Universal resilience patterns in labor markets

Moro, Esteban; Frank, Morgan R.; Pentland, Alex; Rutherford, Alex; Cebrián, Manuel; Rahwan, Iyad

doi:10.1038/s41467-021-22086-3

Cited by 31 publications

(39 citation statements)

References 34 publications

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“…As a result, our analyses and results are specific to the Australian labor market. However, this is a feature of our work rather than a limitation, as it allows to contextualize the analysis to geographical and temporal labor markets—it has been shown that labor markets can be highly contextual [ 39 ]. One can easily leverage our methods to produce results for other countries by applying equivalent country-specific labor market data from job ads, employment statistics, and occupational transitions.…”

Section: Resultsmentioning

confidence: 99%

Skill-driven recommendations for job transition pathways

2021

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Job security can never be taken for granted, especially in times of rapid, widespread and unexpected social and economic change. These changes can force workers to transition to new jobs. This may be because new technologies emerge or production is moved abroad. Perhaps it is a global crisis, such as COVID-19, which shutters industries and displaces labor en masse. Regardless of the impetus, people are faced with the challenge of moving between jobs to find new work. Successful transitions typically occur when workers leverage their existing skills in the new occupation. Here, we propose a novel method to measure the similarity between occupations using their underlying skills. We then build a recommender system for identifying optimal transition pathways between occupations using job advertisements (ads) data and a longitudinal household survey. Our results show that not only can we accurately predict occupational transitions (Accuracy = 76%), but we account for the asymmetric difficulties of moving between jobs (it is easier to move in one direction than the other). We also build an early warning indicator for new technology adoption (showcasing Artificial Intelligence), a major driver of rising job transitions. By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19). They can be leveraged by policy-makers, educators, and job seekers who are forced to confront the often distressing challenges of finding new jobs.

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Section: Resultsmentioning

confidence: 99%

Skill-driven recommendations for job transition pathways

2021

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“…As a proxy for a city's resilience, we calculated the ratio of inscriptions produced before and after 235 CE: a higher proportion of inscriptions produced after 235 CE is here interpreted as indicating higher economic resilience of a city in face of the third century crisis. Drawing on recent empirical studies of modern urban systems [10][11][12], we hypothesized that the cities with a higher sectoral diversity will reveal higher resilience than highly specialized cities.…”

Section: ) In the Case Ofmentioning

confidence: 99%

“…Diversity, on the other hand, is determined by the extent and equality with which employment is distributed across multiple industry sectors. While high sectoral specialization results in higher efficiency and greater economic productivity of a city as a whole, it also reduces urban resilience to change or shock [8,[10][11][12]. A modern example is Detroit whose focus on the car industry contributed to its economic eclipse in the end of the twentieth century [13].…”

Section: Introductionmentioning

confidence: 99%

Division of labor, specialization and diversity in the ancient Roman cities: A quantitative approach to Latin epigraphy

Heřmánková¹,

Kaše²

2022

Preprint

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Recent empirical studies on the division of labor in modern cities indicate a complex web of relationships between sectoral specialization of cities and their productivity on one hand and sectoral diversification and resilience on the other. Emerging scholarly consensus suggests that ancient urbanism has more in common with modern urban development than previously thought. We explore whether modern trends in urban division of labor apply to the cities of the Western Roman Empire from the first century BCE to the fourth century CE. We introduce analyses based on occupational data extracted from a large body of Latin epigraphic evidence by computer-assisted text-mining, subsequently mapped onto a dataset of ancient Roman cities. We detect a higher frequency of occupation terms on inscriptions from cities than from rural areas and identify an accumulation of tertiary sector occupations in large cities. The temporal dimension of epigraphic data allows us to study aspects of the division of labor diachronically and to detect trends in the data in a four centuries-long period of Roman imperial history. Our analyses reveal an overall decrease in the frequency of occupational terms between the first half and second half of the third century CE; the maximum frequency of occupational terms shifts over time from large cities to medium and small towns, and finally, rural areas. Our results regarding the specialization and diversity of cities and their respective impact on productivity and resilience remain inconclusive, possibly as a result of the socio-economic bias of Latin inscriptions and insufficient representativeness of the data. Yet, we believe that our formalized approach to the research problem opens up new avenues for research, both in respect to the economic history of the Roman Empire and to the current trends in the science of cities.

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“…Mechanistic approaches of this type have been successfully developed in recent years to address several societal challenges. Some relevant examples are: the identification of global systemic risks through financial networks [14], the universal description of urban growth and development across nations [15,16], the prediction of collective responses during emergencies [17], the dynamics of labor markets and their resilience to automation [18], and the understanding of gender inequalities in different contexts, from academic career trajectories [19,20] to human mobility aspects [21]. Other studies have investigated the dynamical evolution of ecosystems [22,23] and the impact of globalization on their resilience [24], as well as the quantification of the environmental impact of car sharing [25] or traffic mitigation [26].…”

Section: Introductionmentioning

confidence: 99%

Complex systems for the most vulnerable

et al. 2022

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In a rapidly changing world, facing an increasing number of socioeconomic, health and environmental crises, complexity science can help us to assess and quantify vulnerabilities, and to monitor and achieve the UN Sustainable Development Goals. In this Perspective, we provide three exemplary use cases where complexity science has shown its potential: poverty and socioeconomic inequalities, collective action for representative democracy, and computational epidemic modeling. We then review the challenges and limitations related to data, methods, capacity building, and, as a result, research operationalization. We finally conclude with some suggestions for future directions, urging the complex systems community to engage in applied and methodological research addressing the needs of the most vulnerable.

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Universal resilience patterns in labor markets

Cited by 31 publications

References 34 publications

Skill-driven recommendations for job transition pathways

Skill-driven recommendations for job transition pathways

Division of labor, specialization and diversity in the ancient Roman cities: A quantitative approach to Latin epigraphy

Complex systems for the most vulnerable

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