A NEET Indicator for Post-2015? Let’s be More Precise

By Enrique Pieck, Academic Researcher, Universidad Iberoamericana Ciudad de México, Mexico.

When trying to ensure an effective youth transition to the labor market, it is important to consider the diversity of youth and to define precisely what it is understood by labor market and educational enrollment.

Not in education

When considering to adopt an indicator for NEETs (those not in education, training or employment), we are obliged to reflect upon the diversity behind each term and to disaggregate by sex, age and education level. For example, in Mexico women are the majority within NEET, they are often devoted to housework and that does not show in statistics. Also, when assessing youth that are not studying, age and education level are crucial because it is different to talk about youth that have finished university or youth that have only finished basic or secondary education. Perhaps young people have abandoned school but are enrolled in short training courses. All this leads us to widen the scope of what we consider as ‘not in education’ or ‘not in employment’.

What are we really referring to in a NEET indicator?

If a broader concept of NEET is considered then I think this indicator could be particularly useful when trying to identify problems and social inclusion policies in low-income countries. It is more feasible to find data for indicators that show the amount of young people enrolled in short non formal training programs than to find indicators that show youngsters involved in the informal sector. These indicators could be very useful in order to reflect on how to deal with problems related to how adolescents make the transition from non-formal training courses to the labor market, and also on how to improve work competencies provided by training institutions. However, in low income countries where there are larger proportions of youth not enrolled in the formal education systems and engaged in the informal economy, a broader notion of NEET is needed.

Enrique Pieck, Academic Researcher, Universidad Iberoamericana Ciudad de México, Mexico. Email: epieckg@yahoo.co.uk

On 14th February 2014, the Sustainable Development Solutions Network (SDSN) released a draft report for public consultation on proposed indicators for Sustainable Development Goals (SDGs). This consultation has now closed.

This blog was one of the commentaries received from NORRAG members. 

 

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NEETS is Not a Neat Concept

By Kenneth King, University of Edinburgh and NORRAG

‘Ensure that all youth transition effectively into the labour market’, was one of the draft Post-2015 targets proposed by the Sustainable Development Solutions Network. This target is surely wild! How can a target aim for all youth to transition effectively into the labour market? What does effectively mean? Acquire a job? Or get ‘Decent Work’? Or does effectively mean, make the transition without taking too long?  But what is too long? It would appear that transition to work might include the informal economy, but that is left unclear.

The first of the potential and illustrative core indicators for this target is: Percentage of young people not in education, training, or employment (NEET). ButI doubt if this is a useful category.  Even in the UK where it was first used in 1999, it is not straightforward. See the March 2014 report by Mirza-Davies (2014: 1): ‘Not all unemployed 16-24 year olds are NEET and not all people who are NEET are unemployed.’

But the indicator mentions that: ‘This indicator, known as NEET, tracks the share of youth who are neither in formal employment nor in full-time education or training’ (SDSN). But then it adds confusingly that ‘It is a measure of the proportion of youth who are either unemployed, work in the informal sector, or have other forms of precarious jobs.’

The extension of the meaning of NEET to cover those in the informal sector or other precarious work is problematic. It suggests that the informal economy as a whole covers many different kinds of precarious work.  This is far from being the case. The informal sector covers a huge variety of work, some of it in rural areas, some in urban areas, and much of it actually within the formal sector of the economy. Some of it is at the subsistence level and some is certainly not. Many people in the formal economy, for instance teachers, also have a second or even third informal job which is off the books.

Current estimates for the UK claim that there are just over one million NEETs in the UK (16-24 year olds).  Doubtless this figure is made easier to calculate by the fact that such young people can claim unemployment benefit.

Why it is also now used in South Africa where 3.5 million young people are claimed to be NEETs is not clear.  It was certainly not coined to cover those who are working in the informal sector in that country.

