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The Gender Dimension

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The Gender Dimension

Posted by Niall O'Higgins at July 27. 2010

I think it is worthwhile to introduce one other thread on the gender dimension as it relates to youth ALMPs.

 

I wanted to pick up on some of the issues raised in the previous contributions on this, particularly from Francesco Pastore and Srinivas Reddy.

 

If I understand Francesco correctly, he found that in Mongolia:

 

1) young women earn more than young men; and

 

2) young women had higher educational attainment than young men.

 

Thus finding 1) is explained essentially by finding 2) and indeed, when educational attainment is controlled for, young women earn (around 11%) less than young men in that country.

 

It is is not at all unusual that young women have higher educational attainment than young men, particularly in high income countries - indeed I think in these it is almost universal, in lower income countries, my understanding is that the picture is more mixed, however, here too in recent years in particular it is not so unusual. Despite this, however, it is very unusual to find that women earn MORE than men. Indeed, I am unaware of other countries where this is the case.

 

However, in part this may be due to the fact that we are looking at young people - part of the gender wage gap (perhaps a major part of it) arises from wage dynamics - that is the rate at which wages rise with age. Men tend to have a significantly steeper age-wage profile (their wages rise faster with age than they do for women) - and indeed, Srinivas mentions the issue of occupational segregation which contributes to this phenomenon.

 

Francesco also helps to highlight another important aspect of the issue. That is, young women earn more than young men, but given that they have much higher educational levels (on average) than young men, they should earn even more than they do. That is, they are still subject to negative wage discrimination, which emerges with the more sophisticated analysis controlling for  educational level. This serves to emphasise that discrimination against women (or indeed against other identifiable groups, e.g. ethnic minorities) is not about (in)equality of  earnings per se but about equal pay for work of equal worth (or rather its absence in the presence of discrimination) which is how the relevant ILO conventions frame the issue.

 

Srinivas' point about occupational segregation also serves to remind us that it is not just about wages (although I would argue that occupational segregation serves also to maintain lower wages for women - for work of equal worth)

 

Indeed, as regards ALMPs, one useful role that they can play - as Srinivas Points out - is in shifting attitudes on what is acceptable 'women's' work and so on. Equally, if one is not careful, however, ALMPs (as is all too often the case with VET systems in general) may serve to reinforce gender stereotypes with young women being pushed towrads training and employment in 'female' occupations and so on. I would say that any counter examples - of programmes seeking to redress such imbalances would be particularly welcome

.

As Srinivas says, however, it is not easy since of course women themselves also often subscribe to prevailing value systems and so may be reluctant to participate in certain occupations/training. Srinivas talks of adressing the obstacles to women's participation in such programmes. Although these issues do need to be adressed at the programme design stage, this is also an area where monitoring and evaluation can play a useful role by identifying the precise nature of these obstacles once programmes are underway.

 

Anyway, I think this area is particularly important and I hope we will get some good contributions and examples.

 

Re: The Gender Dimension

Posted by Srinivas Reddy at July 28. 2010

Dear Niall,

 

Thank you for initiating this very important discussion on gender dimensions in ALMPs. To explain the point on occupational segregation I was making earlier, I would like to cite an example of skills development proposal that we received in ILO EAST Project for funding. I would like to remind the colleagues that this proposal to train 87 per cent men and 13 per cent women in 9 skill areas  comes after several rounds of stereotyped proposals sent back to the training providers by the Project implementing partners and ILO EAST colleagues, and after key players involved in the proposal development were trained on gender equality and after having an explicit target of covering at least 40 per cent women benefeciaries.

Please see the below mentioned table:

No

Training Area

Number of Out of School Youth Targeted

Remarks

Male

Female

Total

1

Steel Welding

10

0

10

 

2

Welding

20

0

20

 

3

Computer Technicians

7

5

12

 

4

Mobile Phone servicing

11

5

16

 

5

Furniture manufacturing

12

0

12

 

6

Aluminum furniture manufacturing

10

0

10

 

7

Motor cycle repairs

10

0

10

 

8

Car body repairs and painting

10

0

10

 

9

Bakery and cake production

10

5

15

 

 

 Total

100

15

115

 

This proposal to cover 13 per cent women comes after 2 years of sustained campaign to break the stereotypes and promote gender equality and participation of women in all vocations. This reinforces the need to have ALMPs targeting at various levels with  an intensive component on working at community level to change the mindesets and influence the occupational segregation. Adequate resource allocation and developing local capacities on gender are crucial to make a difference in a sustainable manner.

Any examples and eperiences, promotional tools and case studies from other countries would be highly useful.

Srinivas Reddy

Skills Development Specialist

ILO EAST Project

Re: The Gender Dimension

Posted by silvia cormaci at July 29. 2010

Dear Niall, Srinivas and All,

 

My name is Silvia Cormaci and I work as Associate Expert on Gender Equality in the ILO Bangkok Office.

I would like first to thank you for introducing the gender dimension in the discussion on youth ALMPs. As it was already underlined factors as the gender pay gap (GPG) and occupational segregation play a crucial role.

