Trends Shaping Education 2022

2. Living and working

Abstract

Our everyday lives are changing, both at work and at home. Education can continue to help us grow personally and professionally. But what future do we see for ourselves and our communities? This chapter explores these issues through five themes:

• Work to live or live to work?: looks at trends in working hours and time off work.

• New employment for a new age?: examines the rise of non-standard forms of work, such as temporary employment and digital freelancing.

• The quantification of life: explores how we relate to ourselves and others through digital tracking and relationships.

• 21st century families: illustrates changes in family structures and the evolving distribution of reproductive and caring tasks at home.

• Quality of life: examines our quality of life through personal safety and housing conditions.

These trends are linked to education and its future through a series of questions and scenarios. Potential implications of COVID-19, both immediate- and longer-term, are discussed.

Overview and impact of COVID-19

Both our working and private lives are evolving. On average people are working fewer hours than a century ago, and flexible work, such as part-time or telework, is more common. These changes open up new possibilities but also come with risks, for example greater job instability and precariousness. Beyond the world of work, digital technologies are changing the way we relate to ourselves and others, from tracking our daily steps to organising our love life. In many respects, communities are becoming safer, although differences persist in terms of income, age and gender. At home, family structures are continuing to evolve and slow, yet firm steps towards greater gender equality are visible. From early childhood through to lifelong learning, education can play a role in helping individuals thrive in a rapidly changing economy and society, promoting safe, healthy and caring individuals and communities.

 

Living and working & COVID-19

The COVID-19 pandemic is a reminder that, despite our best laid plans, the future likes to surprise us. Trends can accelerate, bend and break. As the shock subsides, open and important questions emerge about the long-term effects of these shifts.

 

Work to live or live to work?

Despite the impression that in today’s busy world we work more than ever, working time has decreased steadily in the last century. In 1870, workers across the OECD worked on average more than 3 000 hours annually, and weekends did not appear until the early 20th century. The reduction in working hours has been driven by various factors including dramatic increases in productivity, income, labour regulations and more affordable leisure. This has translated into a significant rise in time off work and vacations, as reflected in the expansion of tourism over time. However, averages mask large differences both across and within countries. What is the role of education in preparing for life outside work? To what extent will the decline in working hours fuel a rise in demand for learning?

Figure 2.1. In pursuit of a work-life balance

Note: Average annual hours worked is defined as the total number of hours actually worked per year divided by the average number of people in employment per year. OECD average includes all member countries but Israel and Slovenia.

Source: OECD (2021), OECD Labour Force Statistics (database), https://stats.oecd.org/.

Statlink

During the first half of the 20th century, new international conventions limited the workday and the working week to 8 and 48 hours respectively. By 1971, hours worked had declined to 1 960, eventually reaching 1 743 hours annually in 2019. Yet, large differences persist between countries, with employees in Colombia and Turkey working on average over 46 hours per week in 2019, compared to just under 30 hours per week in the Netherlands.

Differences are also significant within countries, for example with gender. Over 15% of male employees work very long hours (i.e. 50 or more per week) across the OECD, compared with about 6% of women. Additionally, evidence from the United States uncovers how work hours in the top tenth of the income distribution have actually risen since 1940, while workers in the bottom 60% witnessed a 20% decline of hours worked per week. Similar patterns have also been found in other OECD high-income countries.

At present, a full-time worker in the OECD spends on average 63% (or 15 hours) of the day on leisure and personal care, including eating and sleeping. Increasing time off work started gaining momentum in the interwar years, and in 1993, the European Union Working Time Directive established a minimum of 20 working days of paid vacations in EU member countries.

Across the OECD, minimum requirements for paid annual leave have been established in all countries except for the United States. Increased free time helps explain the continued expansion of tourism, which reached 1.47 billion international tourist arrivals in 2019. Between 2009 and 2019, real growth in international tourism receipts (54%) exceeded growth in world GDP (44%). This long-term growth has of course been interrupted by the COVID-19 pandemic: 2020 saw an unprecedented 73% drop in international tourist arrivals. While recovery is expected, many experts do not expect a return to 2019 international tourism levels before 2024.

Figure 2.2. Out of office

Source: World Tourism Organization (2021), Tourism Dashboard, https://www.unwto.org/global-and-regional-tourism-performance.

Statlink

And education?

• In addition to work and studies, there is also leisure, family and political life, and more. Can education help individuals, young and old, to develop the competences needed to engage meaningfully across all aspects of life?

