Global South researchers succeeding against the odds: how are they different?
This blog post was written by Basma Albanna and originally published on the ICT4D Blog on 10 May 2022.
Understanding the Context
How are some global South researchers able to overcome contextual constraints and become highly cited?
There is a clear research divide between the global South and the global North [1] in terms of research investment and capabilities. The average national expenditure on research and development in Southern countries is 0.38% compared to 1.44% in Northern countries [2]. The number of researchers per million population in 2017 was 713 in the global South and 4,351 in the global North [3]. This had implications on the volume and impact of scientific outputs produced by the global South in comparison to the global North. Excluding China and India, in 2018 global North countries produced an average of more than 35,000 scientific and technical journal articles per country while global South countries produced 4,000 journal articles per country, out of which less than 2% made it to the top 1% most cited articles globally. This can be partially explained by the lower levels of investment and English proficiency, smaller relative populations of researchers, institutional exclusion factors and/or biases against Southern researchers when it comes to accepting their papers in top tier journals or awarding grants.
Despite all of the aforementioned challenges, there are a few Southern researchers who are able to achieve better outcomes than their peers. Such researchers could provide valuable insights and lessons that might help to better understand and even mitigate the current North–South divide in research outputs and citation. This blog post will highlight some of the valuable insights emerging from our recently published study that attempted to uncover publication-level and individual-level factors underlying the outperformance of information systems researchers in Egypt.
The Method
This study employed the “data-powered positive deviance” (DPPD) methodology that uses digital datasets to identify positive deviants (those performing unexpectedly well in a specific outcome measure that is digitally recorded, mediated or observed) and potentially also to understand the characteristics and practices of those positive deviants (PDs) if digitally recorded.
Three main steps were conducted to identify and characterise PDs, as shown in Figure 1:
- In the Define step, we defined our study population and the performance indicators that will be used to assign a score for each researcher. The study population comprised 203 information system researchers in Egyptian public universities. Six well-known citation metrics (h-index, g-index, hc-index, hi-index, aw-index and m-quotient) were calculated for each researcher using Publish or Perish and Google Scholar bibliometrics. Several citation metrics were used to avoid putting certain groups at a disadvantage due to factors such as the length of their research career, the size of their research departments, the age of their papers or their publication strategies.
- The Determine step aims at identifying the PDs based on the scores calculated in the previous step. In this study, PDs or outliers were defined as researchers who significantly outperformed their peers in at least one of the six citation metrics. The interquartile (IQR) method was used to identify those outliers based on their deviation from the median, i.e. lying beyond the 1.5*IQR added to the third quartile in at least one of the six citation metrics.
- The third step, Discover, consists of three main stages. In Stage 1, primary data was collected through in-depth interviews from a sample of PDs to explore practices, attitudes and attributes that might distinguish them from non-PDs. During Stage 2, the key findings from Stage 1 plus other predictors of research performance drawn from the literature were used to design a survey tool. That survey then targeted the whole population and tested if the proposed differentiators were significantly different between the two groups. Finally, in Stage 3, the Scopus database was used as the basis for analysis of researcher publications; extending and validating some of the findings identified in the previous stages.
What we found
A combination of data sources (interviews, surveys, publications) and analytical techniques (PLS regression, topic modelling) were used to identify significant predictors of positively-deviant information system researchers. One of the key findings was that PDs contributed to the creation of roughly half (48%) of the publications and achieved nearly double (1.7x) the total number of citations of non-PDs despite representing roughly one-eighth (13%) of the study population. While there were significant predictors of outperformance that are structural (e.g. gender, academic rank and role, workplace perceptions), our focus in this post is on highlighting factors that are transferable i.e. practices and strategies that are to some extent within the control of the individual researchers. Table 1 provides a summary of such factors.
Individual-Level Predictors
Publication-Level Predictors
The analysis also included a visualization of topic prevalence over time for the PD corpus and non-PD corpus as presented in Figure 2. It shows topics, such as Classification Models, where PDs were early movers and then they were followed by NPDs. There is a greater prevalence of Expert Systems and GIS-related topics in the PD corpus in comparison to the NPD corpus. Conversely, there is lower prevalence of Neural Networks and Business Process Management & Process Mining. There are also topics that had very similar proportions over time for both groups, such as Social Network Mining.