If the complexity of the NEET category is taken on board as in the African Economic Outlook 2014 (AEO), then the challenge of using NEET as a way of thinking about a target and an indicator is made all too obvious. The AEO (2014) says of NEETs:  The NEET category is made up of three distinct states of employment: unemployment; discouragement; and inactivity, or having left the labour force. Traditional labour market analysis counts the unemployed among the labour force, whereas the discouraged and inactive are considered to be outside it (AEO, 2014).

These definitional problems are added to by ILO using the term NLEET. The NLEET rate stands for “neither in the labour force nor in education, employment or training”. It is similar to NEET but excludes the unemployed since they are still included in the labour force.

Despite these challenges, the SDSN document claims that the NEET indicator is ‘preferable to standard unemployment measures and is better adapted to low-income and lower middle-income countries’. This is hard to accept. We noticed with the publication of the GMR 2012 that there were great difficulties in comparing youth unemployment rates between OECD countries and those in low-income countries. The key difference is that in countries which don’t have any unemployment benefit, there is no option except to work (apart from those who are in richer families and who can afford to wait for formal sector jobs). The great majority of other youth seek to find opportunities in the informal sector, either as casual workers, apprentices-cum-workers, or even in some countries as unpaid workers.

The three terms mentioned above – unemployment, discouragement and inactivity – don’t make any sense in seeking to analyse the work status of the majority of young people in Ghana, for instance, who have elected to become traditional apprentices. They are not ‘employed’ in the tiny formal sector of the economy; they are not being ‘trained’ in any formal sector setting, and they are no longer in the school system. But they are acquiring technical, social and soft skills over a period of 3 to 5 years.

To describe this huge group of young people as NEETs would be conceptually ridiculous. They are certainly learning to work; they are certainly learning on the job; and they are certainly not in formal education. But to use this imported acronym from the UK setting in Ghana, or in India (where NEET actually means National Eligibility cum Entrance Test!) would be to fail to profit from the more than 40 years of analyzing the informal sector since 1971/2.

References

Mirza-Davies, J (2014) NEET: Young People Not in Education, Employment or Training. SN/EP/06705, Economic Policy and Statistics, House of Commons Library, London

AEO – African Economic Outlook (2014) www.africaneconomicoutlook.org

On 14th February 2014, the Sustainable Development Solutions Network (SDSN) released a draft report for public consultation on proposed indicators for Sustainable Development Goals (SDGs). This consultation has now closed.

This blog was one of the commentaries received from NORRAG members. 

 

 

 

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Will Skills Training Get Short-Changed in the Post-2015 Agenda?

By Claudio de Moura Castro, Positivo, Belo Horizonte, Brazil.

Looking at the draft collection of Sustainable Development Solutions Network Post-2015 indicators, each reader will likely find that his own area is insufficiently covered. That is to be expected. Hence, considering my past interest in training, it should be no surprise that I find that the subject has been short changed.

mdg

Where will vocational skills feature post-2015?

The major indicator of training activities appears as something that youth may be doing, instead of being unemployed or in the informal sector. By any stretch of the imagination, this piece of information is too meager, considering that training – in all its manifestations – is a time-consuming, enormously expensive endeavor and a major determinant of productivity.

Training should be treated as a stand-alone and legitimate complement to academic education and given more attention. As it stands, it is almost an after-thought, without a life of its own. It is merely something people do, instead of being idle.

Indicators should help us understand the world. If all we know is that training fills the time of some youth, we miss on the critical question: Do those who have had training in the past have better chances of not being in the NEET category?

The suggested indicator of training – now rechristened as school-to-work programs – is quite slippery. It purports to “measure the proportion of adolescents who are offered programs that enable them to transition from school to employability and work…”.

Suppose that the entire country has 10 vacancies for training – in whatever. Suppose all youth are offered a place and all of them refuse to take it. According to the indicator, 100% of youth have been offered school-to-work programs. Perfection!

