GIGA Focus Afrika

Decolonising Research via Digital Networks? Exploring Big-Team Science

Nummer 5 | 2024 | ISSN: 1862-3603


  • Who studies whom? Red lines indicate source countries; blue ones depict destination countries. The project analysed 49,000 publications focused on the SDGs, identifying where each originated from.

    Sixty years after the GIGA’s founding as the Deutsches Übersee-Institut (German Overseas Institute), historical legacies still drive the “one-way street” of research collaboration between Germany and Africa. Creative digital approaches, such as “big-team science,” are needed to accelerate knowledge creation in partnership with the continent.

    • Research collaboration with Africa faces persistent asymmetry due to historical factors, structural barriers, socio-economic disparaties, and short-term academic publishing pressures.

    • More equitable collaborations with African institutions are beneficial for both practical and scientific reasons. Practically, equitable involvement of African researchers in research projects can assist with capacity development and academic diversity. Scientifically, they can improve external validity, data quality, and the theoretical novelty of research.

    • Digital cooperation using “big team-science” provides an opportunity to overcome geographical barriers to such international collaboration. The co-creation of digitally distributed large-N studies with African partners can simultaneously help address endemic issues in the Social Sciences: namely, reproducibility, statistical power, and external validity.

    • The creation of such projects is complex and requires training and coordination among researchers and institutes plus overcoming numerous hurdles.

    Policy Implications

    The potential benefits of “big-team science” projects with the African continent are worthy of attention. Policymakers and funding bodies should facilitate the development of such projects through tailor-made funding lines while minimising legal and bureaucratic frictions around these complex endeavours.


    An Unlikely Counterfactual

    In January 2024, I spent 10 days with a small team visiting Kenyan villages in Bomet and Siaya counties to speak with basic-income recipients about their spending and saving practices. The basic-income payments were from GiveDirectly, a private charity operating out of New York City, that has sent unconditional cash transfers via mobile phone to over 1.6 million people all over the world. I was motivated to travel to Kenya because their project there is the largest basic-income experiment in history, with over 50,000 recipients – paid for 12 years for the longest-running ones. My interest in both digitalisation and finance made the destination compelling.

    My return to Germany led me to reflect on why the counterfactual situation with Kenyan researchers visiting Germany is so unlikely. Why is a research project with Kenyan researchers interviewing German welfare recipients somehow ludicrous? Following reflections and discussions during the GIGA Doctoral Conference on Researching with the Global South, I argue it relates to four factors: (1) history; (2) structural barriers; (3) short-term academic culture; and, (4) socio-economic disparities. After explaining these, I will discuss (5) why the current situation is problematic then (6) ways to decolonise via digital networks using “big-team science” along with (7) the benefits and challenges accompanying such an approach.

    History

    Why is a German institute conducting research in Kenya while a Kenyan institute is not active in Germany? History is one part of the answer. The GIGA was founded in 1964 as the Deutsche Übersee-Institut (German Overseas Institute, henceforth DÜI) to combine the existing Institut für Asienkunde (Institute of Asian Affairs), Deutsches Orient-Institut (German Orient Institute), Institut für Iberoamerika-Kunde (Institute of Ibero-American Affairs), and the Institut für Afrika-Kunde (Institute of African Affairs). While its founding occurred after the end of the European imperial era, it is nonetheless surrounded by colonial history. The GIGA building sits on the picturesque Binnenalster across from Hapag-Lloyd (the fifth-largest shipping company in the world), next to the prestigious Übersee-Club (a 100-year-old private club for merchants and industrialists), and across the street from Berenberg Investment Bank (founded in the sixteenth century, its wealth was made from colonial trade). Inside the premises, the GIGA shares a building with the ZBW Leibniz-Informationszentrum Wirtschaft (Leibniz Information Centre for Economics), a body with historical ties to the Central Office of the Hamburg Colonial Institute that was tasked with archiving, processing, and making available all information on German and non-German colonies to trainees and Hamburg merchants.

