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Recent research

Women in blue? Wikipedia's gender gap reverses in some areas


A monthly overview of recent academic research about Wikipedia and other Wikimedia projects, also published as the Wikimedia Research Newsletter.


Women in blue? "[T]he trend reversed in 2022" and female biology professors are now more likely to have a Wikipedia biography than male ones

Reviewed by Czarking0 and Tilman Bayer
"Percentage of female versus male faculty with Wikipedia biographies from 2014 to 2024" (from the paper). "*", "**", and "***" denote statistically significant differences, "n.s." denotes insignificant ones.

Times may be changing on our project. A recent publication in the Proceedings of the Royal Society highlights how representation of female tenure-track biologists has surpassed that of their male counterparts.[1]

Using a recently generated census of 2104 female and 3721 male tenured and tenure-eligible faculty members affiliated with the biology departments of all United States R1 universities, we examined the extent to which biology faculty are covered on Wikipedia. Women in the census were significantly less likely to be featured on the platform than their male peers until 2018. However, the trend reversed in 2022, and women were 25% more likely than men to have a Wikipedia biography in 2024. In addition, women's biographies tend to be longer than those of men.

As we have noted here at various times before (not just regarding gender biases, but also e.g. regarding political biases), gaps in coverage are not necessarily due to biases on behalf of Wikipedia itself (in the sense of editors "putting the thumb on the scale"). In this case though, while trying to understand "the causes of this reversal", the authors plausibly point to changes on Wikipedia itself, namely the activities of the WikiProject Women in Red, which began counteracting the article gap in 2015, and related efforts:

Among the 163 women’s biographies created since 2015, 78 were created by Wikipedia editors that were affiliated with the Women in Red project (figure 5 [reproduced below]), 16 were created by editors affiliated with the Women Scientists project (however, 14 of these were created by individuals that were also part of the Women in Red project), and 13 were created by users registered as students enrolled in university courses that require/encourage contributing to Wikipedia.

"Number of new Wikipedia biographies for female and male biology faculty" over time (from the paper)

The researchers also obtained various other variables as part of their census of professors, and analyzed their relation to the likelihood of having a Wikipedia biography:

Among faculty with Wikipedia biographies, women had significantly fewer publications and citations, lower h-indexes and shorter careers (i.e. they started publishing more recently [...]), suggesting that the research output required to be covered on Wikipedia is higher for men than for women. The university ranking was not significantly different between women and men with Wikipedia biographies

A few further statistical analyses controlling for these academic metrics indicated that

[...] gender has no effect on the number of views (p = 0.600), the number of edits (p = 0.488) or the number of edits per year (p = 0.485), indicating that women’s Wikipedia biographies are viewed and edited as often as those of men with the same academic rank and a similar affiliation, seniority and research output. However, gender does have an effect on biographies’ lengths (p = 2.66 × 10−5), and a separate linear regression analysis for women’s and men’s biographies indicates that, given any h-index, women’s biographies tend to be longer than those of men [...].

In Germany, "female professors seem to have a higher chance of having a Wikipedia biography than their male counterparts"

Predicted probabilities [for professors in Germany to have an article on German Wikipedia] differentiated by university type, gender, and discipline]", according to the authors' models (from the paper)
Reviewed by Tilman Bayer

Another recent study[2] focused on the coverage of German scholars on the German Wikipedia and similarly found that

Surprisingly, gender had a positive and significant effect: female professors seem to have a higher chance of having a Wikipedia biography than their male counterparts (B = 0.340, p = 0.024).

This effect was determined to be concentrated in STEM disciplines:

Female professors in STEM fields had a higher predicted probability of having a Wikipedia biography than their male colleagues. Outside STEM, no gender effects were observed.

Similar to the above study of US biology professors on enwiki, the authors started with a systematic census of their target population, and also examined the (not necessarily causal) effects of other scholarly metrics on the likelihood of being covered on Wikipedia:

Our study is based on data from an online survey of 1839 professors in Germany. Four binary logistic regression models and predicted probabilities were calculated to test our hypotheses. The results indicated that the number of published articles (OR = 0.999; p = 0.110) and awards (OR = 1.007, p = 0.781) did not predict having a Wikipedia page, while press articles had a positive but small effect (OR = 1.005; p = 0.005). Among all variables aiming to capture notability, a professorship at a university of applied science (UAS) was most powerful and had a significant negative effect (OR = 0.176; p < 0.001). Individual activities, such as social media activity (OR = 1.248; p = 0.002) and networking (OR = 1.433; p = 0.012), had a positive effect.