Suppose we interpret differently the definition and consider only those programs that effectively lead to jobs. What about all the youth who enrolled in training programs and could not find a job afterwards? Even though they cost money, those programs do not exist?

To disconnect the school-to-work programs from regular education is quite a task. The Dual System is what? And Technical Schools?  And the Comprehensive High Schools of the United States? In the real world, the difference between success and failure in leading youth to meaningful jobs lies in the good fit between the solutions and the problems. Unless we understand the intricacies and merits of each scheme, there is little we can learn. Therefore, creating such a lame indicator is of little help in dealing with the NEET issue.

Another difficulty is the treatment of the informal sector as the ugly nemesis of meaningful employment.  Decades after the first papers on the informal sector were written, under the umbrella of the ILO, it is quite disappointing to see such a naïve and narrow use of the concept.

In more traditional societies, the standard mode of employment is defined today as informal. And it still survives, in the case in many jobs, all over the world. And it is real employment in real jobs. Some are demeaning, some are not.

To illustrate the definitional quandaries, why is so little is said about the informal sector in the United States? One of the reasons is the high flexibility of legal employment in that nation. The same job would be classified as informal in most other countries.

One should not associate the informal sector with poverty or precariousness. What about youth who work in family business, helping in a thousand different ways? In countries where formal employment entails much higher costs for the employers, by mutual consent, to work without a contract is a better deal for both sides – sometimes, in high paying jobs.

A case in point is the university professor who engages in consultancy, with no formal contracts. Is that not to be considered the informal sector?

To sum up, the impression one gathers from examining what the paper includes in training suggests that, indeed, the issue has been short-changed. Compared to the more complete and plentiful indicators of education, what is included in training is too little and too muddled to be of any use for policy making.

Claudio de Moura Castro, Positivo, Belo Horizonte, Brazil. 

Email: claudiodemouracastro@me.com

On 14th February 2014, the Sustainable Development Solutions Network (SDSN) released a draft report for public consultation on proposed indicators for Sustainable Development Goals (SDGs). This consultation has now closed.

This blog was one of the commentaries received from NORRAG members.  

Read other NORRAG Blogs on technical and vocational skills and Post-2015: 

 

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‘Big Data’ Does Not Mean Good Data

By Susan L. Robertson, University of Bristol.

gotanydataAndreas Schleicher – Head of the Indicators and Analysis Division in the OECD, Paris, in his many presentations on the now famous Programme of International Student Assessment – or PISA – likes to conclude with the phrase: “Without data, you are just another person with an opinion”.

Now this is an extremely powerful claim, not only just because it aims to locate data at the centre of what might count as ‘truth’, but because it is also a particular kind of data: numbers and quantification. And what is equally as important here is that a small group of data framers and brokerage merchants – which now includes the OECD, the World Bank, Brookings Institution and Pearson Education, are increasingly located at the global level beyond the spaces in which education politics and policies are debated by the profession and the wider public.

Saber

The spread of SABER

The World Bank’s entry into the business of ‘truth’ gathering is also by way of collecting global data sets on various aspects of education. In 2011 it launched SABER – Systems Approach for Better Education Results, and is now in various stages of data collection and reporting.  Thirteen areas of education have been identified, ranging from teacher policies, to policies on school finance and student assessment. Unlike the OECD, who collects data on student performance and teacher characteristics, the Bank has chosen to collect data on system policies as evidence these practices exist, and which in turn are assumed to create better student outcomes.

Yet the Bank has a highly normative, or dare I say ideological, view as to what counts as a good education system. It is one that favours education as a consumer good, where limits are placed on state monopolies of education, that are open to the for profit sector in what many regard as core business, and which introduces incentives for better teacher and student performance. Using data collected from national systems, the Bank then charts the levels of progress toward this assumed ‘best system of education’ around judgements as to where along this path the country is currently located – as ‘latent’, ‘emerging’, ‘established’, ‘mature’ and so on. Reports are then produced for the participating country, which includes comparisons with other countries who are participating in the round of data collection.