    The Hamburg Colonial Institute itself was founded in 1908 after campaigning by Hamburg Senator Werner von Melle, who convinced Berlin officials that Hamburg, the centre of German trade, would be the perfect location to train personnel for the then German colonies in Africa and Asia. After the loss of the colonies in World War I, the Hamburg Colonial Institute and Hamburg Scientific Foundation merged to become the University of Hamburg in 1919. Since its founding, the GIGA has maintained a close relationship with the University, with various senior researchers consistently holding professorships there from its early days through the present. On 16 December 1964, at the opening of the DÜI, the First Mayor of Hamburg Paul Nevermann announced:

    Our world has become so small due to technological progress that every current event in a country, no matter how distant, has an impact on our political and economic life, which is why state and business are equally interested in being informed about the background to these events. The DÜI’s work should therefore aim to provide as comprehensive an overview as possible of the conditions prevailing in non-European countries; it should help to improve understanding between Germany and these countries and to increase knowledge of the problems in Africa, Asia, and Latin America. (Translated from German; italics added for emphasis)

    Such a focus on researching problems in the Global South shows the paternalistic, colonial nature of the DÜI’s initial remit regarding the various regions. Research on its organisational history supports this interpretation. Its first president, Andreas Predöhl, has been shown to have had strong ties to colonial racist ideology (Hein and Kappel 2014). Predöhl argued that smaller countries should cater to the economic needs of “core nations,” such as Germany, and accept their political subjugation.

    Six decades on, while the GIGA has shed such views and arguably expanded its focus to knowledge about these regions in general, much of its research still focuses on problems there such as conflict, poor economic development, weak governance, or democratic backsliding. Indeed, this might somewhat explain the one-way traffic to the African continent for research projects rather than two-way partnerships with, for example, well-established Kenyan universities (such as the University of Nairobi, which dates to the 1950s). With Africa seen as the one with problems, it would be unnecessary for a Kenyan researcher to come to critique German governance, for instance. Even if the motivation existed for these exchange formats, several structural barriers also hinder such collaboration.

    Structural Barriers

    Not completely unrelated to said colonial history are the impediments that exist for Kenyans prospectively coming to Germany. Citizens of former coloniser countries generally enjoy greater mobility than those from the regions they once ruled over. As Figure 1 below shows, 2.84 per cent of German studies on the United Nations’ sustainable development goals (SDGs) are about Kenya while not a single study at the latter’s universities is researching the SDGs with a focus on Germany. This may not be surprising until you notice that 11.3 per cent of Kenyan studies on the SDGs are focused on the United States, followed by on the United Kingdom (3.48 per cent), Italy (2.61 per cent), and Spain (1.74 per cent). Does this suggest barriers exist to researching in Germany or merely that Kenyans have no interest in carrying out such academic pursuits here?


    Figure 1. Who Studies Whom

    Who studies whom? Red lines indicate source countries; blue ones depict destination countries. The project analysed 49,000 publications focused on the SDGs, identifying where each originated from.
    Source: Yang et al. (2024).
    Notes: Red lines indicate source countries; blue ones depict destination countries. The project analysed 49,000 publications focused on the SDGs, identifying where each originated from (determined by the affiliations of authors) as well as its region(s) of focus (determined by locations mentioned in the title and abstract).

    Restrictions on international mobility are a problem in general for Kenyan and other researchers from the Global South. Difficulty getting visas, prohibitive financial requirements, and excessive bureaucracy are among the structural barriers to doing research in Germany. But even removing these constraints will not see other cultural barriers to academic collaboration that exist easily surmounted.

