Interconnectedness in Education Systems

Candia, C., Pulgar, J., & Pinheiro, F. L. (2022). Interconnectedness in Education Systems. Manuscript submitted for publication. arXiv: Physics: Physics Education. https://doi.org/10.48550/arXiv.2203.05624Traditional methods used in education sciences often disregard the underlying complexity of the educational system and consequently its emergence phenomena. Underlying complex systems, there is a rich web of interconnected components that determine the relational properties of the system. Here, we argue that an interconnected vision of educational systems -- from classrooms to an organizational level -- is key to improving learning, social integration, well-being, and decision making, all fundamental aspects of the educational experience. Hence, understanding the education system as an interconnected network of people, degree programs, and/or institutions requires methods and concepts from computational social sciences. Thus, we can leverage institutional records and experimental designs to elicit the relational maps of key players in education and derive their implications in their functioning at all scales. Here, in different settings, from elementary classrooms to higher education programs, we show how mapping the network relationships between entities can lead to the inference of novel insights about education systems and the development of solutions with societal implications.preprintsubmitte

connecting degree programs from individuals’ choices

Candia, C., Encarnação, S., & Pinheiro, F. L. (2019). The higher education space: connecting degree programs from individuals’ choices. EPJ Data Science, 8(1), [39]. https://doi.org/10.1140/epjds/s13688-019-0218-4Data on the applicants’ revealed preferences when entering higher education is used as a proxy to build the Higher Education Space (HES) of Portugal (2008–2015) and Chile (2006–2017). The HES is a network that connects pairs of degree programs according to their co-occurrence in the applicants’ preferences. We show that both HES network structures reveal the existence of positive assortment in features such as gender balance, application scores, unemployment levels, academic demand/supply ratio, geographical mobility, and first-year drop-out rates. For instance, if a degree program exhibits a high prevalence of female candidates, its nearest degree programs in the HES will also tend to exhibit a higher prevalence when compared to the prevalence in the entire system. These patterns extend up to two or three links of separation, vanishing, or inverting for increasing distances. Moreover, we show that for demand/supply ratio and application scores a similar pattern occurs for time variations. Finally, we provide evidence that information embedded in the HES is not accessible by merely considering the features of degree programs independently. These findings contribute to a better understanding of the higher education systems at revealing and leveraging its non-trivial underlying organizing principles. To the best of our knowledge, this is the first network science approach for improving decision-making and governance in higher education systems.publishersversionpublishe

Stable leaders pave the way for cooperation under time-dependent exploration rates

Pinheiro, F. L., Pacheco, J. M., & Santos, F. C. (2021). Stable leaders pave the way for cooperation under time-dependent exploration rates. Royal Society Open Science, 8(2), [200910]. https://doi.org/10.1098/rsos.200910The exploration of different behaviours is part of the adaptation repertoire of individuals to new environments. Here, we explore how the evolution of cooperative behaviour is affected by the interplay between exploration dynamics and social learning, in particular when individuals engage on prisoner's dilemma along the edges of a social network. We show that when the population undergoes a transition from strong to weak exploration rates a decline in the overall levels of cooperation is observed. However, if the rate of decay is lower in highly connected individuals (Leaders) than for the less connected individuals (Followers) then the population is able to achieve higher levels of cooperation. Finally, we show that minor differences in selection intensities (the degree of determinism in social learning) and individual exploration rates, can translate into major differences in the observed collective dynamics.publishersversionpublishe

Consensus and polarization in competing complex contagion processes

Vasconcelos, V. V., Levin, S. A., & Pinheiro, F. L. (2019). Consensus and polarization in competing complex contagion processes. Journal of The Royal Society Interface, 16(155), [20190196]. https://doi.org/10.1098/rsif.2019.0196The rate of adoption of new information depends on reinforcement from multiple sources in a way that often cannot be described by simple contagion processes. In such cases, contagion is said to be complex. Complex contagion happens in the diffusion of human behaviours, innovations and knowledge. Based on that evidence, we propose a model that considers multiple, potentially asymmetric and competing contagion processes and analyse its respective population-wide dynamics, bringing together ideas from complex contagion, opinion dynamics, evolutionary game theory and language competition by shifting the focus from individuals to the properties of the diffusing processes. We show that our model spans a dynamical space in which the population exhibits patterns of consensus, dominance, and, importantly, different types of polarization, a more diverse dynamical environment that contrasts with single simple contagion processes. We show how these patterns emerge and how different population structures modify them through a natural development of spatial correlations: structured interactions increase the range of the dominance regime by reducing that of dynamic polarization, tight modular structures can generate structural polarization, depending on the interplay between fundamental properties of the processes and the modularity of the interaction network.authorsversionpublishersversionpublishe