Unlike the above US-focused Proceedings of the Royal Society paper, the authors here did not attempt to track changes in the German Wikipedia's coverage over time, or to assess the potential impact of editing campaigns that target gender gaps. Those are only mentioned in passing in a section titled: "What can scientists do to get a Wikipedia biography?":

[...] extended professional networks could also have a direct impact on Wikipedia biographies, as they increase the likelihood of being portrayed as part of Wikipedia editing campaigns (such as edit-a-thons). This may be especially helpful for female professors, as there are Wikipedia networks such as “FemNetz” and “WomenEdit” in Berlin as well as “Who writes his_tory?” in Switzerland, which are committed to writing biographies about women on Wikipedia [...].

Other recent publications

Other recent publications that could not be covered in time for this issue include the items listed below. Contributions, whether reviewing or summarizing newly published research, are always welcome.

Compiled by Tilman Bayer

"Quantifying (Mis)alignment Between Reader Focus and Editor Citation in Scholarly Biomedical Topics in Wikipedia"

From the abstract:[3]

"we quantitatively explore both (a) how scholarly biomedical research is cited in biomedically-focused Wikipedia articles, and (b) whether this reflects the topical patterns of those articles' readership in Wikipedia. Our methods identify quantitative avenues for improved alignment between editors' limited effort and readers' focus, with respect to both the biomedical topics themselves and the caliber of biomedical research cited. In other words, readers focus on topics that are very human-focused, but editors focus their citation work on basic science topics (e.g. molecular and cellular biology), leading to disproportionate citation rates of basic research publications for biomedical topics in Wikipedia."

See also our coverage of earlier research that similarly found a "Misalignment Between Supply and Demand" of Wikipedia's content

"The most influential philosophers in Wikipedia: a multicultural analysis"

From the abstract:[4]

"We explore the influence and interconnectivity of philosophical thinkers within the Wikipedia knowledge network. Using a dataset of 237 articles dedicated to philosophers across nine different language editions (Arabic, Chinese, English, French, German, Japanese, Portuguese, Russian, and Spanish), we apply the PageRank and CheiRank algorithms to analyze their relative ranking and influence in each linguistic context. Our findings suggest that while philosophers, and their associated schools of thought, do not serve as the foundational building blocks of the Wikipedia knowledge structure, they remain critical reference points within it. The top ten articles devoted to philosophers for each language edition is determined. We observe significant cultural variations in the ranking of these figures across language editions, with Western philosophers, in particular, being disproportionately represented among the most influential."

See also our earlier coverage of related research: "Wikipedia-based graphs visualize influences between thinkers, writers and musicians"

"Filling in the Blanks? A Systematic Review and Theoretical Conceptualisation for Measuring WikiData Content Gaps"

From the abstract:[5]

"Wikidata [...] features a long-tail of items with limited data and a number of systematic gaps within the available content. In this paper, we present the results of a systematic literature review aimed to understand the state of these content gaps within Wikidata. We propose a typology of gaps based on prior research and contribute a theoretical framework intended to conceptualise gaps and support their measurement. We also describe the methods and metrics present used within the literature and classify them according to our framework to identify overlooked gaps that might occur in Wikidata. We then discuss the implications for collaboration and editor activity within Wikidata as well as future research directions. "

References

  1. ^ Alvarez-Ponce, David; Iyengar, Niveda (27 May 2026). "Monitoring the gender gap in the coverage of biology professors on Wikipedia". Proceedings of the Royal Society B: Biological Sciences. 293 (2071) 20252566. doi:10.1098/rspb.2025.2566. ISSN 0962-8452. PMID 42191161.
  2. ^ Spagert, Lina; İnal, Zeynep; Wolf, Elke (2026-08-05). "Who gets a Wikipedia biography? Analysing notability criteria, actions for visibility and gender effects among professors in Germany". Humanities and Social Sciences Communications. 13 (1): 1284. doi:10.1057/s41599-026-08217-5. ISSN 2662-9992.
  3. ^ Afshar, Askar Safipour; Yang, Qiyao; Thebault-Spieker, Jacob; Hutchins, B. Ian (2026-02-17). "Quantifying (Mis)alignment Between Reader Focus and Editor Citation in Scholarly Biomedical Topics in Wikipedia". Quantitative Science Studies. 7: 326–348. doi:10.1162/QSS.a.457. ISSN 2641-3337.
  4. ^ Rollin, Guillaume; Lages, José (2025-09-30). "The most influential philosophers in Wikipedia: a multicultural analysis". EPJ Data Science. 14 (1): 69. doi:10.1140/epjds/s13688-025-00570-w. ISSN 2193-1127.
  5. ^ Ripoll, Marisa; Reeves, Neal; Kurteva, Anelia; Simperl, Elena; Peñuela, Albert Meroño; Diepold, Klaus (2025-06-10). "Filling in the Blanks? A Systematic Review and Theoretical Conceptualisation for Measuring WikiData Content Gaps". arXiv:2505.16383 [cs.SI].