    Short-Term Academic Culture

    Collaboration with researchers in Kenya, or elsewhere, requires building international research capacity and partnerships. Such work is time-consuming, with a high risk of early failure and a pay-off that may only come years later. For researchers in a highly competitive Western academic ecosystem, with a laser-eyed focus on publishing papers, such long-term investment can be seen as needless or risky, especially if partner universities require training in knowledge or skills to facilitate such collaboration. In other words, the “publish-or-perish” mindset is biased against those who invest more resources in fewer studies (cf. Smaldino and McElreath 2016). The Maria Sibylla Merian Initiative, which sees the GIGA partner with two Merian Institutes in Tunisia and Ghana, can be held up as a notable attempt to reduce asymmetrical knowledge production. But, overall, quickly publishing papers requires focus on short-term projects premised above all on data collection rather than long-term investments in academic development.

    Socio-Economic Disparities

    From the Kenyan side, short-termism is less about publishing pressures than a simple lack of resources. As Dr. Lynette Osario from Strathmore University, Nairobi, states about the challenges accompanying fieldwork: “There is no budget for such research, so it would have to be sourced from project funders; this is not guaranteed.” In general, African countries spend 0.42 per cent of their gross domestic product on research and development compared to the global average of 1.7 per cent (Caelers and Okoth 2023). Socio-economic status and low per capita income are argued to influence African scholars in various ways by impoverishing “the quantity and quality of their scientific research works” (Mulisa 2021: 931). Since many African scholars are often forced to seek extra means of income to meet their basic needs, such as consulting or teaching on multiple campuses, they often do not have adequate time to conduct rigorous, innovative scientific studies (Teferra 2016).

    The above inequality is evident in the literature’s makeup, too. For example, looking at the patterns to be found in leading Economics journals publishing regularly on Africa between 2005 and 2015, Chelwa (2021) found that, on average, only 25 per cent of the articles in question had at least one African-based author over this period. Further, while the examined journals dedicate about 30 per cent of their content to African affairs, only 3 per cent of their editorial-board members are based on the continent itself.

    Why Change the Status Quo?

    While the above may help explain the dissonance between my research in Kenya and the equivalent being done in Germany, it may not, prima facie, justify reform. One might claim that the GIGA is simply pursuing the interests of German science for the country’s taxpayers and cannot address every source of inequality currently prevailing in the global research landscape. However, there are scientific reasons why the status quo should be addressed – namely, so German taxpayer money is spent on better research.

    Diversity of Ideas

    Historically produced academic Eurocentrism, where researcher identity and incentives affect the topics studied, can benefit from a greater diversity of ideas that sees us move away from paternalistic attitudes towards the African continent. Increased collaboration was highlighted by Gibbons et al. (1994) as a key way to solve practical problems affecting society, thus calling for expertise across disciplines and institutional boundaries. A given region’s both insiders and outsiders can offer crucial insights. For example, variolation – an early method of inoculation against smallpox in the eighteenth century – resulted from the knowhow of an enslaved African man named Onesimus, who later introduced this technique to clergyman and researcher Cotton Mather in Boston (Nakayama 2022). Onesimus described how, in his homeland, material from smallpox sores was deliberately introduced into the skin of healthy individuals, leading to a mild infection that conferred immunity against future severe outbreaks. Similarly, a Kenyan researcher in Germany can offer a perspective that their European counterpart may not have considered, and vice-versa. Collaborating researchers can cross-pollinate ideas via their respective insider–outsider perspectives.

    Data-Quality Issues

    Replicability haunts the Social Sciences, with researchers struggling to reproduce the results of published studies. It is unclear how much of this relates to poor data-collection practices. My experience in Kenya made clear that most GiveDirectly basic-income recipients are not aware of the wider context to the research endeavours that they are participating in. Despite signing consent forms that explained what would take place, many admitted they viewed interview questions from visiting enumerators as some form of test that they needed to answer correctly to keep receiving payments or potentially increase them. Such social-desirability bias – that is, the impulse to state the most pleasing answer rather than the truth – seemed evident from other answers given. Respondents would often say the money was spent chiefly on school fees, livestock, and food, while flatly denying spending any of it on alcohol. While it was clear from personal observation and speaking to school staff that indeed money was being spent on the above needs, a visit to the local illicit brewer indicated that the days each month when GiveDirectly payments arrived coincided with her busiest. One recipient said his payments were stopped due to a neighbour informing GiveDirectly of his alcoholism. Again, this made it unsurprising that a level of social-desirability bias would take hold vis-à-vis research answers. Reports of underpaid and overworked Kenyan enumerators falsifying data exacerbate such concerns over the latter’s quality (Kinstler 2024). The greater involvement of local researchers could help address these failings in data collection and foster closer ongoing relationships with participants, rather than simply extracting information from them.