However there are huge limitations in the SABER instruments; it all too clear that the gap between policy artifacts and policy practice is more than chasm-like. Take, for instance, SABER-Teachers, one of the Bank’s 13 SABER instruments – and the Bank’s account (in the form of a report) of Cambodia, one of the countries in their SABER-Teachers Project.  The Bank offers a reasonably favourable view of the level of development trajectory of teacher policies. However, as researchers of Cambodia will point out, this picture that is painted is hugely different from education on the ground.

To be sure, there are policies in place, but this is where it begins and mostly ends for many teachers. A policy is a promise, or in this case a policy fantasy to be realized. But still a fantasy. In reality, many teachers in Cambodia – particularly in rural settings – are often in highly precarious situations with regard to their conditions of work, their wages, class sizes, and far too comfortable a relationship to the market and the excessive commodification of almost all aspects of the education experience.  Yet we are told in the report card on Cambodia that teachers have conditions of work that are very appealing (rated ‘established’) though teachers are likely not to be trained according to particular standards or indeed receive ongoing professional development (noted as ‘latent’). Students are also closely monitored (implying a link back to effective teaching) through examinations, yet again as researchers on Cambodian education show – the examination system is rife with corruption, and it is the shadow education system that matters most (and which students have to pay for) which determines student outcomes.

Now the difference between policy and practice opens up even further in that there is a yawning gap between the formal education system which the Bank is reporting on, and the shadow system that sits out of sight but which is central to understanding student performance and teachers’ work.

Now this is not the place to log on an account of the issues facing the Cambodian education system. But, it is a useful example to show that Schleicher’s confidence in data is not just misplaced, but somewhat ambitious. For surely what is at issue here is that big data can be big bad data, just as some data can be bad data. Big simply magnifies the margins of error.  And for the Bank and its SABER-Teachers project, it is these seem to be huge.

 

Professor Susan L. Robertson is the Director of the Centre for Globalisation, Education and Societies, Graduate School of Education, University of Bristol, UK. Email: S.L.Robertson@bristol.ac.uk

This blog is based on a paper presented by the author at the Comparative and International Education Society (CIES) 2014 Annual Conference, on a NORRAG-organised panel on ‘Big data on education and the hegemony of counting’ (Tuesday 11/3/2014).

Views and opinions expressed in blogs are those of the authors and are not intended to represent the view of all NORRAG members.

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Understanding EFA within a Political Economy Perspective

By Grace Akukwe, American Institutes for Research (AIR).

EFAAs the 2015 MDG deadline approaches, the development community is focused on whether we will achieve the Education For All (EFA) targets or not. One major concern about the EFA targets which have been under less scrutiny is the differing institutional structures that support EFA implementation and how these are affecting progress. Institutional capacity and ownership have serious implications for the attainment of the EFA targets especially as we consider what needs to change beyond 2015. The lagging progress in the EFA goals is as a result of multiple factors amongst them weak government institutions.

As the global community looks beyond 2015, it is important to understand the broader political and economic circumstances of developing countries and how their governments’ institutional arrangements affect the implementation of EFA in terms of translating EFA targets into action. The presentation I made at the recent Comparative and International Education Society (CIES) annual conference highlighted EFA from a political economy perspective and the need for increased investments in institutional infrastructure.

The prohibitive finance gap of $26 billion for achieving Education For All is not the only threat to the vision of universal access to basic education. The issues of ownership and capacity of governments who signed on to EFA are also major challenges.