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  • re: "Women in Blue" - are these findings reported in "Gender bias on Wikipedia? I dont see it there. --Altenmann >talk 03:21, 24 August 2026 (UTC)reply
    I just noticed this research a few days two weeks ago, and I look pretty systematically for Wikipedia-related news items. ☆ Bri (talk) 03:27, 24 August 2026 (UTC)reply
    This is not an answer to my question. Is anybody going to update "Gender bias on Wikipedia? It looks pretty outdated to me. --Altenmann >talk 04:48, 24 August 2026 (UTC)reply
    If you can find the time, it looks like you might be the best choice make any amendments needed to that article. The research cited here seems sufficient for at least some changes. Best, ~ Pbritti (talk) 18:14, 24 August 2026 (UTC)reply
    Whom are you addressing to when you write "you"? Most surely I am far from being a good choice to edit about gender bias, for many reasons. Of course, WP is "the free encyclopedia that anyone can edit" :-) Yes, I can, but after that 4 more editors will be needed to fix my fixes. :-) --Altenmann >talk 18:54, 24 August 2026 (UTC)reply
    Hey there! Just so you know, I've tried my best at summing up the news on the aforementioned Wikipedia page. I hope this helps. By the way, if confirmed, this would be a major milestone for WIR and other projects focusing on gender equality! Oltrepier (talk) 20:43, 24 August 2026 (UTC)reply
  • Re the biomedical citations paper, might this be a consequence of WP:MEDRS by design suppressing citations to primary medical research? Fences&Windows 12:44, 26 August 2026 (UTC)reply
    Nah this is likely a case of differing interests. Random Disease X exists. The basics of disease X will need 20-30 hard science papers to cover the background alone. What causes it? What type of bacteria/virus/other pathogen is responsible? Mechanisms of action? When was it discovered? What are the possible treatments/research possibilities into treatments? All that stuff will need Wikipedians to cite Smith et al, Wang et al, Kirov et al, Perez et al. in the Journal of Very Serious Science Business and other venues. Whereas Uncle Tom and Aunt Sally are coming at the article from "I saw on the Facebook that Disease X was caused by the Government using 5G to create a humour imbalance that you can solve by taking Dr Podcast's magic sugar pills for only 13.99$ a month." or have much more basic questions like "Does Disease X cause cancer?" Headbomb {t · c · p · b} 13:57, 26 August 2026 (UTC)reply
    I think “primary” in this context refers not to primary sources, but to basic scientific research, which can be supported by both primary and secondary sources. More importantly, I think the paper is seriously flawed. The analysis should have been restricted to articles within the scope of WP:MED, but it also includes WP:MCB articles. As a result, the study ends up comparing reader interest in patient-relevant topics with citation volume in a body of literature whose corresponding Wikipedia articles which were never oriented toward patients in the first place. Boghog (talk) 16:01, 26 August 2026 (UTC)reply
  • I've read the "biomedicine" paper, and I found parts of it a bit confusing.
    • For example, they say we assumed each citation contributed equally to an article’s views. It seems strange for them to assume that the citations cause page views. Also, we know that each citation doesn't get equally viewed. They don't appear to account for the number of times a citation is re-used in an article, and they don't appear to account for the fluctuation in the number of citations in an article over time.
    • They worry that only "0.54%" of Wikipedia pages cite one or more PubMed-indexed articles, but Wikipedia might well be 99.46% non-biomedical articles. An articletopic search[1] finds 88.5K medicine-related articles, which is about 1.2% of all articles, and that's probably over-counting, because the non-biomedical article Sigmund Freud is on the first page. I wonder whether their "biomedical" articles include non-biomedical articles that happen to mention medical terms (e.g., Medical practice management software or Anthony Fauci or Susan G. Komen).
    • AFAICT their main result – though they don't seem to realize it – is that a lot of human health information can be sourced to medical textbooks and reference works (which they ignore), but up-to-date MCB content often requires citing scientific literature directly. For example, they write Although clusters with higher readership tend to have higher quality citations, they are less frequently cited, but the paper cannot determine this; the most it can say is Although clusters with higher readership tend to have higher quality citations, they are less frequently cited to papers published in PubMed, because we ignored all those citations to textbooks, reference works, and anything else that wasn't indexed by PubMed. Similarly, they want to be transferring scientific research publications into Wikipedia’s scientific content, whereas we want to be transferring scientific information into Wikipedia’s scientific content.