    External Validity and Big Data

    Scientific findings generated by small foreign teams result in a patchwork literature that can lack external validity, meaning that it is not generalisable from its initial location to elsewhere. This can be frustrating for practitioners and policymakers. While various technical solutions have been proposed, greater collaboration will allow larger samples across more locations to be amassed. Related to this is the standardisation of datasets. With the growth of computational research, large-N models are hungry for vast, standardised datasets. Some common examples are the Demographic and Health Surveys and Human Development Reports. But with “small-team science,” the datasets created are fragmented across numerous repositories with differently formatted codebooks and specificities of respective data collection. This makes utilisation of such data in large-N studies messy and time-consuming.

    What Does It Mean to “Decolonise” Research?

    Addressing all the above scientific weaknesses can be a benefit of “decolonising” research projects. So doing means to concern ourselves with epistemology, the processes informing knowledge production, and how the legacies of colonial-era structures and beliefs have residual effects in the contemporary era. As stated by Smith:

    The globalization of knowledge and Western culture constantly reaffirms the West’s view of itself as the centre of legitimate knowledge, the arbiter of what counts as knowledge and the source of ‘civilized’ knowledge. (Smith 2019: 72)

    Decolonialising research does not mean replacing European or “Western” knowledge. Rather, it seeks to challenge the hegemony of these perspectives to better appreciate the diversity of experiences and forms of knowledge that co-exist in the world – especially in the Global South. Mainstream academia has typically overlooked the latter as a credible source of knowledge production, often treating it as merely a place for knowledge testing or application instead. The aim here, then, is to expand the scope of academic practice by better reflecting the lived experiences of people around the world.

    This means a shift to co-designing research and moving away from the extractive manner in which data collection is conducted at present, while removing the structural, socio-economic, and cultural barriers that exist to collaboration on equal footing.

    Exploring “Big-Team Science” as a Tool of Decolonisation

    “Big-team science” emerged as a contrast to typical projects deemed representative of “small-team science” – that is, those involving a very limited number of collaborators centred around a single primary investigator. By definition, and in contrast, “big-team science” involves many researchers. These individuals furthermore collaborate “across labs, institutions, content areas, culture and geography” (Kreamer et al. 2024: 3).

    The above-listed challenges can be tackled head on by adopting a “big-team science” approach. Large sample sizes increase statistical power, and a wide variety of locations being involved generates large datasets and makes the science more robust, though still not necessarily universally generalisable (Ghai, Forscher, and Hu 2024). “Big-team science” also allows for specialisation and a division of labour, a key to efficiency gains, with tasks given to those best placed to do them.

    Figure 2 below shows how different tasks that can be delegated among team members, labs, or institutions (Adetula 2024). Their allocation should be equitably negotiated between partners to avoid potential exploitation. For instance, if African scholarly collaborators are only involved in data collection and not the design or analysis of results, despite a desire to contribute, then this can be problematic since they are kept from involvement in the creative elements of what can be considered “high value-added” processes. Instead, genuine equilibrium would see all partners involved in any aspects they wished to be; if support or teaching are required from the other party, then this would be balanced out by doing additional work for the project. Those institutes that are weak in some of these areas can still participate in suitable roles as their skills and capacities continue to develop over time, then expanding to other tasks.


