Knowledge (XXG):Knowledge (XXG) Signpost/2019-08-30/Recent research

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similar language and vocabulary for both. But for athlete-related articles, there are far less articles about female athletes than males, hindering the fair representation of the female in the athletic world. The researchers also found an outlier in "she"-heavy articles, due to articles related to battleships, which are often referred to as "she" instead of "it" in naval vernacular. This finding indicates that some articles, especially "she"-heavy ones, are about objects yet still contain a pronoun that is primarily used to refer to a person, which could be undesirable and misleading. The researchers acknowledge some limitations of their proposed model: for example, the analysis of the pronouns was projected only on English Knowledge (XXG) and the articles which are structured with the binary gender pronouns. They admit that one metric is not enough to capture the bias as a whole as the gender bias is far more complex to quantify in terms of only the usage of pronouns in articles. Therefore, the author suggests more studies on the quest for more quantifiable and efficient metrics which may provide a better understanding of gender bias in Knowledge (XXG).

778:"As an example of gap, posts by women on talk pages are slightly less likely to receive a reply than posts by men. One of the only cues available to Knowledge (XXG) users for guessing the author of a talk page post’s gender is their username, i.e. their pseudonym on the platform. We therefore examined whether users with obviously female names receive fewer replies than users with obviously male names. Contrary to our expectations, we find that users with clearly female names are slightly more likely to receive a reply than users with clearly male names. We also find that the fraction of users with a female name is much lower than the fraction of female users, suggesting that, unlike men, women using Knowledge (XXG) do not include contain obvious gender markers in their usernames. This result is important for the Knowledge (XXG) community because it implies that we found no evidence of discrimination of female users based on their usernames, unlike what other studies have found in offline and online correspondences in male-dominated fields." 511:

such bias. Like other efforts to detect biases or their absence, their methodology still suffers from various limitations - e.g. the raters came only from the United States, leaving open the question whether a gender or racial bias could still exist in other countries. Also, of course, the population of Mechanical Turk workers may differ in some characteristics from that of the Knowledge (XXG) editors who review most Knowledge (XXG) contributions in real life. (However, among the various hypotheses offered by the authors as possible explanations for their results, they argue that "the familiarity of crowd workers with crowdwork incentives and work practices distinguishes them from the general population and makes them less likely to show race or gender-based bias when doing a rating task".) Still, the fact remains that the results of a series of statistically rigorous experiments were at odds with widespread assumptions often taken for granted in discussions about Knowledge (XXG)'s biases.

625:"... we investigate how quantification of Knowledge (XXG) biographies can shed light on worldwide longitudinal gender inequality trends, a macro-level dimension of human development. We present the Wikidata Human Gender Indicator (WHGI), located within a set of indicators allowing comparative study of gender inequality through space and time, the Knowledge (XXG) Gender Indicators (WIGI), based on metadata available through the Wikidata database. Our research confirms that gender inequality is a phenomenon with a long history, but whose patterns can be analyzed and quantified on a larger scale than previously thought possible. Through the use of Inglehart–Welzel cultural clusters, we show that gender inequality can be analyzed with regard to world’s cultures. We also show a steadily improving trend in the coverage of women and other genders in reference works." 450:

marginalization of traditionally excluded voices and histories" (p. 4). This re-examination of the initial editathon experiences, previously published, resulted in a broadened perspective of how a group of Knowledge (XXG) editors understood their roles as representing history, one that was not neutral and one whose voice had the power to fill historical gaps in knowledge. This led to an awareness of the gendered role of male-dominated discourse on the Internet, one which could be balanced with active participation within editing Knowledge (XXG) articles from more theoretically critical perspectives. As a result, personal learning journeys could have powerful implications for what is experientially learned through participating in editathons that include materials, technology, and social relations combined through Knowledge (XXG) engagement.