    • I thought this was particularly interesting: Popular clusters with high readership on Wikipedia tend to cite a higher proportion of high strength-of-evidence studies, as per our EBM strength-of-evidence metric. However, clusters that are heavily cited on Wikipedia often have a lower proportion of these studies. In essence, the popularity of a topic on Wikipedia aligns with the strength of evidence of research cited, but clusters with extensive citations by editors do not necessarily focus on high strength-of-evidence research. Translated into wikijargon, this says that high-traffic medical articles tend to use WP:MEDRS sources, and low-traffic articles tend to cite a large number of weak WP:MEDPRI sources. This probably shouldn't surprise anyone. WhatamIdoing (talk) 05:10, 27 August 2026 (UTC)reply
    I don't get that 0.54% of articles. There's at least 1.35M pmid from {{cite journal}} alone [2]. We're at about 7.2M (7,239,347) articles. That should be ~19% of articles (if you use Pages instead, which you really shouldn't, because no one cares about redirects, categories, templates, subpages, etc...) you'd have 66M instead (66,244,197) but 1.35M/66M still is 2%. Headbomb {t · c · p · b} 13:00, 27 August 2026 (UTC)reply
    I think that tool is counting the number of instances of the parameter, e.g., so that Cancer is 180 copies of |pmid=, rather than one article containing that parameter an arbitrary number of times.
    {{Cite journal}} is in ~975K articles[3], so its |pmid= is used in less than that many articles. My quick search suggests that |pmid= is in ~229K articles, or about 23% of the articles that use the {{cite journal}} template, or a bit more than 3% of all articles (now; they were using an older dataset). WhatamIdoing (talk) 17:20, 27 August 2026 (UTC)reply
    Looking deeper, my number was all instances across all namespaces, so your number of 975K is more accurate (the tool I used returns 978K distinct pages across all namespaces for cite journal). 1.35 M is, like you said, total PMID usage. For articles, it's 229K. There's further 30K from {{citation}}. There's a further ~500 from {{pmid}}.
    There will be some overlap, but there are also other templates with PMIDs. So (229K+30K+500)/7.2M = 3.6%. Still pretty far from 0.54%. Headbomb {t · c · p · b} 21:06, 27 August 2026 (UTC)reply
  • Thanks, WhatamIdoing and Headbomb. Your comments were very helpful, particularly the distinction between medical and MCB sourcing practices. That prompted me to look more closely at the article population. I have been in contact with the authors of the paper, who have been quite responsive. They sent me the "views.csv" file used in their analysis, which links Wikipedia pages with readership, PubMed citations, reference counts, and article-quality metadata. The table below summarizes WikiProject membership among the 130,108 Wikipedia articles in this file. My conclusion is that only about 20% of the articles analyzed in the paper fall within the WP:MED umbrella. Many of the remaining articles belong to hard-science projects such as WP:MCB, WP:MICRO, and WP:CHEM. I was able to reproduce the published negative citation–readership relationship in the full dataset, but this relationship disappears when the analysis is restricted to the 25,807 WP:MED umbrella articles. This suggests that the reported misalignment is driven at least in part by pooling medical articles with nonmedical scientific articles that have different readership and citation patterns. Boghog (talk) 08:37, 29 August 2026 (UTC)reply
  • One more point. Cluster readership is strongly associated with article scope. Clusters with higher average readership had a substantially larger fraction of citations originating from WP:MED articles, while clusters with lower readership were more enriched for MCB-only/basic-science articles. This suggests that “popular clusters” act as a crude surrogate for WP:MED articles. Boghog (talk) 07:49, 30 August 2026 (UTC)reply
Relationship Correlation p-value Interpretation
Cluster readership vs fraction of citations from WP:MED articles +0.644 8.33 x 10−24 Higher-readership clusters are strongly enriched for WP:MED citations
Cluster readership vs fraction of citations from MCB-only articles -0.700 1.10 x 10−31 Higher-readership clusters are strongly depleted for MCB-only citations
  • This is a more general example of what happened to FRCS members. All women members had articles some years ago. Apart, of course, from new members, this means that the ratio can only now shift in "favour" of men. Nonetheless we would, surely, prefer to see full coverage. All the best: Rich Farmbrough 18:24, 7 September 2026 (UTC).reply


















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