• Non-formal, informal and formal learning influence and reinforce each other. Is equitable access to non-formal learning, such as educational leisure, sufficiently considered in your system? What can education systems (local, regional, national) do to improve in this area?

• Despite an average fall in working hours, many parents across the OECD flag inconvenient timing and conflicting work hours as the main impediments for participating in school-related activities. What can schools and education systems more generally do to facilitate their participation?

New employment for a new age?

Labour markets are changing as new business models, job regulations and policies take hold. Non‑standard forms of work, such as temporary and part-time employment, are on the rise. Digital technologies have enabled entirely new forms of non-standard work, notably remote work and jobs mediated by online platforms. While these new modes of labour can boost employment and offer more flexible and self-directed work arrangements, they may also give rise to unpredictable working patterns, intensifying work demands and blurring the lines between employment and private life. Robust lifelong learning systems will be essential to support the adaptability and resilience required to navigate the future of work.

Figure 2.3. The age of precariousness

Note: Temporary employment is part of dependent employment.

Source: OECD (2021), OECD Labour Force Statistics (database), https://stats.oecd.org/.

Statlink

Non-standard work now encompasses over a third of the entire labour force in most OECD countries, impacting young workers the most. In 2020, temporary employment accounted for 24% of dependent employment for those aged 15-24, compared to 11% for the general population. This corresponds to a 7% increase for 15-24 year-olds compared to 1980. Part-time contracts have also been rising over the last two decades, particularly among young workers.

Non-standard work may lead to poorer quality jobs and reduced well-being for workers (especially for those with low and middle skills), due to greater job instability, lower wages, weaker social benefits and protections as well as fewer opportunities for training and promotion. It also heightens the risk of falling into income poverty, increasingly common among young adults nowadays, often dubbed the working poor.

Digital technologies are an important driver of change. The “gig economy”, where workers match themselves with customers via websites and apps, embodies the digital spread of non-standard work. While estimating the numbers of the gig economy is difficult, the global demand for online freelancing has almost doubled in the last five years, growing 11% annually from 2016 to 2021.

Yet despite increased efficiency, productivity and flexible working schedules, the gig economy arguably commodifies work. For some workers, it could signal a return to the informal and casual labour structures of the past, characterised by weak social and employment protection and poor working conditions. There is thus growing demand for better policy to regulate this new economy, to fully harness its potential while mitigating risks. Education and training systems can upskill and reskill people for a dynamic, constantly changing world of work, allowing everyone to learn, lifelong and life-wide. But how well are they meeting this goal? Is there more education should be doing?

Figure 2.4. Digital Taylorism

Note: The OLI tracks the number of projects and tasks across platforms, countries and occupations in real time. It does not estimate absolute numbers of gig workers, as it does not cover work obtained online and carried out locally, like delivery. See StatLink for full information.

Source: Kässi, O., C. Hadley and V. Lehdonvirta (2019), Online Labour Index: Measuring the Online Gig Economy for Policy and Research, figshare Dataset. https://doi.org/10.6084/m9.figshare.3761562.v1842.

Statlink

And education?

• With rising forms of non-standard employment, how do we structure our days if schedules are not given to us by our work organisations? How can education support children and adults in learning how to manage their time?

• Given the changing world of work, education systems are increasingly expected to prepare people for multiple jobs over their life course. Are they achieving this goal? If not, what should they start and/or stop doing?

• What are the consequences for on-the-job learning and training if increasing numbers of workers have no permanent fixed employer to sponsor such education? What does this shift mean for education systems, formal or non-formal, and for education professionals? What is the potential of new training opportunities emerging from the gig economy, such as peer networks and crowd-curated resources, to fill this gap?

The quantification of life

Individuals are increasingly focusing their free time on productivity, efficiency and self-improvement. Thanks to wearable tech and the ever-expanding Internet of Things, we can now distil parts of our life story down to data harvested on our smart devices. And the trend does not stop with our health: now even love and relationships are increasingly the product of algorithms. Once the realm of the individual (or family), our private lives are increasingly quantified and commodified by the same companies that extract value from the data we produce. Education helps develop the critical thinking necessary to make informed choices, as well as support and empower students of all ages to choose their own authentic path in an increasingly quantified society.

Figure 2.5. An app a day keeps the doctor away?

Note: Active Fitbit users are those who use their device (at least) once a week. Apple net sales include sales of AirPods, Apple TV, Apple Watch, Beats products, HomePod, iPod touch and other Apple-branded and third-party accessories.