    Figure 2. “Big-Team Science” and the Allocation of Research Tasks

    Figure shows how different tasks that can be delegated among team members, labs, or institutions. Their allocation should be equitably negotiated between partners to avoid potential exploitation.
    Source: Author’s own compilation, based on Adetula (2024).

    Funding matters are considered part of the team’s mandate, but the division of labour here operates non-hierarchically to prevent those managing finances from exerting disproportionate control. Sourcing and managing the research budget should not make these individuals superior to other team members. “Big-team science” thus requires a balancing act between partners. Inclusive governance structures can be established to allow democratic decision-making within said team.

    Digitalisation and “Big-Team Science”

    Digitalisation facilitates “big-team science” in a multitude of ways. What were previously paper-based surveys can now be done by tablet, with results uploaded from anywhere in the world to a cloud server via mobile or satellite Internet. Video calls, instant messaging, and free collaborative platforms such as Pumble or Rocket.Chat allow global communication, while artificial intelligence-based translation systems enable people to speak and interact across linguistic divides. This flexibility can be prospectively leveraged by a coordinated group of field researchers situated in thousands of locations worldwide all collecting data. The same digital technology that allows GiveDirectly to send money to over a million people at present could also pay researchers to contribute to collaborative projects around the world.

    Examples of “Big-Team Science” Projects

    “Big-team science” typically involves seeking large-scale breakthroughs that cannot be achieved in smaller settings. Frustration with a lack of replication in Behavioural Genetics led to large research consortia pooling their resources to create the UK Biobank that now holds data on 500,000 participants (Forscher et al. 2023). In Particle Physics, mega collaboration around nuclear research led to the European Organization for Nuclear Research (CERN) – builder of the Large Hadron Collider that discovered the Higgs-Bosson particle. In the Social Sciences, a number of “big-team science” projects already exist in Psychology (Forscher et al. 2023). For example, the Psychological Science Accelerator (PSA) is a network of more than 2,400 researchers from 73 countries with an organised governance structure, and a set of policies for evaluating, preparing, and conducting studies and disseminating research products. Anyone can submit a study proposal to the PSA which then goes through review to determine its feasibility and, if approved, proceeds to be tested across all sites for generalisability. A related example is ManyLabs Africa, another “big-team science” project running experiments – except in this case, the typical Western structures are flipped upside down such that psychological theories identified in Africa by Africans are tested for generalisability in 46 sites across North America, Europe, and the home continent (Adetula 2024).

    In fields relating directly to the GIGA’s work, “big-team science” would be most useful for distributing experiments relevant in a wide variety of contexts. For example, the comparative effects of misinformation, migration flows, economic inequalities, climate economics, supply-chain governance, conflict and peacebuilding, and international cooperation, to name a few. “Big-team science” makes sense for an institute like the GIGA: that is, one focused on comparative studies. Gathering large amounts of data from different countries without needing to send people all over the world is possible herewith, thereby reducing the sizeable carbon footprint typically associated with international collaboration.

    Benefits and Challenges of “Big-Team Science”

    In terms of decolonisation, the co-designing of a “big-team science” project and democratic decision-making around the research questions employed (in line, for instance, with the PSA’s current approach) means there are no “local” experts as such. Everyone is a collaborator; fluidity between projects and countries ensues. By building long-term trust among team members and across institutions, the foundations are set for meaningful collaboration transcending traditional hierarchies. This trust is critical for ensuring partnerships begin on equal footing, emphasising the necessity of research projects’ co-designing rather than merely incorporating additional voices or using them as a postscript. Capacity-building initiatives can also be run through the network, such as tandem PhD programmes where, for instance, doctoral students from Germany and Kenya can collaborate on the same research question, switching countries midway to gain both insider and outsider perspectives – each bringing unique understandings vis-à-vis local contexts.

    As discussed, “big-team science” can also enhance research robustness and statistical power by pooling expertise and resources. Multilateral approaches ensure not only the development of local research systems but also the equitable participation of all team members in knowledge creation. This model actively integrates indigenous expertise, enriching theoretical frameworks and improving contextual accuracy.

