Teaching inclusive and critical searching

1. Introduction

As a university lecturer, you guide your students not only in what to learn, but also how to learn. In today's world of information overload, that means helping them engage with search engines and databases in a critical way. While these tools provide quick access to academic literature, they are far from neutral: what you and your students will find (or more importantly, will not find) is influenced by algorithms, disciplinary traditions and the commercial interests of the companies behind those search engines and databases.

This online guide will help you:

  • recognize biases of the most common search engines and databases;
  • understand why awareness of these biases matters for academic teaching and research;
  • equip your students with strategies for more inclusive and critical searching.

2. The biases of common search engines and databases

There are two types of important biases in search engines and databases:

  • biases in the ways search results are ranked by the search engine or database;
  • biases in what sources are covered by the search engine or database.

In the following, we present several examples to illustrate these types of biases.

Biases in how search results are ranked

Google Scholar

According to Google Scholar, results are ranked by weighing factors such as the full text of a document, where it was published, who authored it, and how often and how recently it has been cited. At first glance, this mirrors how researchers might assess relevance. Yet, Google Scholar does not disclose how these criteria are applied or prioritized.

We may understand why citations play a major role in its ranking system, but research has shown another significant bias. Google Scholar consistently favors English-language publications, even when highly cited non-English works are available. A study using keywords spelled the same in English and Spanish (e.g., capital, invisible) found that in searches of the first 1,000 results, over 900 were in English (Rovira et al. 2021, 17).

VU Library online catalogue

The VU Library catalogue is an important starting point for finding literature. Students can log in with their VUnetID to access ebooks, journals, or request physical books.

Although a library catalogue may seem neutral, results are ranked to prioritize materials available at the VU or accessible through its licenses. This also applies in the default libraries worldwide mode, which technically searches across WorldCat. On the one hand, this is practical, since publications students can access immediately are highlighted. On the other hand, relevant sources elsewhere may remain hidden. The VU catalogue reflects the research and teaching that has historically been carried out at the VU, so that certain niche or emerging topics may be underrepresented. If your students want to embark on such a topic for their paper or thesis, they may miss important literature beyond the VU's holdings if they rely on a quick search.

Biases in what sources are covered

English-language bias in Scopus and Web of Science

We have seen how Google Scholar prioritizes English-language publications. Something similar goes for two well-known databases, Web of Science and Scopus.

  • In 2019, 95,37% of the publications in Web of Science were in English, while almost half of the journals covered by the Directory of Open Access Journals are non-English (Vera-Baceta, Thelwall and Kousha 2019).
  • In 2017, Scopus prided itself on covering 2000 journals from the Asia-Pacific region, while in Indonesia and Japan alone 9000 and 3000 journals are listed in their respective national portals (Tennant 2020).

As a result, many high-quality, peer-reviewed journals from the 'Global South' that might be highly relevant for you and your students depending on the research topic, are missing in Web of Science and Scopus. E.g.,

 

A note on the VU Library's collections

Like many European and North American libraries, the VU Library’s collections reflect a bias toward Western perspectives. This means important but marginalized voices are underrepresented, and some metadata may be outdated or offensive. The catalogue’s ranking system prioritizing VU-owned content reinforces these limitations. We realize that these biases may directly influence students’ first contacts with academia. What message do our collections send students about what counts as “good” research and who belongs in academia?

With one of the most culturally diverse student populations in the Netherlands, the VU Library is actively working to create a more inclusive collection. A dedicated working group is committed to ensuring that all students and staff feel represented, both online and on in our study rooms. You can learn more about their work on our webpage.

Context: Biases in databases and knowledge production

To understand biases in academic databases, it is important to look at the broader political economy of knowledge production. The ways in which knowledge is produced, published, and disseminated are shaped by structural inequalities:

  • Market concentration and monopolization: A few major publishers (e.g. Elsevier, Springer, Taylor & Francis and Wiley) dominate the academic publishing landscape. This commodification of knowledge often prioritizes profit over equitable access.
  • 'Publish or perish' culture: Academic staff are pressured to publish frequently, often privileging quantity and citation counts over diversity of perspectives.
  • Representation gaps: Despite increasingly diverse student populations, academia remains marked by persistent whiteness and gender imbalances in faculty positions.
  • Barriers to structural change: Diversity, equity, and inclusion (DEI) efforts receive limited recognition in academic reward systems, making long-term transformation difficult.
  • Global inequalities: Authors from the Global South face particular challenges, including limited access to open access publishing opportunities and the broader digital divide.

These dynamics are reflected in the databases students use. What appears as 'neutral' search results is in fact deeply influenced by inequalities in who produces knowledge, who gets published, and whose work is most visible.

3. Why recognizing bias is crucial for you and your students

Because of biases in search engines and databases, research that falls outside the mainstream, yet could be highly relevant for your students’ essays, can be surprisingly hard to find in the common search engines and databases.