Source: OECD calculations from Fitbit full year results (2014-2020), https://investor.fitbit.com/, and Apple annual reports on Form 10-K (2015‑2020), https://investor.apple.com/.

Statlink

Smart and wearable technologies are ubiquitous and increasingly part of our lives. Thousands of mHealth (mobile health) apps are available for download on smartphones, wearable devices and other tech gadgets. The list of things these tools can measure continues to grow, including breathing and heart rate, oxygen saturation, hours slept, calorie intake and physical activity. The number of Fitbit active users grew from 6.7 million in 2014 to 31 million in 2020; an explosion that epitomises the momentum of the self‑monitoring phenomenon, also known as self-quantification.

Interestingly, monitoring aspects of one’s life in the quest for self-knowledge is not a new practice, as illustrated by age-old strategies like journaling. Yet, digital technologies have enabled us to reach unchartered waters: a growing number of people regularly engage in building self-knowledge through numbers with the goal of improving physical, mental and emotional performance.

Amidst the progressive quantification of life, even love and relationships are increasingly transformed into products of algorithms. The number of paid subscriptions to the dating platform Tinder skyrocketed from 304 000 to almost 7 million in five years. It is estimated that Tinder currently has over 66 million monthly users - a true mass phenomenon. Through such dating apps, the dating scene becomes a market, a place to shop for potential partners like items in a catalogue. Given the endless alternatives available, romantic relationships may increasingly resemble commodities to be consumed quickly and en masse, while encounters become economic transactions.

Is this just the “new normal”? Digital, data and health literacy is key to identifying and raising awareness of the increasing 'datafication’ of everyday life and associated risks.

Figure 2.6. Love at first swipe

Source: OECD calculations from Match Group Investor Presentation (2015-2019) & 2020-2021 Quarters Result https://ir.mtch.com/overview/.

Statlink

And education?

• Many aspects of education are being increasingly measured and quantified. Are we reducing education only to quantifiable things? If we can’t measure it, will it still count?

• Do education institutions have the capacity to understand and use the data that are generated by digital tools, platforms and services? If not, what could help? Strengthening teachers’ data literacy? Introducing and integrating new professional roles in schools and universities?

• Increasing quantification of life is linked to a growing expectation of perfection – in education, appearance, relationships, and life more generally. What is the best way to empower learners to resist this pressure? How can education help not only address but also prevent potential negative consequences (e.g. increasing stress and anxiety; and reduction in risk-taking due to fear of making mistakes)?

21st century families

Family structures continue to evolve across OECD countries. The institution of marriage is evolving, for example, with declining marriage and fertility rates, increasing divorce, and the average age of marriage delayed until later in life. But romance is not dead: long-term partnerships, like cohabitation and civil unions have become more common. These changes reflect shift in social values, but other factors reinforce these trends such as increasing labour force participation of women, greater job instability and economic insecurity. Despite these shifts, certain family features are slow to change. Women still bear the brunt of reproductive and child-rearing work, balancing between work at the office and at home. Education policy can help build communities where all members are cared for and gender stereotypes fought.

Figure 2.7. Till death do us part

Note: Data for New Zealand include civil unions. Where data were unavailable, figures from the closest year are used. See StatLink for details.

Source: OECD (2021), OECD Family Database, https://www.oecd.org/els/family/database.htm; for 2019, data from the respective national statistics offices have been used to produce this figure.

Statlink

Marriage rates have been declining across the OECD over the past 50 years, from just over 8 marriages per 1 000 people in 1970 to less than 5/1 000 in 2019 on average. People are also marrying later: the average age of marriage rose by five years for both sexes between 1990 and 2017, to 30 years for women and 33 for men. In parallel, divorce rates have been rising in all countries except for Denmark, Estonia, Hungary, Latvia and the United States. Cohabitation has become correspondingly more common, with almost 10% of individuals in a cohabiting couple on average across the OECD. This is particularly popular in the Nordic countries: in Sweden, for example, 20% of couples live together without being formally married. An institution in transition, marriage itself has also changed and modernised, with same-sex marriage being legalised in 21 OECD countries as of 2020.