    While “big-team science” may be strong in theory, myriad daunting practical challenges currently exist. On the African side, limited infrastructure and slow Internet connections can impede participation and collaboration. These logistical hurdles are compounded by heavy bureaucracy, which often delays processes like obtaining ethics approval – a particularly messy and time-consuming aspect of cross-national research.

    Career growth poses another pitfall, as contributing to a “big-team science” project often does not carry the same weight for one’s individual advancement as producing leading independent studies might. This can disincentivise participation. Additionally, teams may sometimes suffer from ineffective management or members with insufficient expertise, creating gaps in research quality and efficiency that require unrealistic levels of training to rectify.

    Regulations like GDPR add further complexity, particularly when handling sensitive data across borders. Funding rules, including strict deadlines for disbursement, often clash with the fluid timelines of large-scale, collaborative research. Moreover, the coordination and networking demands of “big-team science” can become overwhelming, requiring significant effort to manage diverse teams and align respective goals. Testing indigenous forms of knowledge creation may meet with epistemological scepticism in academic circles making funding such approaches difficult, as they may not satisfy conventional priorities or criteria here.

    Small Steps on a Long Road

    Despite its challenges, “big-team science” carried out via digital networks offers an innovative framework for increasing partnership with Global South researchers no matter their skill level and nationality, being scaled up where the potential for that exists. Decolonising research herewith is not to be done merely out of altruism; it also constitutes a viable means of addressing the various pressing scientific issues discussed throughout. Such projects cannot be expected to be implemented overnight, but openness to them as a necessary first step for their further development and gaining of momentum will allow more African and non-African researchers to collaborate and make key discoveries together going forwards.



    Fußnoten


      Literatur

      Adetula, Adeyemi (2024), Building Research Capacity in Africa Via Big-Team Science: Challenges and Lessons Learned from the ManyLabs Africa Initiative, in: Patrick S. Forscher and Mario Schmidt (eds), A Better How: Notes on Developmental Meta-Research, Nairobi: Busara, 102–111, accessed 5 December 2024.

      Caelers, Di, and Dann Okoth (2023), Research Funding in Africa: Navigating Sustainability and Shifting Perspectives, in: Nature Africa, 10, 14 December, accessed 5 December 2024.

      Chelwa, Grieve (2021), Does Economics have an ‘Africa Problem’?, in: Economy and Society, 50, 1, 78–99, accessed 5 December 2024.

      Forscher, Patrick S., Eric-Jan Wagenmakers, Nicholas A. Coles, Miguel Alejandro Silan, Natália Dutra, Dana Basnight-Brown, and Hans IJzerman (2023), The Benefits, Barriers, and Risks of Big-Team Science, in: Perspectives on Psychological Science, 18, 3, 607–623.

      Ghai, Sakshi, Patrick S. Forscher, and Chuan-Peng Hu (2024), Big-Team Science Does Not Guarantee Generalizability, in: Nature Human Behaviour, 8, 1053–1056.

      Gibbons, Michael, Camille Limoges, Peter Scott, Simon Schwartzman, and Helga Nowotny (1994), The New Production of Knowledge: The Dynamics of Science and Research in Contemporary Societies, in: Contemporary Sociology A Journal of Reviews, 24, 6, 751–752, accessed 5 December 2024.

      Hein, Wolfgang, and Robert Kappel (2014), Raum, Welt, Wirtschaft: Andreas Predöhl – eine deutsche Wissenschaftlerkarriere [Space, World, Economy: Andreas Predöhl – A German Academic Career], GIGA Working Paper 252, accessed 5 December 2024.

      Kinstler, Linda (2024), How Poor Kenyans Became Economists’ Guinea Pigs. Randomised Controlled Trials Have Many Problems. They May Still Be the Best Too for Solving Poverty, in: 1843 Magazine, The Economist, 1 March.