Depending on the topic, your students might want to find research that goes beyond the mainstream in terms of:

  • Epistemological perspectives, example, e.g. Chinese sources for a paper on Zen Buddhism in China or indigenous research for a paper on lithium mining in Chile
  • Authors, e.g. female authors for a paper on feminist theology  
  • Country/region, e.g. sources from Brazil for a paper on gender inequality in Latin America
  • Language, e.g. Spanish or Portuguese sources for a paper on gender inequality in Latin America

3. Strategies for more inclusive and critical searching

Check the boxes below to maximize your search results

  • The asterisk (*) represents any group of (or no) characters (e.g. liturg* searches for liturgy, liturgies, liturgical etc.).
  • The question mark (?) represents any single character (e.g., organi?ation searches for organization and organisation).
  • The dollar sign ($) represents zero or one character (e.g., religion$ searches for religion and religions).
  • No search engine or database contains all publications. Always combine several search tools!

 

 

 

Strategies for inclusive searching in common search engines and databases

Publications in languages other than English

The VU Library catalogue and many other search engines and databases will let you search for publications in other languages than English.

  • Look for a language filter in the side bar of your search results or under advanced search options.
  • Use non-English keywords. For instance, when searching Spanish-language articles, use 'desigualdad de género' instead of 'gender inequality'. Please note that publications in Web of Science and Scopus are indexed in English, so that using non-English keywords doesn't work.

If possible, combine both strategies.

These strategies and example have been taken from the blogpost Finding scholarly literature in languages other than English from the blog series Inclusive searches & sources @FMG Library from the UvA Library.

Publications from authors working in a specific country or region

Some search engines and databases will let you search for publications from authors working in a specific country or region. Look for filters like 'Country/Region' or 'Affiliation'. Here follow two examples:

  • Scopus offers two options: 1) select ‘Affiliation’ and type the name(s) of the Country/Countries before running the search, or, 2) refine the search results afterwards by ‘Country/territory’.
  • The openly accessible database Lens.org offers several filter options to look for research from a specific country. 1) before you search, select 'Scholarly works'. 2) After you have run the search, you can refine your results by 'Institution' or 'Institution Country/Region'. These two filters are also visualized to the right of the page (institution logo's and world map). 

These strategies and the first example (Scopus) have been taken from the blogpost Finding scholars
working elsewhere than in Europe, North America and Oceania from the blog series Inclusive searches & sources @FMG Library from the UvA Library.

Other (advanced) search options

There are several other ways to manipulate common database in order to find publication beyond the mainstream:

  • By excluding mainstream authors, concepts etc. by using the Boolean operator 'NOT' (or '-', enz., depending on the search engine or database you are using). E.g., 'cultural capital NOT Bourdieu'.
  • By including non-mainstream authors, concept etc.
    • by using the Boolean operator 'AND' (or '+', enz.), e.g., 'decolonization AND Fanon'.
    • by adding a specific author to your search (e.g. 'F Fanon') in the advanced search (author field).

These strategies and examples have been taken from the blogpost Google Scholar: bias, settings, advanced search, alerts from the blog series Inclusive searches & sources @FMG Library from the UvA Library.

 

Alternative search engines and databases to find more diverse literature

Please note that this list is work-in-progress. We very much welcome suggestions. Please email them to Michèle Meijer at m.l.meijer@vu.nl.

 

Finding authors from groups underrepresented in academia: examples of professional organizations, databases and special (research) collections

Databases that help find publications from the 'Global South'

Lists with more alternative databases from other institutions

Grey literature

For tips on how to find grey literature (e.g. organization reports, government documents, working papers etc.) please visit the blog post Grey literature: A tentative overview of (mostly) open access resources from the blog series Inclusive searches & sources @FMG Library from the UvA Library.

References

Pouw, W. & Bakker, B. (2024, December). 'Bezuinigen'? Tijd voor een open access-revolutie. ScienceGuide

Rovira, C., Codina, L., & Lopezosa, C. (2021). Language bias in the Google Scholar ranking algorithm. Future Internet, 13(2), 31.

Tennant, J. P. (2020). Web of Science and Scopus are not global databases of knowledge. European Science Editing, 46, e51987.

Vera-Baceta, M. A., Thelwall, M., & Kousha, K. (2019). Web of Science and Scopus language coverage. Scientometrics, 121, 1803-1813.

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    2025-11-03 13:53:50
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    This short elearning is created by Michèle Meijer (VU), Linde Voorend (VU) and Stefano Giani (UvA), on behalf of the VU University Library.

    The elearning is largely based on the workshop Diversity and Inclusion in Searching: Awareness, Sources and Strategies, given by Stefano Giani and Michèle Meijer on 20 January 2025 at the Library Academy, organized by the libraries of VU, UvA and HvA.

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    Inclusief literatuur zoeken voor VU-docenten
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    WO - Bachelor; WO - Master;
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    leraar
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    gemiddeld
    Keywords
    bias, biases in searching, critical searching, decolonization, diversity, inclusion, inclusive, inclusive literature, inclusive searching, inclusive teaching

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