While marriage is evolving, other family matters are slow to change. Women still spend twice as much time in unpaid and care work as men across the OECD, with tasks such as cooking, cleaning, caring and shopping taking on average four-and-a-half hours of their time every day. To address this, many countries have expanded paid paternity, parental and home care leave for fathers over the last three decades – increasingly preventing leave entitlements from being transferred to the mother. Despite these efforts, in 2020 father-specific entitlements were still far shorter than those for mothers (9 versus almost 51 weeks on average across the OECD). Japan and Korea have the most generous allowance, where fathers are entitled to up to one year of paid leave. But uptake of parental and home care leave – aimed at childcare – remains low OECD-wide, with men making up only about one in every five users. This ratio is even lower in Korea, despite the generous allowance: Korean fathers make up less than one in every ten users. Fathers’ involvement in childcare can positively impact child development, and improve educational outcomes and career expectations, especially for girls. Positive attitudes towards care, irrespective of gender, can be modelled and fostered in education from an early age.

Figure 2.8. Man of the house?

Note: Information refers to entitlements that can be used only by fathers and cannot be transferred to mothers, and any weeks of sharable paid leave that must be taken by the father in order for the family to qualify for 'bonus' weeks of parental leave. OECD average includes 38 countries.

Source: OECD (2021), OECD Family Database, https://www.oecd.org/els/family/database.htm.

Statlink

And education?

• Where do we draw the line between family and school responsibilities (care, teaching and learning, etc.)? Are the different roles reflected in education policies, such as those governing school schedules and resourcing?

• How can education systems, including adult education, help challenge gendered care roles and aspirations? By promoting more balanced role models? Changes in curricula? In the composition of the teaching workforce?

• Access to high-quality early childhood education and care is associated with higher school achievement and life outcomes. It is also a key support structure for working parents. How can governments ensure that it is accessible to all, especially the most disadvantaged?

Quality of life

People’s quality of life has improved in recent decades on several measures. Across the OECD, homicide rates and road fatalities have decreased, and people feel safer when walking alone at night in their neighbourhoods. Satisfactory housing conditions have also improved, with overcrowding and the share of households lacking basic sanitation decreasing on average. Nevertheless, major inequalities persist and even grow. Personal safety varies substantially across countries and different gender, age and education groups. And despite improvements in housing conditions, housing affordability is still a serious problem. How can education serve all learners, including those facing circumstances that are more difficult?

Figure 2.9. Strangers in the night

Note: Gender ratios are calculated by dividing the share of women who feel safe walking alone at night, by the share of men who feel safe. Source: Gallup (2021), Gallup World Poll (database), www.gallup.com/services/170945/worldpoll.aspx.

Statlink

Safety, or its absence, has far-reaching consequences for well-being. On average across the OECD, homicide rates have fallen by 33% since 2010, and road fatalities have dropped by over 20%. In 2020, around 74% of people reported feeling safe when walking alone at night in their neighbourhood, up from 66% in 2006. Yet, significant differences exist across countries and between population groups. For example, those aged 30-49 and university educated are more likely to feel safe.

From a gender perspective, men feel safer than women when walking alone at night in all OECD countries – on average, eight in ten men compared to six in ten women. The gap is particularly high in Australia and New Zealand: around 80% of men feel safe compared to around 50% of women. Yet, the gender gap in feelings of safety has narrowed slightly between 2006-13 and 2014-20 in several OECD countries – notably in France, Italy and United Kingdom.

Households are dedicating an increasingly large share of their disposable income to housing, due in part to rising housing prices, especially for renters. Higher prices hamper consumption and saving abilities, making people more vulnerable to economic shocks. Between 1980-2020 rents increased on average more than 350% across OECD countries. Since 2005, rents have more than doubled in Estonia, Iceland, Lithuania and Turkey. These trends disproportionately affect the poor. Nearly three in ten households in the bottom 20% of the income distribution spend on average over 40% of their disposable income on rent or mortgage payments. They are also more likely to live in poor quality and overcrowded dwellings.

This financial burden can ultimately lead to eviction or even homelessness: prior to the COVID‑19 pandemic, over 3 million formal eviction procedures had been initiated in the OECD and homeless rates had been rising in one-third of OECD countries, affecting over 2 million people. Education, together with other social services, must work to support healthy development for all students, removing learning barriers within schools and classrooms – and, with the rise of digital learning, beyond them as well.

Figure 2.10. How (un)affordable is your home?

Note: Where data were unavailable, figures from the closest year are used. See StatLink for further detail.

Source: OECD (2021), “Housing prices” (indicator), https://doi.org/10.1787/63008438-en.

Statlink

And education?

• Emotional and physical safety are key for learning and healthy development. How can schools and communities work together to ensure student safety? How can education systems better prepare and support teachers in doing this?