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sociologists, indicating that any coverage gaps (at least along the lines of gender) derive from different rates of article creation. The authors offer two potential explanations for these findings, which they describe as "supply" and "demand" side explanations respectively. On the supply side, Adams and colleagues argue that differential coverage patterns may reflect broader patterns of underrepresentation of women and people of color in the world. According to this perspective, Knowledge (XXG)'s gaps in coverage could derive, at least partly, from inequities that originate elsewhere. On the demand side, however, Adams and colleagues note that some portion of the coverage gaps also seem likely to derive from issues with gatekeeping and exclusionary behavior within the community. Specifically, they identify Knowledge (XXG)'s

571:"We illustrate the method by investigating how well the English language Knowledge (XXG) addresses the content interests of four sample audiences: readers of men’s and women’s periodicals , and readers of political periodicals geared toward either liberal or conservative ideologies ... We found that 73.8% of the randomly selected 400 keywords from conservative-oriented periodicals were covered, and 81.5% of the randomly selected 400 keywords from liberal-oriented periodicals were covered. This represents a 7.7% difference in topical coverage. ... We found that 67.6% of 'women's' topics and 84.1% of 'men’s' topics were covered. This represents a 16.5% difference in the topical coverage of Knowledge (XXG) as it is represented from periodicals targeted to a specific 'gendered' readership." 241:, reports evidence of race and gender-based coverage gaps, even among similarly accomplished faculty in terms of seniority, institutional status, publication count, and H-index. The authors analyze a sample of nearly 3,000 sociology faculty in elite ("R1") research universities in the United States in 2014. They then gather demographic, institutional affiliation, and citation data for all of these individuals and match the names of as many as they can to articles in the "living sociologists" category on English Knowledge (XXG) as of October 2016. In supplementary analysis, the authors also collect data on "articles for deletion" ( 680:"The theoretical discussion starts from two concepts of the literature about the public sphere to analyze the case of organized groups (WikiProject Women's History and WikiProject Feminism) that seek to use the collaborative encyclopedia as (a) a platform that produces public visibility and, consequently, (b) that supports online debate about politics producing an exchange of reasoning and consolidating social representations. Based on the analysis, it is evaluated the capacity of Knowledge (XXG) to configure itself as a communicational environment that establishes new methods of construction of social representations." 507:

from race and gender through a standardized image selection process"), and, for the former, also via a demographically valid first name. The Knowledge (XXG) rating task was added after "none of our first three studies found that participants showed race- or gender-based rating bias. To help understand these results, we sought advice and insight from a Gender Studies scholar. She suggested that the task of evaluating writing critique might be too abstract or unnatural", leading to the choice of Knowledge (XXG) content as a rating object instead.

446:, the first group of women who studied medicine at the university. They wanted to understand how this editathon, as an informal event, still constituted professional learning. Social network analysis of the 47 members of the editathon, with limited qualitative interviews of some of the participants, presented an evolving picture of how historical narratives can be constructed. Moving from consumers of information to producers of it, the researchers explored the participants' awareness of the non-neutral construction of knowledge. 667:"... the authors examine how Knowledge (XXG)’s generic regulations determine that women’s often experiential ethos is unwelcome on the site. Thus, women are often unable to construct knowledge on the 'breastfeeding' entry; their epistemological methods are ignored or banned by other contributors. This chapter also examines six breastfeeding-focused mommyblogs, proposing blogs as an alternative genre that welcomes women’s ethos. However, the authors also recognize that such blogs are not a perfect epistemological paradigm." 701:"Consistent with previous studies, we found a gender gap, with women making up only 38% and 15% of readers and editors, respectively, and with men editors being much more active. Our data suggest two salient explanations: 1) women readers more often lack confidence with respect to their knowledge and technical skills as compared to men, and 2) women's behaviors may be driven by personal motivations such as enjoyment and learning, rather than by 'leaving their mark' on the community, a concern more common among men." 612:"After reading the excellent analysis of AfD vs gender by Andrew Gray , where he writes about the articles that faced and survived the 'Article for Deletion' process, I couldn’t help but wonder what happened to the articles that were not kept, that is, where AfD was 'successful'. ... Of the (male+female) articles, 23% are about women, which almost exactly matches Andrew’s ratio of women in BLP (Biographies of Living People). That would indicate no significant gender bias in actually deleted articles." 198: 1483: 1435: 1325: 1284: 1217: 650:"Despite-or perhaps because of-the controversies the Knowledge (XXG) gender gap offers valuable lessons for understanding the problems of archival bias, not only in Knowledge (XXG) but in crowdsourced archives more generally.This special issue of NTIK argues that archival and activist theory provides a productive theoretical framework for critiquing such bias. The issue originates from a two-day event held in Copenhagen on March 8 and 9, 2015, on the topic of gender and Knowledge (XXG)" 472:

within the professions. Their findings include far more representation of male titles, images, and names on Knowledge (XXG) than would be expected from labor market statistics for the corresponding professions. As the methodology was computational, the authors did not seek to explain why this strong gender imbalance exists, yet they did propose this study as a useful starting point when raising the issue and seeking ways to address it through future writing and editing efforts.