Attention to the ownership issue was drawn by Kenneth King (King, 1992) when he examined the relationship between aid and capacity-building.  King posited that education reform in aid-recipient countries was initially propped by “enclave projects managed and protected” by special donor-appointed agents whereas there is now a move to promote local sustainable institutions (p. 257). King’s paper made critical observations about the place of external agendas in national education planning in aid approaches – e.g. whether the shift to supporting local institutions had strengthened the local agenda enough to displace the donor’s own global education agenda. King elaborates how the narrowing of the original Jomtien agenda of Schooling for All (SFA) to Education for All (EFA) was donor determined due to resources available and also a powerful lobby for primary education by multi and bi-lateral agencies such as World Bank, UNICEF, USAID and ODA (now DFID); and further demonstrates an external agenda that was not driven by aid-recipient governments.

Following the Paris Declaration and Dakar Framework, King observed in another paper that alignment of EFA targets and indicators to national planning architecture is a critical issue when considered in terms of ownership and the broader national objectives of the aid-recipient governments (King, 2004); King challenged whether Ministries of education identify the MDG and EFAs as their own agenda.

That being said we agree that the rapid enrollment drive during the EFA put intense pressures on government education systems personnel to meet all the conditions for access. Many countries are hindered in their EFA efforts by the lack of enforcement of reform frameworks and isolated policy reviews (UNESCO, 2012). Many government institutions are not adequately equipped to manage multi-faceted data and policy directives or they have not sufficiently evolved to work in an interfaced and integrated manner to tackle the competing demands within their operational environments. This is especially true in countries where the central government Ministries of Education are not strong to begin with and yet have devolved or decentralized management functions to the lower tiers of their governance structures.

To address these two problems, Sinclair (2013) proposes the idea of linking targets to different conditions of countries –i.e. to match goals with developmental status and delineated by three or four levels. Another approach being proposed is universal and tiered goals that are linked to human rights and feasible for recipient government with the appropriate operational support.

Despite the many reports that cite High Level Panels, Task Teams, Civil Society, government and international development agencies in the participation of the EFA agenda, we cannot simply accept high level participation in international fora as a proxy for demonstrated political will and or capacity to implement and achieve the EFA targets. Macro-level support doesn’t automatically translate into micro-level execution.  Beyond 2015, more support is needed to enhance the capacities of ministries of education to develop and implement EFA policies and programs as well as to generate reliable data with which to monitor and evaluate educational performance.

This blog is based on a paper presented by the author at the Comparative and International Education Society (CIES) 2014 Annual Conference, on a NORRAG-organised panel on ‘Big data on education and the hegemony of counting’ (Tuesday 11/3/2014). For the paper and list of citations referred to above, please contact the author on the email below.

Grace Akukwe is a principal project specialist with the International Development, Education, and Research Program at the American Institutes for Research (AIR). Email: gakukwe@air.org

Views and opinions expressed in blogs are those of the authors and are not intended to represent the view of all NORRAG members.

 

 

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International Private Sector Entities and Education Reform: a View from the CIES Conference

By Alexandra Draxler, Independent Consultant.

Low fee private school in Ghana

In some OECD countries, education “reform” has of late become a code word for measures that involve rolling back government responsibility and investment, reining in unions, and using standardized data collection and individual testing as the principal yardstick to measure quality of teaching and learning. So-called public-private partnerships are implemented in a process of devolution to private entities of a wide array of educational activities, from the ownership and running of schools to creation of curriculum and delivery mechanisms, training and certifying teachers, and finally, design of outcomes standards.

In recent years, “reforms” have moved beyond the OECD countries. Proposals and implementation are turning up in development assistance literature, policies and funding flows with approving descriptions. There is also a heated, and highly ideological, debate between the reformers and those who believe that privatizing parts of education weaken the whole system.

In the name of these reforms, “low-cost” private schooling is being scaled up in a number of countries (Pakistan, Ghana, for example) with government support in the form of vouchers or financial concessions, and described as filling gaps in public basic education (see also this recent Oxfam blog). Technological aids to learning, such as individual laptops or tablets for young learners are being purchased, very often with a TCO (total cost of ownership) higher than the government investment per pupil (Rwanda, Uruguay). New internationally-standardized data-gathering mechanisms and tools (Pisa for Development, Learning Metrics Task Force, World Bank – Saber) funded by intergovernmental or bilateral funding are presented as essential for improving quality of education. In all of these instances, private entities, many of which are international corporations, are gaining access to expanding lucrative markets subsidized by government and international aid monies.

