Bas Hofstra

Knowledge lost, parity gained? COVID-19 and gender gaps in Dutch academia - Scientometrics We investigated the extent to which the COVID-19 pandemic impacted long-standing gender inequalities in Dutch academia. Dutch academia is an ideal case to gain insight on exacerbated gender differentials due to COVID-19 on employees, because men and women face comparable institutional contexts and any COVID-19 impact becomes visible and measurable fast through potentially decreased yearly publications. We reconstructed the complete publishing careers up till 2022 of more than 8000 Dutch scientists who received a PhD from 1990 onwards and still had an active publication career before the pandemic started. We compared the publication dip between men and women during COVID-19. Our data allowed us to investigate whether the gendered impact of COVID-19 varied across research domains, different PhD cohorts and type of research output. We consistently find that COVID-19 did not have more severe consequences on research output for women than for men.

COVID has reduced the number of papers published by NL-based scholars, but it has not increased the gender gap. link.springer.com/article/10.1...

This is a key paper in the growing literature on the effects of COVID-19 on academia. It is done purely with webscraped data, and it is a showcase how you can do fine-grained analyses if you put in the work.

But:
- Barriers to productivity remain persistent for women scientists
- Yet, the productivity gender gap did not widen during COVID

📖 What did we find?
- During COVID-19, scientists published about 33% fewer papers
- Dutch science was hit hard: “lost” around 20,000 publications
- Scientists with childcare responsibilities struggled to maintain productivity
- Researchers with a migration background were also hit harder

🔭 We analyzed publication data from more than 8,000 scientists across all disciplines at all Dutch universities, covering the period from 1990 to 2022.

🧐 We asked whether women in Dutch science show a stronger productivity decline than men during COVID-19

Knowledge lost, parity gained? COVID-19 and gender gaps in Dutch academia - Scientometrics We investigated the extent to which the COVID-19 pandemic impacted long-standing gender inequalities in Dutch academia. Dutch academia is an ideal case to gain insight on exacerbated gender differentials due to COVID-19 on employees, because men and women face comparable institutional contexts and any COVID-19 impact becomes visible and measurable fast through potentially decreased yearly publications. We reconstructed the complete publishing careers up till 2022 of more than 8000 Dutch scientists who received a PhD from 1990 onwards and still had an active publication career before the pandemic started. We compared the publication dip between men and women during COVID-19. Our data allowed us to investigate whether the gendered impact of COVID-19 varied across research domains, different PhD cohorts and type of research output. We consistently find that COVID-19 did not have more severe consequences on research output for women than for men.

I'm thrilled to share our latest study, published open access in Scientometrics. The paper is by Jochem Tolsma, myself, and Anne Maaike Mulders.

Here's the paper: link.springer.com/article/10.1...

Here's the replication website: coviddutchacademia.netlify.app

Het geheim van een geslaagde introductieweek? Onbezonnen lachen en niet als eerste naar bed De introductieweken voor nieuwe studenten zijn weer begonnen. Hoe maak je vrienden in deze spannende levensfase? ‘Voor iedere hobby bestaat wel een clubje.’

Het geheim van een geslaagde introductieweek? Onbezonnen lachen en niet als eerste naar bed

Ik werd geinterviewd met een aantal vragen over hoe je duurzame en nuttige netwerken opbouwt als student in een interessant stuk van de trouw @trouw.nl in de introductieweken.

GitHub - bhofstra/aca-web Contribute to bhofstra/aca-web development by creating an account on GitHub.

I built the website with Quarto, R, GitHub, and host it through Netlify. Curious how it’s made? The source code is available on my GitHub repository: github.com/bhofstra/aca.... I licensed it through CC-BY 4.0, so feel free to re-use what you need.

I’m excited to share the launch of my new website: bashofstra.com!

This site brings together all my work in a clear, accessible format. The new website is clean, minimal, responsive, and scalable and works seamlessly on desktop and mobile.