      Kreamer, Liana M., Haley R. Cobb, Christopher Castille, and Joshua Cogswell (2024), Big Team Science Initiatives: A Catalyst for Trustworthy Advancements in IO Psychology, in: Acta Psychologica, 242, February, accessed 6 December 2024.

      Mulisa, Feyisa (2021), Challenges for African Scholars in the Globalization Era: Contexts Speak, in: Journal of Knowledge Economy, 12, 923–942, accessed 6 December 2024.

      Nakayama, Don K. (2022), America’s Original Immunization Controversy: The Tercentenary of the Boston Smallpox Epidemic of 1721, in: The American Surgeon, 88, 10, 2425–2428, accessed 6 December 2024.

      Smaldino, Paul E., and Richard McElreath (2016), The Natural Selection of Bad Science, in: Royal Society Open Science, 3, 9, Article 160384, accessed 6 December 2024.

      Smith, Linda T. (2019), Decolonizing Research: Indigenous Storywork as Methodology, London: Bloomsbury Publishing.

      Teferra, Damtew (2016), Conclusion: The Era of Mass Early Career Academics and Aging Faculty – Africa’s Paradox, in: Studies in Higher Education, 41, 10, 1869–1881, accessed 6 December 2024.

      Yang, Liuhuaying, Elsa Andres, Emanuele Calò, Maria del Rio Chanona, Marcia Ferreira, Maria Henkel, Júlia Számely (2024), Complexity Science Hub: Who Studies Whom, accessed 5 December 2024.


      Lektorat GIGA Focus Afrika

      Petra Brandt

      Editorial Management


      Forschungsschwerpunkte

      Wie man diesen Artikel zitiert

      Crawford, Andrew (2024), Decolonising Research via Digital Networks? Exploring Big-Team Science, GIGA Focus Afrika, 5, Hamburg: German Institute for Global and Area Studies (GIGA), https://doi.org/10.57671/gfaf-24052


      Impressum

      Der GIGA Focus ist eine Open-Access-Publikation. Sie kann kostenfrei im Internet gelesen und heruntergeladen werden unter www.giga-hamburg.de/de/publikationen/giga-focus und darf gemäß den Bedingungen der Creative-Commons-Lizenz Attribution-No Derivative Works 3.0 frei vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden. Dies umfasst insbesondere: korrekte Angabe der Erstveröffentlichung als GIGA Focus, keine Bearbeitung oder Kürzung.

      Das German Institute for Global and Area Studies (GIGA) – Leibniz-Institut für Globale und Regionale Studien in Hamburg gibt Focus-Reihen zu Afrika, Asien, Lateinamerika, Nahost und zu globalen Fragen heraus. Der GIGA Focus wird vom GIGA redaktionell gestaltet. Die vertretenen Auffassungen stellen die der Autorinnen und Autoren und nicht unbedingt die des Instituts dar. Die Verfassenden sind für den Inhalt ihrer Beiträge verantwortlich. Irrtümer und Auslassungen bleiben vorbehalten. Das GIGA und die Autorinnen und Autoren haften nicht für Richtigkeit und Vollständigkeit oder für Konsequenzen, die sich aus der Nutzung der bereitgestellten Informationen ergeben.

      GIGA Working Papers | 06.2023

      Digitalisation and Labour Markets in Developing Countries

      Die Auswirkungen der Digitalisierung auf die Arbeitsmärkte sind weltweit zu spüren. Im Globalen Süden wird der Internetzugang ausgeweitet, digitale Plattformen verbreiten sich, aber Zugang zu und Nutzung von digitalen Technologien ist noch nicht überall gegeben. Wir untersuchen die Auswirkungen einiger dieser digitalen Trends auf den Arbeitsmarkt.

      Benachrichtigungen

      Melden Sie sich hier für E-Mail-Benachrichtigungen zu GIGA-Aktivitäten an

      Soziale Medien

      Folgen Sie uns