By Trey Menefee, University of Hong Kong.
On the one hand, the skills community should be delighted that the Post-2015 High Level Panel (HLP) of Eminent Persons has suggested a skills target. Specifically, they suggested an “increase the number of young and adult women and men with the skills, including technical and vocational, needed for work by x%.” Elsewhere they suggest increasing “the number of good and decent jobs and livelihoods by x%”. Indeed, it is good to see the HLP proposed goal looking beyond enrolments and dollars per day. But one hopes that the High Level Panel’s gift to the Technical, Vocational Education and Skills (TVET) community comes with a receipt, as it is likely too flawed to be put to good use.
The skills target, as proposed, has a conceptual starting point in labor planning in that it assumes that we can identify what skills the market can put to productive use. Even at the personal level where rewards for the “right” skills have their largest and fastest pay-off, examples abound of the misplaced assumptions about the economic returns of skills. For example, the Filipina woman who walks my dog in Hong Kong is a trained Java programmer; her friend who helps at my neighbor’s house is a Registered Nurse. What makes it even stranger that there is a skills shortage for IT and healthcare workers in Hong Kong. Both of these women are victims of employment trends in the late 1990s that led to people and governments to rationally assume that these skills were paths to prosperity, rather than paths to being domestic helpers with a socio-economic status so low that they are exempt from minimum wage requirements.
The issue isn’t that the world doesn’t need Java programmers or nurses. The issue is that economies as intrinsically emergent, self-organized phenomena shaped by the feedbacks and interactions inside socio-economic systems. The economy is emergent in that it is the interdependencies, diversity, and interconnectivity in the marketplace that produces higher-level phenomena that looks quite unlike the individual components that it is constructed of. This emergent pattern is often very structured, but is intrinsically self-organized (as Adam Smith’s anthropomorphized “invisible hand” alludes to).
Complexity further implies irreducibility. Knowing that skills are important for a vibrant economy is very different from knowing which skills, deployed in which contexts, lead to personal and national gain. Simply adding skills to an economic system and expecting the relevant jobs to emerge is almost as efficient as placing neurons in a petri dish and expecting consciousness to emerge. Skills and neurons are essential pieces, no doubt, but a complex chemistry animates them into something larger than the parts.
Alongside economic change and complexity, a third issue arises in that the types of knowledge that are most valued in the workforce are found in the tacit domain of knowledge. This is the experiential knowledge that often resists the written form and testing. It is resistant to goal setting, unless those goals sounded like “more work experiences” or “lower unemployment.”
But institutional thinking, especially the type found in international institutions, is compelled to convert the tacit to the explicit to make it tangible policy. We see this with governments around the world who are promoting Science, Technology, Engineering, and Math (STEM) subjects as a proxy for fostering logical thinking and innovation. Similarly, English is clearly an increasingly important workplace skill in China, but the best speakers of the language I have met learned the language by watching TV and chatting online. They often did fair poorly in English examinations, just as it is common for those who are barely conversant in English to have done well on such tests.
We know that university dropouts tinkering in garages developed many of the world’s most innovative technologies. My father was a telecommunications engineer who flunked every Math class he came upon, but was nonetheless employed by some of the largest companies in the world to build platforms handling satellite communication and plotting cell phone tower sites. Last year, I taught myself professional book publishing and design software by tinkering around, asking friends, and finding online tutorials and message boards.
Focusing on education and skills in isolation, or in relation to one or two other variables, is likely a recipe for failure. Undoubtedly, “workplace skills” is a crucial component of economic growth – but so are a dozen other different components, whose links to translating skills to human capital need further research. In short, a skills target is an “add more skills” approach to economic development that suffers from the same conceptual myopia as neoliberalism’s “remove regulations” and “lower government spending.”
Despite all of this, I am in the chorus of those who believe that TVET (and even nonformal education) needs a metric to gain political traction. If it doesn’t, it will be sidelined, neglected, and replaced with something like simple enrolment rates. What I would instead propose is to look past goals, per se, and focus on creating “red flags” to signal areas that need improvement. We need metrics that show where there are skills shortages, low economic efficiency in education, or a surplus of under-utilized skills. I have proposed a model with the Educational Capital Index(EdCI), which will be presented at the UKFIET Conference in Oxford (10-12 September 2013).
Ultimately, forgoing a skills target represents the spirit of the best of what the TVET community has to offer. At most we should champion basic literacy and numeracy as a basis for providing modular education opportunities for all. Beyond that, we should not presuppose having many “best practices” or answers. Instead, we have a basket of flexible, adaptable, and responsive solutions for specific and rapidly changing contexts. Together, this would have us prioritizing the expansion of labor market opportunities rather than promoting more of any specific measurable thing.
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