For all of these reforms, there are perverse effects that can be immediate or show up over time. Researchers have demonstrated the thin or absent evidence that many privatization initiatives contribute to cost-effectiveness, reduction of inequality, increased quality or scaled-up access. Low-cost private schooling cannot and does not reach the poorest. The schools themselves can only operate with untrained teachers paid at even lower wages than the public sector and a consequently high turnover. It has not been demonstrated that the increase in low-cost private schooling substantially expands enrolments rather than merely shifting them. Widespread technology at basic education level frequently leaches away funding that could be used to improve teacher training, working conditions and retention. Infrastructural difficulties often annihilate or severely limit use as planned of devices. Evaluations have occasionally indicated some improvements in learning over the short term, but rarely scalability and never cost-effectiveness. Widespread standardized testing can disempower teachers and result in a narrowed curriculum and teaching practice. While it may reveal information about quality it also has perverse effects of reducing teaching time, encouraging cheating and creating winners and losers. Expanding internationally comparable data gathering has a considerable opportunity cost, and the use of international firms and consultants can capture rather than build capacity within countries.

Such measures are not a match for the international rhetoric around Post-2015 that aims at leaving no one behind, reducing poverty and inequality, and improving quality. They do not target the poorest or contribute to reducing disparities. They can substantially weaken public education and thereby contribute to diminished quality over time. They touch at the basic notion of education as a human right and a public good. Finally, accountability and transparency should be made an integral part of any public-private partnership.

It seems that more peer reviewed research needs to be carried out on the extent of the corporate involvement and profit on public education. Conflicts of interest and permeability between public funds and private profits need to be examined and described. The burden of proof of benefit for costly reforms involving private sector implementation needs to be on the reformers.

This blog is based on the ideas and questions that were debated in a number of panels concerned with privatization and the effects of corporate influence on education at the recent Comparative and International Education Society (CIES) in Toronto (9 – 15 March 2014). Researchers and practitioners at them often called for more scrutiny of effectiveness, opportunity costs and cost-effectiveness of reforms, as well as governance of new forms of alliances between private and public sector entities and conflict of interests of reformers.  Comments, criticism and additional information by readers will be welcome.

Among the CIES panels was one organized by NORRAG called “Big data on education and the hegemony of counting” with NORRAG members Grace Akukwe, Michel Carton, Alexandra Draxler and Susan Robertson.

Alexandra Draxler is a former UNESCO education specialist, and now an independent consultant and member of NORRAG’s team. Email: a.draxler@gmail.com

>>Read other NORRAG blogs on low-fee private schools

Views and opinions expressed in blogs are those of the authors and are not intended to represent the view of all NORRAG members.

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The SDSN’s Proposed Indicators for the SDGs: Some Commentaries on the Treatment of Livelihoods and Skills

By NORRAG Blog Editor. 

SDSNOn 14th February the Sustainable Development Solutions Network (SDSN) released a draft report for public consultation on proposed indicators for Sustainable Development Goals (SDGs). We asked several NORRAG members to comment on how livelihoods and skills training were treated in these proposed indicators: here is a summary of what they said (see the embedded links for their full comments).

The NEET indicator isn’t neat, and not a nice fit for the informal economy

One of the potential core indicators proposed by the SDSN was to measure the: ‘Percentage of young people not in education, training, or employment’.

Pieck calls for more clarity on what the NEET indicator is actually referring to. When trying to assess the indicator known as NEET, we are obliged to reflect upon the diversity behind each term (‘education’, ‘training’, ‘employment’). For example, in Mexico women are the majority within NEET, they are often devoted to housework and that does not show in statistics.

de Moura Castro, King and Mehrotra all have a problem with the way the informal economy is treated as part of this indicator. The SDSN comment that the NEET indicator is a measure of the proportion of youth who are either unemployed, work in the informal sector, or have other forms of precarious jobs’.