From Co-Location Patterns to an Informal Social Network of Gig Economy Workers

Pilatti, G., Candia, C., Montini, A., & Pinheiro, F. L. (2023). From Co-Location Patterns to an Informal Social Network of Gig Economy Workers. Applied Network Science, 8, 1-15. [77]. https://doi.org/10.21203/rs.3.rs-2742628/v1, https://doi.org/10.1007/s41109-023-00603-1---GP, AM, and FLP are very grateful for the suggestions given by the audience and peer review of the Complex Networks and Their Applications XI conference, in which we were able to clarify some points and enrich the research. The authors are thankful to the food delivery platform for sharing the data for this study. The findings, interpretations, and conclusions expressed by the authors in this work do not necessarily reflect the views of the food delivery platform. FLP acknowledges the financial support provided by FCT Portugal under the project UIDB/04152/2020 – Centro de Investigação em Gestão de Informação (MagIC).The labor market has transformed with the advent of the gig economy, characterized by short-term and flexible work arrangements facilitated by online platforms. As this trend becomes increasingly prevalent, it presents unique opportunities and challenges. In this manuscript, we comprehensively characterize the social networks of gig economy workers in each of the 15 cities studied. Our analysis reveals a scaling relationship between networks and the city population. In particular, we note the high level of modularity of the networks, and we argue that it results from the natural specialization of couriers along different areas of the cities. Furthermore, we show that degree and betweenness centrality is positively correlated with income but not with tenure. Our findings shed new light on the social organization of the gig economy workers and provide valuable insights for the management and design of gig economy platforms.publishersversionepub_ahead_of_prin

using network analysis to understand the position of Portugal in a global FDI network

Lima, F., Pinheiro, F. L., Silva, J. F., & Matos, P. (2020). Foreign direct investment: using network analysis to understand the position of Portugal in a global FDI network. In Bridging measurement challenges and analytical needs of external statistics: evolution or revolution?: Proceedings of the IFC Conference on external statistics, Lisbon, Portugal, 17-18 February 2020 (pp. 1-16). (IFC Bulletin; No. 52). Bank of International Settlements. https://www.bis.org/ifc/publ/ifcb52.htmUnderstanding the role of foreign direct investment (FDI) is of utmost importance in a world economy of increasingly interdependent economies. However, the lack of an unified data source of FDI covering a long time frame has posed serious challenges to its analysis. In this article we apply methods of network analysis to build a representation of the global FDI relationships. We show how the network representation of the global FDI can be used to identify patterns, identify preferential paths for investment, establish trends and describe the relations between countries over time. We present the results by using specific visualisation tools that graphically illustrate the interlinkages between the economies, and that can be a valuable instrument for the design and deployment of regulating instruments.publishersversionpublishe

relatedness, complexity and regional inequality in Europe

Pinheiro, F. L., Balland, P-A., Boschma, R., & Hartmann, D. (2022). The dark side of the geography of innovation: relatedness, complexity and regional inequality in Europe. Regional Studies, 1-16. https://doi.org/10.1080/00343404.2022.2106362------------------------Funding: Flavio L. Pinheiro acknowledges the financial support provided by FCT Portugal under the project UIDB/0415s2/2020 – Centro de Investigação em Gestão de Informação (MagIC). Dominik Hartmann would like to express his gratitude for the financial support of CNPq [grant numbers 406943/2021-4 and 315441/2021-6]. Ron Boschma acknowledges the support from the European Union-funded PILLARS (Pathways to IncLusive LAbouR marketS) project [grant agreement number 101004703]. Pierre-Alexandre Balland acknowledges the financial support from the MSCA-RISE TREND (Transition with Resilience for Evolutionary Development) project [grant agreement number 823952].As regions evolve, their economies become more complex, and they tend to diversify into related activities. Although there is a bright side to this diversification process in terms of economic development, there may also be a dark side to it, as it possibly contributes to regional inequalities. The paper uses data on industries and patents to analyze the diversification patterns of 283 regions in 32 European countries over the past 15 years. We find that only the most economically advanced regions have the opportunity to diversify into highly complex activities. These regions tend to focus on related high-complex activities, while lagging regions focus on related low-complex activities, creating a spatial inequality feedback loop. This pattern creates a wicked problem for innovation policy: the strategy needed to improve the innovativeness of the European knowledge system might disproportionately benefit regions that are already developed and foster disparities.preprintpublishersversionepub_ahead_of_prin

Comparing cars with apples? Identifying the appropriate benchmark countries for relative ecological pollution rankings and international learning

Hartmann, D., Ferraz, D., Bezerra, M., Pyka, A., & Pinheiro, F. L. (2021). Comparing cars with apples? Identifying the appropriate benchmark countries for relative ecological pollution rankings and international learning. Frontiers in Environmental Science, 9, 1-17. [779378]. https://doi.org/10.3389/fenvs.2021.779378One of the most difficult tasks that economies face is how to generate economic growth without causing environmental damage. Research in economic complexity has provided new methods to reveal structural constraints and opportunities for green economic diversification and sophistication, as well as the effects of economic complexity on environmental pollution indicators. However, no research so far has compared the ecological efficiency of countries with similar productive structures and levels of economic complexity, and used this information to identify the best learning partners. This matters, because there are substantial differences in the environmental damage caused by the same product in different countries, and green diversification needs to be complemented by substantial efficiency improvements of existing products. In this article, we use data on 774 different types of exports, CO2 emissions, and the ecological footprint of 99 countries to create first a relative ecological pollution ranking (REPR). Then, we use methods from network science to reveal a benchmark network of the best learning partners based on country pairs with a large extent of export similarity, yet significant differences in pollution values. This is important because it helps to reveal adequate benchmark countries for efficiency improvements and sustainable production, considering that countries may specialize in substantially different types of economic activities. Finally, the article (i) illustrates large efficiency improvements within current global output levels, (ii) helps to identify countries that can best learn from each other, and (iii) improves the information 2 base in international negotiations for the sake of a cleaner global production system.preprintpublishersversionpublishe