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dismissive of a relationship between their gender identity and experience on-wiki). Menking et al. approach the gender gap not from the standpoint of skills or abilities but how a lack of safety within Knowledge (XXG) spaces for women creates barriers to participation. By interviewing experienced editors, they are able to not just identify issues, but also highlight coping strategies that these women have created to deal with issues of safety on Knowledge (XXG).

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strong right skew in the H-index distribution" (I don't get it, but okay) and throw a bunch of other factors into a regression analysis, they get the result that women are being cheated out of articles after all. I don't know. Seems like a lot of degrees of freedom here and discarding a simple test with what's probably the most objective merit-based measure available (the h-index) in favor of an opaque regression analysis isn't necessarily convincing.

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whether the word "he" occurs more in any article and vice versa. There is a firm motivation for this study: Knowledge (XXG) has become an important source of data for artificial intelligence and machine learning algorithms development. These data driven algorithms will badly suffer from stereotype reinforcements if the data source is at risk of biases. For investigation, the research scientists from

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including the other measures in the model nor transforming the H-index values (by calculating the natural logarithm of each value) undermines it in any way. Indeed, the regression results in Table 3 indicate that H-index is (as you seem to expect!) the measure most closely related with being the subject of an article (the odds-ratio is quite large and statistically significant). The analysis

1727:"departmental reputation" are awful ways to estimate whether someone merits a Knowledge (XXG) article. The best measure (though it is of course, like everything, imperfect) is the h-index. But instead of sticking to that, the authors decided to go with a complicated composite measurement instead – one that I'd say is a lot less accurate. In the end this is not a persuasive analysis. 120: 36: 140: 2038:: " also about the dangerous pleasures of outrage, what Roth called 'the ectasy of sanctimony'. Of course, we have to be aware of hate speech and embedded bias, they are problematic. But using your need to feel virtuous to tear others apart is also problematic". Too many of these studies start from a virtuous/sanctimonious premise. Good studies draw conclusions 100: 714:".. I reflect upon the problems connected with writing women in mathematics into Knowledge (XXG). I discuss some of the current projects and efforts aimed at increasing the visibility of women in mathematics on Knowledge (XXG). I present the rules for creating a biography on Knowledge (XXG) and relate my personal experiences in creating such articles." 503:(respectively). To manage the workload for our participants, we also ensured that each article was between 1,000 and 10,000 bytes of body text. We also made sure these pieces of writing did not look too similar to a Knowledge (XXG) article. We did so by scraping the body of these pages and removing all links (retaining the text) and styling." 740:" ... gender is a complex issue on Knowledge (XXG), which the realisation that articles on topics relevant to feminist and gender studies or others related to minorities rights movements may be more likely to be removed from Knowledge (XXG) (Carstensen, 2009) makes visible. To understand the background and reasons for this phenomenon, 150: 555:"Comparison of Knowledge (XXG) profiles of Fortune 1000 CEOs reveals that selection, source, and influence bias stemming from structural constraints on Knowledge (XXG) advantage women and disadvantage men. This finding suggests that information developed by open collaboration communities may contain unexpected forms of bias." 352:... the bias increases (that is worsens) as we change our corpus from general popular Knowledge (XXG) articles (captured by Lateral) to the 'Good' and 'Featured' articles captured by MetaMind. This further suggests that the editor process of an article to be 'Good' or 'Featured' introduces additional bias... 510:

The authors call their results "striking" in light of "previous work showing race and gender bias". They emphasize their "statistical confidence in the overall finding", which included an "absence check" using Bayesian methods that allowed them to place an upper bound on the size of the effect of any