 

In this regard, the ILO in 2008 published a study on ‘Work, Income and Gender Equality in East Asia’ comparing gender inequalities and in particular gender pay disparities in 8 countries in the Region (China, Hong Kong, Japan, Republic of Korea, Philippines, Singapore, Thailand, Vietnam). The research provides very interesting data on GPG and its determinants and useful suggestions for action. The study can be found under the following link: http://www.ilo.org/public/libdoc/ilo/2008/108B09_295_engl.pdf

 

I would like to highlight here that in the above mentioned countries it was found that the main variables influencing the GPG are age and education; industrial sector and occupation; location, type and size of establishment; and informal and migrant status in employment. While data are scarce and their comparability is limited, based on the information that was available for this guide, the trends seem to be:

  • Age: as was already mentioned, there is a growing gender wage gap by age, with a far larger gap among older than younger workers. The gender wage gap tends to be the narrowest for the young age groups, where women sometimes earn slightly more than men (in Singapore, for instance, women in the 25-29 age group earned more than their male counterparts in a few -mainly white collar- occupations in 2006) and it is significantly wider for the older age groups (Japan and the Republic of Korea). This may be due to a number of reasons: older women may experience the effects of past discrimination, for example they may have had less access to education as compared to their male counterparts, or they may have had less years of work experience.
  • Education:    an ambivalent relationship between the gender wage gap and the level of education, with some data pointing to a narrowing of the gender wage gap with the level of education (Hong Kong SAR and Japan), while other data show the opposite, especially for older workers (Singapore) and/or in urban locations (Viet Nam). As it was already pointed out by Niall, the effects of higher education are not always positive, as pay gaps tend to increase among higher level jobs as for example in Bangladesh, where the pay gap between men and women with tertiary education amounted to 8%. Data from Europe and Chile also show that the wage gap often grows with the level of education. For example, in the European Union the gender pay gap is 30% for those with third-level education and 13% among those with lower level secondary education.
  • No clear cross-country trends for the gender pay gap by industrial sector or occupation: for example, in Thailand, among professional nurses women earned more than men whereas in the Republic of Korea, the female-to-male wage ratio for professional nurses was only 44%. Similarly, the “professionals” occupational category had one of the lowest female-to-male wage ratios in the Republic of Korea and Malaysia, but in Hong Kong SAR and Singapore it was among the occupational categories where the earnings of women and men showed the least disparity
  • A higher gender wage gap in urban areas than rural areas in Viet Nam and Thailand (although this trend does not appear to hold in China)
  •  A wider gender wage gap among private sector workers than workers in the public sector, and in larger enterprises as compared to smaller ones
  • A wider gender wage gap in informal and irregular employment than formal and regular employment, and among part-timers and internal migrant workers as compared to full-timers and non-migrant workers

 

It should be noted, however, that while single-variable data provides a useful indication of the general effect that a variable may have on the gender pay gap, it does not show what the joint impact of these variables is, and how much of the gender pay gap can – or can not – be explained by that joint impact. Because of this, single-variable analysis has the notable disadvantage that it fails to capture the income effects of discrimination against women workers, as the case provided by Srinivas on discrimination on women access to skills training.

 

 Indeed, direct and in particular indirect discrimination has been proved to be the major factor influencing women participation in the labour market, GPG and occupational segregation. As instance, this is the case of Malaysia, where although women have an higher level of education than their male counterpart,  they amount to only around one-third of the total labour force.  Researches in Malaysia show that discrimination play a crucial role here,    being the role of women associated with house and family responsibilities. Many women are not able to join or reenter the labour market after they get married and have children. Providing child care facilities and maternity and paternity benefits is a way to promote an increased balance of work and family responsibilities.

 

It is also very well know that discrimination is the cause of wage gap for work that should be of equal value. In the Philippines for example it was found that nurses (occupation where women are prevalent) earned much less than driver (considered ‘men job’).  It would be useful to determinate wages through job evaluation methodology, establishing the real value of the job and the correspondent pay based on objective criteria and not on the sex of the worker. Also useful are Wage Indicator online salary checks, internet-based salary checkers to construct an information base on wages, allowing workers to assess their salaries against those of others in the same occupation by eg.  sex, occupation.

 

Setting quota to increase women participation at senior level in private and public institutions and codes of conduct in public and private sector to enhance opportunities of career development for women are useful measures to reduce inequalities in the work place.

 

Other measures include the establishment of special promotion and enforcement mechanisms such as the Equal Opportunities Commissions in Hong Kong and the ratification, monitoring and implementation of international legal instruments on gender equality such as the ILO Conventions No. 100 and 111 on non discrimination and equal pay and CEDAW. National laws should also avoid to include discriminatory provisions such as the different retirement age for women and men, which denies women the opportunity of career advancement and to earn additional income.

 

Ok that’s it for now, and thank you again for the opportunity to provide inputs to the discussion!

 

Best

 

Silvia Cormaci

 

Associate Expert on Gender Equality and Migration

ILO Bangkok

 

Re: The Gender Dimension

Posted by Niall O'Higgins at July 29. 2010

Thanks for all your useful and constructive contributions. I would at this stage particularly like to encourage further contributions offering examples or suggestions of specifically how ALMPs an be used to reduce gender discrimination - and above-all, combat occupational segregation -  and how the broader attitudinal issues can be dealt with in this context. 

Niall

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