Recently presented at the CREST Sociology seminar, now published in @ssreditorial.bsky.social: @mtorre.bsky.social's "The uneven effects of gender parity"

Link: doi.org/10.1016/j.ss...

Aflevering 200 Journalistiek programma met een eigen kijk op het dagelijks nieuws.

📺 RTL EditieNL besteedde aandacht aan en interviewde mij over ons onderzoek naar de kennissenkring van Nederlanders. Samen met Beate Völker, Rense Corten, en Frank van Tubergen onderzochten we hoe groot deze netwerken zijn en hoe homogeen ze blijken te zijn.

Vanaf 7:32: www.rtl.nl/nieuws/uitze...

Met in de @volkskrant.nl tekst en uitleg bij de studie:

www.volkskrant.nl/wetenschap/e...

De @volkskrant.nl schreef een stuk over ons onderzoek naar sociale contacten en haar scheidslijnen! Zie hieronder:

Onderzoek met Beate Volker, @rensec.bsky.social, en Frank van Tubergen.

Een Nederlander kent zo’n 568 mensen: ‘Soort zoekt soort en opleiding is een bepalende factor’

Een Nederlander kent zo’n 568 mensen: ‘Soort zoekt soort en opleiding is een bepalende factor’

Nothing like having your Social Networks article (as seen at #Sunbelt2024) published while attending #Sunbelt2025!

You can find the paper here: www.sciencedirect.com/science/arti...

You can find the replication website to the paper here: bhofstra.github.io/netsize_dutch/

(PS: fitting that this gets out while I'm currently at the Sunbelt conference of the International Network of Social Network Analysis!)

Additionally, we find a pretty strong presence for gender and educational homogeneity.

These findings have important implications for Dutch social structure as to who is at risk to become socially isolated and as to where social barriers between groups exist.

We find fascinating patterns where average network size across a representative set respondents in the Netherlands is about 518 people. But more importantly, it decreases with age, unemployment, lower income, lower house values, lower education, and fewer people in a household.

This is a project that came out of our earlier popular publication at Quest where they asked us similar questions!

In this paper we use computational methods (for insiders, specifically the Network Scale-Up Method) to calculate both network size and its determinants, as well as network homogeneity and its determinants.

Who’s in your extended network? Analysing the size and homogeneity of acquaintanceship networks in the Netherlands This study advances the understanding of the size and homogeneity of personal networks, focusing on extended networks that encompass both core discuss…

Thrilled to share my latest publication in the journal Social Networks, together with Beate Völker (lead), @rensec.bsky.social, and Frank van Tubergen.

www.sciencedirect.com/science/arti...

After a pretty gruesome train ride, finally arrived in Paris for #sunbelt #sunbelt2025. Can’t wait to hear about all the amazing network studies. Shoot me a message if you want to meet or catch up!

As some of you guessed, the two models are statistically indistinguishable. The answer is Model 1, but there was no way to tell from the data. I was very surprised when I first saw this. Here we show that this confounding of heterogeneity and reinforcement is general: www.pnas.org/doi/10.1073/...

What about research sitting at the intersection of the union of two literatures…?

Two peas in a pod? How to mix methods in ethnic and migration studies This introduction to the Special Issue on ‘Two peas in a pod? How to mix methods in ethnic and migration studies’ highlights scholars’ experiences and reflections on doing mixed methods research wi...

Mixed methods milestone! 🛠️Check out this Special Issue edited by @nielsspierings.bsky.social, Tine Davids & I! No textbook perfections but practical realities on how to mix methods in migration studies and which structural barries keep mixed methods from thriving! www.tandfonline.com/doi/full/10....

Where my paper is on the quantitative end of mixing methods, the special issue includes other important pieces on mixing methods with all sorts of (quantitative and qualitative) data types.

A thank you to the special issue editors @nellageurts.bsky.social, Tine Davids, and Niels Spierings for their thoughtful feedback, and for creating a space for important work on mixing methods.

And a cautionary tale on rushing into data linkages without seriously considering the implications for things like representativity and selection bias. I include concrete examples and steps on how to address these issues.