• Residential segregation is a key driver of school segregation, hindering education’s quality and equity. Which enrolment and resourcing policies mitigate the effects of and reduce segregation in education systems?

• Learners come to education from different and evolving family and housing circumstances. What are the implications of remote and hybrid learning for different student groups? How can time, spaces and people be reorganised to support the diverse needs of students and families?

What future for living, working and education?

Trends allow us to consider what current patterns might mean for the future. But what about new patterns, shocks and surprises that could emerge over the next 15 to 20 years?

Building on the OECD Scenarios for the Future of Schooling, this section encourages readers to consider how growth could connect with education to evolve in multiple ways. Two vignettes illustrate possible stories: the Reader is invited to adapt and create new ones as desired. The next page sets out some key questions for education, and a set of potential shocks and surprises that could impact education and learning in unexpected ways. The descriptions of each scenario can be found in the Introduction of this volume.

 

In 2040, things look quite different

 

Shocks and surprises

Despite the best laid plans, the future likes to surprise us. What would these shocks mean for education and learning if they came to pass? Can you see signs of other potential disruptions emerging?

 

Find out more

Relevant sources

• Gallup (2021), Gallup World Poll (database), www.gallup.com/services/170945/worldpoll.aspx.

• Huberman, M. and C. Minns (2007), “The times they are not changin’: Days and hours of work in Old and New Worlds, 1870–2000”, Explorations in Economic History, Vol. 44/4, pp. 538-567, https://doi.org/10.1016/j.eeh.2007.03.002.

• Kässi, O., C. Hadley and V. Lehdonvirta (2019), Online Labour Index: Measuring the Online Gig Economy for Policy and Research, figshare Dataset, https://doi.org/10.6084/m9.figshare.3761562.v1842 (accessed 1 June 2021).

• Markovits, D. (2019), The Meritocracy Trap: How America's Foundational Myth Feeds Inequality, Dismantles the Middle Class, and Devours the Elite, Penguin Random House, New York.

• OECD (2021), “Building for a better tomorrow: Policies to make housing more affordable”, Employment, Labour and Social Affairs Policy Briefs, OECD, Paris, http://oe.cd/affordable-housing-2021.

• OECD (2021), OECD Employment Outlook 2021: Navigating the COVID-19 Crisis and Recovery, OECD Publishing, Paris, https://doi.org/10.1787/5a700c4b-en.

• OECD (2021), “Housing prices” (indicator), OECD Affordable Housing Database, https://doi.org/10.1787/63008438-en (accessed 20 May 2021).

• OECD (2021), OECD Family Database (database), https://www.oecd.org/els/family/database.htm (accessed 28 October 2021).

• OECD (2021), Labour Force Statistics (database), https://stats.oecd.org/ (accessed 26 October 2021).

• OECD (2020), How's Life? 2020: Measuring Well-being, OECD Publishing, Paris, https://doi.org/10.1787/9870c393-en.

• OECD (2020), OECD Employment Outlook 2020: Worker Security and the COVID-19 Crisis, OECD Publishing, Paris, https://doi.org/10.1787/1686c758-en.

• OECD (2019), Measuring the Digital Transformation: A Roadmap for the Future, OECD Publishing, Paris, https://doi.org/10.1787/9789264311992-en.

• OECD (2019), OECD Employment Outlook 2019: The Future of Work, OECD Publishing, Paris, https://doi.org/10.1787/9ee00155-en.

• OECD (2019), Society at a Glance 2019: OECD Social Indicators, OECD Publishing, Paris, https://doi.org/10.1787/soc_glance-2019-en.

• OECD (2016), “Parental leave: Where are the fathers?”, OECD Policy Brief, OECD, Paris, https://www.oecd.org/policy-briefs/parental-leave-where-are-the-fathers.pdf.

• Palmer, L. (2020), “Dating in the age of Tinder: Swiping for love?”, in Carter J. and L. Arocha (eds), Romantic Relationships in a Time of ‘Cold Intimacies’, Palgrave Macmillan Studies in Family and Intimate Life, Palgrave Macmillan, Cham, pp. 129-149, https://doi.org/10.1007/978-3-030-29256-0_7.

• UNWTO (2021), International Tourism Highlights, 2020 Edition, World Tourism Organization, Madrid, https://doi.org/10.18111/9789284422456.

Glossary

• Civil Unions: Legal recognition of the committed partnership of two individuals. Typically, the civil registration of their commitment provides the couple with legal benefits that approach or are equivalent to those of marriage.

