 0 .4 8 2 1 .6 1 9 0 .0 0 1y e a r1 0 -0 .2 3 0 0 .7 9 5 0 .1 4 0y e a r1 1 -0 .3 3 6 0 .7 1 4 0 .0 2 1y e a r1 2 -0 .5 5 2 0 .5 7 6 0 .0 2 7a s c o 4 1 -0 .4 0 0 0 .6 7 0 0 .9 8 0a s c o 4 2 -0 .5 1 7 0 .5 9 7 0 .4 9 0a s c o 4 3 0 .0 3 8 1 .0 3 9 0 .2 4 0a s c o 4 4 -0 .1 0 9 0 .8 9 7 0 .9 9 0a s c o 4 9 -0 .6 1 5 0 .5 4 1 0 .2 7 0e m p g t o 0 .0 6 4 1 .0 6 6 0 .5 2 0t ra i n r t o 0 .1 9 1 1 .2 1 1 0 .1 5 0t ra i n c l o s e d 1 .4 7 6 4 .3 7 7 0 .0 0 0t ra i n p u b l i c -0 .8 1 9 0 .4 4 1 0 .4 2 0l i n c o m e -3 .6 6 7 0 .0 2 6 0 .1 8 0

S c o re ( l o g ra n k ) t e s t = 1 8 6 9 o n 3 4 d f , p = 0

L i k e l i h o o d ra t i o t e s t = 1 4 7 2 o n 3 4 d f , p = 0W a l d t e s t = 1 6 4 0 o n 3 4 d f , p = 0

1 .1 4 7R s q u a re = 0 .1 6 9

0 .5 1 4 0 .1 3 7

0 .6 3 80 .1 3 5 -0 .5 9 5 0 .5 5 10 .0 6 2 -0 .4 4 9

0 .9 2 90 .0 4 4 -0 .1 3 1 0 .8 7 70 .0 4 2 -0 .0 7 3

0 .9 9 70 .0 7 2 0 .1 2 2 1 .1 3 00 .0 9 1 -0 .0 0 3

1 .2 2 60 .1 2 9 -0 .8 3 9 0 .4 3 20 .0 6 1 0 .2 0 4

1 .5 8 00 .1 1 0 0 .0 1 1 1 .0 1 10 .0 7 9 0 .4 5 7

1 .3 5 50 .0 8 6 0 .5 1 6 1 .6 7 50 .0 7 9 0 .3 0 4

0 .9 1 20 .1 3 1 -1 .1 5 5 0 .3 1 50 .0 6 6 -0 .0 9 2

0 .9 7 10 .0 8 9 -0 .2 4 7 0 .7 8 10 .0 0 4 -0 .0 2 9

T a b le 1 0 : C o x p ro p o rtio n a l h a z a rd m o d e l o f c a n c e lla tio n w ith g e n d e r in te ra c tio n te rm s

G e n d e r i n t e ra c t i o n t e rm ss e (c o e f ) c o e f e x p (c o e f)

Multivariate analysis of cancellation

Reasons for cancellation

0.0 10.0 20.0 30.0

D e c e a s e dM u t u a l C o n s e n t

E m p l o y e r C a n n o t P r o v i d e T r a i n i n gD i f f i c u l t i e s O n - t h e - J o b

D i f f i c u l t i e s O f f - t h e - J o bE m p l o y e r C l o s u r e o r S a l e o f B u s i n e s s

A p p r e n t i c e M i s c o n d u c tA p p r e n t i c e H a s A n o t h e r J o b

I n a d e q u a t e W a g eP e r s o n a l o r M e d i c a l R e a s o n s

P a r t y i s N o t L o c a t a b l eO t h e r o r U n k n o w n R e a s o n

N o O f f - t h e - J o b T r a i n i n g A v a i l a b l eS t a t e T r a i n i n g C o u n c i l D e c i s i o n

T r a i n i n g C o n t r a c t N o t A p p r o v e dI n c o m p a t i b i l i t y

A p p r e n t i c e H a s R e l o c a t e dE m p l o y e r H a s F i n a n c i a l D i f f i c u l t y

T r a i n i n g C o n t r a c t A p p r o v a l R e v o k e dT r a i n i n g R e c o g n i t i o n C o u n c i l

P a r t y i s N o t L o c a t a b l e - S 6 1T r a i n i n g E m p l o y m e n t R e c o g n i t i o n

% C o n t r ib u t io n b y re a s o n

F e m a le

M a le

F i g u re 1 6 a : A g e p ro f i l e o f i n d i vi d u a l s w h o c a n c e l l e d fo r P e rs o n a l o r m e d i c a l re a s o n s F i g u re 1 6 b : H i g h e s t ye a r o f s c h o o l i n g o f i n d i vi d u a l s w h o c a n c e l l e d fo r P e rs o n a l o r m e d i c a l re a s o n s

F i g u re 1 6 c : A S C O s e c o n d d i v i s i o n o c c u p a t i o n o f e m p l o ym e n t fo r i n d i vi d u a l s w h o c a n c e l l e d fo r P e rs o n a l o r m e d i c a l re a s o n s

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5 . 0

1 0 . 0

1 5 . 0

2 0 . 0

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4 0 . 0

1 5 - 1 7 1 8 - 1 9 2 0 - 2 4 2 5 - 3 4 3 5 - 4 4 4 5 + A ge c o h o rt

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10.0

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40.0

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60.0

year 9 year 10 year 11 year 12H i ghe s t ye a r o f s c ho o l ing

% o

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70.0

ASCO41 ASCO42 ASCO43 ASCO44 ASCO45 ASCO49A ge c o ho rt

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M a l e F e m a le

Reasons for cancellation

• 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.

Key issues

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.

Implications