De Moura Castro is disappointed to see such a naïve and narrow use of the informal sector concept; and both he and King comment that one should not associate the informal sector only with poverty or precariousness.

Mehrotra adds that, since the indicator (and the term ‘informal sector’) will mean different things for different countries, there needs to be a simple and consistent definition for ‘informal’ employment built into the rationale.

It is hard to accept that the NEET indicator is ‘preferable to standard unemployment measures and is better adapted to low-income and lower middle-income countries’, as the SDSN notes. King notes that the 2012 UNESCO Education For All Global Monitoring Report highlights the great difficulties in comparing youth unemployment rates between OECD countries and those in low-income countries. The key difference is that in countries which don’t have any unemployment benefit, there is no option except to work.

Technical and vocational skills needs its own indicator

As de Moura Castro notes, currently the major proposed indicator of training activities (the NEET indicator) appears as something that youth may be doing, instead of being unemployed or in the informal sector. Training should be treated as a stand-alone and legitimate complement to academic education and given more attention. As it stands, it is almost an after-thought, without a life of its own. It is merely something people do, instead of being idle.

Vardigans adds that critical references to ‘skills development’ and ‘adults’ have been omitted. He proposes that a clear technical and vocational skills indicator be included, for example, stating the % of youth having at least notional Level 2-3 education and/or TVET skills certification.

Agricultural education and training gets sidelined in the indicators

If the SDSN proposed Goal 6 (‘Improve Agriculture Systems and Raise Rural Prosperity’) does become reality, Menefee notes that there will be implications for education and skills, both at the higher education and training level, and with regard to farmer education skills training. The SDSN Goal 6, has a proposed indicator to measure the ‘share of farmers covered by agricultural extension or equivalent programs’. It would be useful also to measure the level of R&D in agriculture, as well as the tertiary level enrolment in agriculture-related courses.

Indicators for school-to-work programs

One of the ‘additional indicators that countries may consider’ was the ‘proportion of adolescents (15-19 years) with access to school-to-work programs’. However, de Moura Castro questions the usefulness of this indicator:

‘Suppose that the entire country has 10 vacancies for training – in whatever. Suppose all youth are offered a place and all of them refuse to take it. According to the indicator, 100% of youth have been offered school-to-work programs. Perfection!’

Furthermore, he questions how it will be possible to disconnect the school-to-work programs from regular education.

A Decent Work indicator?

Vardigans wonders why ‘decent work’ appears in the proposed target 02a of SDSN Goal 3 (‘Achieve Development within Planetary Boundaries’), which states that ‘Each country reaches at least the next income level and promotes decent work’. He notes that the term decent work seems to be added as an afterthought and does not seem to fit with the goal statement. ‘Decent Work’ is a very specific and well-defined ILO term which captures some extremely important issues relating to employment/ livelihood. He suggests that the key reference to Decent Work should first appear under Goal 03 (Ensure Effective Learning for All Children and Youth for Life and Livelihood), linked to target 03c (Ensure that all youth transition effectively into the labor market). He notes that there should be a Decent Work indicator, perhaps managed by ILO under the Decent Work Agenda, could then disaggregate those in employment and decent employment.

A labour force participation rate indicator?

If we are really serious about Target 3c (‘Ensure that all youth transition effectively into the labour market’), Mehrotra notes, then the fact is that the Labour Force Participation Rate of women, and of young girls especially, must be monitored carefully.

What do you think of the proposed SDSN indicators related to work, education and skills?

The SDSN public consultation period on Indicators for Sustainable Development Goals has just been extended to March 28th, 2014 (from 14th March). Make use of it, send in your comments directly to the SDSN, or if you prefer not to submit an official comment, feel free to add your thoughts below this post.

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