- WORK | meaning in the Cambridge English Dictionary.
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Either the children do household tasks a few hours a day for somebody else while living with their own family or they live with their employer. The latter recieve either money or room and board as payment. Some working children sell goods for money. These goods can be fruits, vegetables, eggs, cooked food, clothes, newspapers and other items that can be sold at a market, on the street, in food stalls or in shops.
Some of these children have an employer, some are self-employed. This kind of work can be arranged with school, but some children work full time and do not recieve an education.
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Another possibility for children to earn money is collecting waste including bottles, tin cans, rubbish etc. I associate his voice with metal for reasons of sound and sense. Sense-wise, the metal comes from knowing Levine grew up working in autoplants. For me, auto-plants equal metal.
Remembering Philip Levine’s Poetics of Labor | Hanif Willis-Abdurraqib
Many metal machines working metal into other metal machines, with a few soft bodies scattered about and busy. And Levine never comes to a clear conclusion about what work is. Readers have to make up their own minds about work. He writes about workers, Midwesterners, blue-collar people, without glorifying them—as Carl Sandburg is wont to do in Chicago Poems —or making them too morose—as Edgar Lee Masters does in his Spoon River Anthology , a book that comes to mind as supreme example of literature concerned with depressing Midwesterners.
Being from the Midwest, and knowing a fair share of depressives, I admit there is some authenticity to the thwarted people he describes. Maybe it was, though. The number of people employed in these occupations is small compared to those in healthcare or construction, but they are high-wage occupations. By , we estimate that this trend could create 20 million to 50 million jobs globally. For the next three trends, we model both a trendline scenario and a step-up scenario that assumes additional investments in some areas, based on explicit choices by governments, business leaders, and individuals to create additional jobs.
Infrastructure and buildings are two areas of historic underspending that may create significant additional labor demand if action is taken to bridge infrastructure gaps and overcome housing shortages. New demand could be created for up to 80 million jobs in the trendline scenario and, in the event of accelerated investment, up to million more in the step-up scenario.
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These jobs include architects, engineers, electricians, carpenters, and other skilled tradespeople, as well as construction workers. Investments in renewable energy , such as wind and solar; energy-efficiency technologies; and adaptation and mitigation of climate change may create new demand for workers in a range of occupations, including manufacturing, construction, and installation. These investments could create up to ten million new jobs in the trendline scenario and up to ten million additional jobs globally in the step-up scenario.
The last trend we consider is the potential to pay for services that substitute for currently unpaid and primarily domestic work. This so-called marketization of previously unpaid work is already prevalent in advanced economies, and rising female workforce participation worldwide could accelerate the trend. We estimate that this could create 50 million to 90 million jobs globally, mainly in occupations such as childcare, early-childhood education, cleaning, cooking, and gardening.
Definition of stress
When we look at the net changes in job growth across all countries, the categories with the highest percentage job growth net of automation include the following:. The changes in net occupational growth or decline imply that a very large number of people may need to shift occupational categories and learn new skills in the years ahead. The shift could be on a scale not seen since the transition of the labor force out of agriculture in the early s in the United States and Europe, and more recently in in China.
Seventy-five million to million may need to switch occupational categories and learn new skills. We estimate that between million and million individuals could be displaced by automation and need to find new jobs by around the world, based on our midpoint and earliest that is, the most rapid automation adoption scenarios. New jobs will be available, based on our scenarios of future labor demand and the net impact of automation, as described in the next section.
However, people will need to find their way into these jobs. Of the total displaced, 75 million to million may need to switch occupational categories and learn new skills, under our midpoint and earliest automation adoption scenarios; under our trendline adoption scenario, however, this number would be very small—less than 10 million Exhibit 1. In absolute terms, China faces the largest number of workers needing to switch occupations—up to million if automation is adopted rapidly, or 12 percent of the workforce.
While that may seem like a large number, it is relatively small compared with the tens of millions of Chinese who have moved out of agriculture in the past 25 years. For advanced economies, the share of the workforce that may need to learn new skills and find work in new occupations is much higher: up to one-third of the workforce in the United States and Germany, and nearly half in Japan. Today there is a growing concern about whether there will be enough jobs for workers, given potential automation.
History would suggest that such fears may be unfounded: over time, labor markets adjust to changes in demand for workers from technological disruptions, although at times with depressed real wages Exhibit 2. We address this question about the future of work through two different sets of analyses: one based on modeling of a limited number of catalysts of new labor demand and automation described earlier, and one using a macroeconomic model of the economy that incorporates the dynamic interactions among variables. If history is any guide, we could also expect that 8 to 9 percent of labor demand will be in new types of occupations that have not existed before.
Both analyses lead us to conclude that, with sufficient economic growth, innovation, and investment, there can be enough new job creation to offset the impact of automation, although in some advanced economies additional investments will be needed as per our step-up scenario to reduce the risk of job shortages. A larger challenge will be ensuring that workers have the skills and support needed to transition to new jobs.
Countries that fail to manage this transition could see rising unemployment and depressed wages.
The magnitude of future job creation from the trends described previously and the impact of automation on the workforce vary significantly by country, depending on four factors. Higher wages make the business case for automation adoption stronger. However, low-wage countries may be affected as well, if companies adopt automation to boost quality, achieve tighter production control, move production closer to end consumers in high-wage countries, or other benefits beyond reducing labor costs.
Economic growth is essential for job creation; economies that are stagnant or growing slowly create few if any net new jobs. Countries with stronger economic and productivity growth and innovation will therefore be expected to experience more new labor demand. Countries with a shrinking workforce, such as Japan, can expect lower future GDP growth, derived only from productivity growth. The automation potential for countries reflects the mix of economic sectors and the mix of jobs within each sector. Japan, for example, has a higher automation potential than the United States because the weight of sectors that are highly automatable, such as manufacturing, is higher.
The four factors just described combine to create different outlooks for the future of work in each country see interactive heat map. Japan is rich, but its economy is projected to grow slowly to It faces the combination of slower job creation coming from economic expansion and a large share of work that can be automated as a result of high wages and the structure of its economy.
However, Japan will also see its workforce shrink by by four million people. The United States and Germany could also face significant workforce displacement from automation by , but their projected future growth—and hence new job creation—is higher. The United States has a growing workforce, and in the step-up scenario, with innovations leading to new types of occupations and work, it is roughly in balance.
At the other extreme is India: a fast-growing developing country with relatively modest potential for automation over the next 15 years, reflecting low wage rates.
What Work Is
Our analysis finds that most occupational categories are projected to grow in India, reflecting its potential for strong economic expansion. India could create enough new jobs to offset automation and employ these new entrants by undertaking the investments in our step-up scenario. China and Mexico have higher wages than India and so are likely to see more automation. To model the impact of automation on overall employment and wages, we use a general equilibrium model that takes into account the economic impacts of automation and dynamic interactions.
Automation has at least three distinct economic impacts. Most attention has been devoted to the potential displacement of labor. But automation also may raise labor productivity: firms adopt automation only when doing so enables them to produce more or higher-quality output with the same or fewer inputs including material, energy, and labor inputs. The third impact is that automation adoption raises investment in the economy, lifting short-term GDP growth.
We model all three effects.
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