Implications for practice and policy
This analysis cannot, of course, guarantee that applying these factors more broadly would lead to the same outcomes achieved by PDs. Nonetheless, there would be value in individual Southern researchers reflecting on the research- and paper-related behaviours that have been shown associated with positively-deviant research profiles. For instance, Southern researchers work in contexts of resource limitation, hence, research grants and travel funds are of outmost importance. Including partners from Northern universities (as PDs do) increases the chances of securing the funds as those partners are more familiar with grant procurement processes and more experienced in writing proposals. Studying abroad also seems to put Southern researchers at an advantage as it does not just equip them with the technical know-how and the degree needed to pursue their academic careers, but also helps them establish channels of collaboration with their supervisors and their PhD granting universities, long after they returned to their home countries. Those long standing relationships provide further access to research grants either directly or via joint grant applications.
In terms of paper-related strategies, Southern researchers could avoid low-visibility local conferences and can select journals instead as they are more likely to deliver citations. Publishing with more authors (domestic and international) could also help pay for journal publication fees, with fees split across more authors or paid from overseas sources. Publishing with foreign authors could also help Southern researchers overcome the institutional biases[4] among editors, reviewers in single-blind or open review systems, and readers. PDs’ preference for working on established research areas rather than on radical research topics may also help in relation to institutional barriers, with research that builds incrementally on existing ideas and literature being more likely to be accepted for publication by referees, and cited by others working in the established area. Hence, Southern researchers seeking more citations could consider contributing to mainstream topics that build on existing work. Along the same lines, having multiple authors and affiliations increases the likelihood of citations, as each author has their own network and bringing those networks together can increase readership. Similarly, publishing papers with a larger number of references increases paper visibility through citation-based search in databases that allow it, such as Google Scholar, and through the “tit-for-tat” hypothesis i.e. authors tend to cite those who cite them. [5]
Higher education institutions and higher education policy makers may also reflect on the findings, and consider strategic implications for training, resource provision, collaborations, etc. For example, English and scientific/formal writing courses were associated with PD performance; such courses could be prerequisites for starting a PhD research. There could be more academic training designed around research grant writing and providing guidance on funding bodies that researchers can apply to. International research collaborations appeared as an important predictor of PDs; so, university senior managers and policy makers can explore ways to reduce barriers and increase opportunities for overseas PhD study, post-PhD return, and ongoing joint research projects with global North universities.
Citation rates are, of course, not the “be all and end all” of research: there are and should be other motivations and indicators of research. However, we hope the findings presented here can provide valuable “food for thought” for global South researchers.
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[1] The terms “South” and “Southern” will be used to refer to countries classified as upper-middle income, lower-middle income, and low income. Accordingly, the terms “North” and “Northern” will be used to refer to countries that are members of the OECD (Organisation for Economic Co-operation and Development) or are classified as high-income economies by the World Bank based on estimates of gross national income per capita.
[2] Blicharska, M., Smithers, R. J., Kuchler, M., Agrawal, G. K., Gutiérrez, J. M., Hassanali, A., Huq, S., Koller, S. H., Marjit, S., Mshinda, H. M., & Masjuki, H. (2017). Steps to overcome the North-South divide in research relevant to climate change policy and practice. Nature Climate Change, 7(1), 21–27.
[3] World Bank. (2020). Science & Technology Indicators. World Bank.
[4] Karlsson, S., Srebotnjak, T., & Gonzales, P. (2007). Understanding the North-South knowledge divide and its implications for policy: A quantitative analysis of the generation of scientific knowledge in the environmental sciences. Environmental Science and Policy, 10(7–8), 668–684.; Gibbs, W. W. (1995). Lost science in the third world. Scientific American, 273(2), 92–99.; Leimu, R., & Koricheva, J. (2005). What determines the citation frequency of ecological papers? Trends in Ecology & Evolution, 20(1), 28–32.
[5] Webster, G. D., Jonason, P. K., & Schember, T. O. (2009). Hot topics and popular papers in evolutionary psychology: Analyses of title words and citation counts in evolution and human behavior, 1979–2008. Evolutionary Psychology, 7(3), 147470490900700300.