• Cohabitation: People who are living with a partner in a consensual union but who are not legally married to the partner and are not in a registered partnership with the partner.

• Crude marriage (and divorce) rates: Defined as the number of marriages (and divorces) during the year per 1 000 people.

• Dependent employment: Employment compensated by a wage or salary.

• Eviction: The process of the involuntary removal of people from rental dwellings, involving a judicial process in courts or other litigating bodies, such as landlord and tenant boards or rental housing tribunals. Evictions can also affect households in owner-occupied housing, especially households that fall behind on their mortgage payments.

• Gig economy: A way of working based on temporary jobs or doing separate pieces of work, each paid separately, rather than working for an employer. Gig (or platform) workers are individuals who use an app (such as Uber) or a website (such as Amazon Turk) to match themselves with customers, in order to provide a service in return for money. They offer a diverse range of services including transport, coding and writing product descriptions.

• Income poverty: When the income level of an individual or household is so low that basic human needs cannot be met.

• Internet of Things: Refers to all devices and objects whose state can be altered via the internet, with or without the active involvement of individuals. It includes all kinds of objects and sensors that permeate the public space, the workplace and homes, and that gather data and exchange these with one another and with humans.

• Leisure: A wide range of indoor and outdoor activities, such as sports, entertainment and socialising with friends and family. Leisure excludes paid and unpaid work and personal care activities, such as eating and sleeping.

• mHealth (mobile health): A variety of applications used on mobile and wearable devices to monitor health, treat disease and improve human health outcomes.

• Non-standard dependent employment: Refers to wage and salary workers working either on a part‑time or on an unstable basis (i.e. involving frequent transitions between dependent employment and unemployment over a number of years).

• Non-standard work: All temporary, part-time and self-employment arrangements, i.e. everything deviating from the “standard” of full-time, open-ended employment with a single employer. As working from home does not take place at the employer’s premises, but rather at the worker’s home or at another location of their choosing, it too is considered a diverse employment arrangement.

• Online freelancing: Refers to individuals that find a job online and work via internet. It does not include work obtained online and carried out locally like delivery and ridesharing.

• Overcrowded dwellings: Living conditions where less than one room is available in each household: for each couple in the household; for each single person aged 18 or older; for each pair of people of the same gender between 12 and 17; for each single person between 12 and 17 not included in the previous category; and for each pair of children under age 12.

• Paid annual leave: A paid number of days each year that an employee is allowed to be away from work. Annual leave can generally be taken at the choice of the employee (albeit with the exact timing of the leave often made in agreement with the employer).

• Paid home care leave: Employment-protected leave of absence that sometimes follow parental leave and that typically allow at least one parent to remain at home to provide care until the child is two or three years of age. They tend to be paid only at a low flat-rate. They are also called childcare or child raising leave.

• Paid parental leave: Employment-protected leave of absence for employed parents that often supplements maternity and paternity leave and frequently, but not in all countries, follows the period of maternity/paternity leave. Entitlements to parental leave itself are often individual (i.e. each parent has their own entitlement).

• Paid paternity leave: Employment-protected leave of absence for employed fathers at or in the first few months after childbirth, or in some countries, adoption.

• Personal care: Includes time spent in activities required by the individual in relation to biological needs (sleeping, eating, resting etc.); performing own personal or household health care and maintenance or receiving this type of care; travel related to personal care activities in relation to spiritual/religious care; doing nothing, resting, relaxing; meditating, thinking, planning.

• Remote work: Carrying out work while remaining physically at home - or at another location - and not being present at the company's or at a client's premises during normal working hours, irrespective of whether it is occasional or regular.

• Tinder: One of the most famous online dating applications that allows users to anonymously swipe to like or dislike other users' posted profiles, which generally comprise their photo, a short bio and a list of their personal interests. Once two users have "matched", they can exchange messages.

• Unpaid and care work: Includes time spent in routine housework; shopping; care for household members; child care; adult care; care for non-household members; volunteering; travel related to household activities; and other unpaid activities. Care work refers to the provision of personal care but also the supervision and the education of a child, including reading and talking with children, as well as transporting children.

• Wearable Tech: A category of electronic devices that can be worn as accessories, embedded in clothing, implanted in the user's body, or even tattooed on the skin. The devices are hands-free gadgets with practical uses, powered by microprocessors and enhanced with the ability to send and receive data via the internet.