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The result was then presented to raters (without mentioning Knowledge (XXG) as the source) alongside a prominent portrait of the purported author, with gender and race being conveyed through a portrait photo ("On the advice of an ethnic studies scholar, we sought to control for potential biases apart

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The lack of safety can lead women to choose to avoid certain spaces (e.g., editing articles that are particularly contentious). This clearly could have unfortunate consequences regarding the diversity of voices that contribute but also is a reminder to researchers to not interpret behavior on-wiki as

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Many of the women interviewed had found ways to cope with any lack of safety they felt on-wiki, but many of these strategies are not sanctioned. This highlights that though many women do stick around and edit, this continued participation does not necessarily indicate that the design and norms within

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I thought it would be best to reflect the wording of the paper, which never uses the word "citation impact", though I take your point that it can be used to refer to h-index. The paper says "academic rank, length of career, and notability measured with both H-index and departmental reputation" which

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Article titles: "Wikipedians' Knowledge and Moral Duties", "Neutrality in the Face of Reckless Hate : Knowledge (XXG) and GamerGate", "Biases We Live By", "Knowledge (XXG) and the Myth of Universality", "From Webcams to Knowledge (XXG): There Is An Art & Feminism Online Social Movement Happening

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That means the "Featured" category contains significantly less "Equal" or unbiased articles than "All" category. One reason suggested by the researchers is that unbiased articles tend to focus more on abstract ideas or technical topics, e.g., scientific developments or mathematical theorems, than on

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In the extended abstract, the authors Anwesha Chakraborty and Netha Hussain investigate what barriers occur for women editors to contribute to Knowledge (XXG), with a focus on Indian editors. In their ethnographic study, they interview 5 editors (4 female, 1 male editor), and identify challenges and

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This article is one of only a few studies published in an American Sociological Association affiliated journal that focuses on Knowledge (XXG) as an empirical context. It breaks new ground in the understanding of content coverage gaps on Knowledge (XXG) by focusing on a specific profession for which

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encompasses a persons entire professional trajectory whereas the measures used here only pertain to a specific moment in that career (plus its length) 3) it seems from the above discussion that the concerns about the interpretation of the result regarding the h-index have been resolved. (I do agree

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I regret making fun of the log operation, which really is fine. And regression analysis is fine too - though I stand by my criticism of "length of career" being a suitable indicator of notability. I'm developing a more nuanced take on this and the corresponding author has kindly promised to send me

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The paper closes with three provocations for design – noting that designers of online and offline spaces need to be intentional about 1) designing for safety, 2) creating tools that allow individuals to create safe spaces within these communities, and 3) not putting the burden of creating safety on

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Gosh, this is a boring subject in the context of Knowledge (XXG) because much of it actually has little to do with Knowledge (XXG) per se, despite the (often extremely small) samples using WP as a means to "prove" their hypotheses. This is particularly evident in the Indian survey mentioned, which

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But whatever, all of this is a side issue since you're quite right that there must be other factors. Indeed, the very data in the paper shows that if you went by H-index alone and used that 100% fairly to pick out sociologists to write articles about then (assuming the same number of articles) you

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This straightforward method doesn't give the result they were expecting – and indeed it might even suggest that more articles on male sociologists are what's needed if gender-blind notability fairness is the ideal. But fear not, once the authors use a "logged version of the H-index to adjust for a

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The authors explored the existence of gender bias on German Knowledge (XXG) through looking at articles about professions, exploring gender titles and images that were used. They used Google hits and labor market indicators to compare this information with how men or women are actually represented

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They highlight the importance of studying not just Knowledge (XXG) namespaces but all of the communication and spaces outside of Knowledge (XXG) that inform one's relationship with the rest of the community (IRC, edit-a-thons, conferences, mailing lists, etc.). This may be a less salient point for

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the distribution and organization of the topics among the articles. The study suggests some interesting facts. In musician- and music-related articles, for example, although there are less "she"-heavy articles (containing more "she” pronouns) than "he"-heavy ones (vice-versa), the editors use very

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This article is about addressing the issue of gender bias in Knowledge (XXG) from a quantitative perspective. It proposes a simple metric, known as "Gender Pronoun Gap", which is the ratio between the number of times the pronouns "he" and "she" are used in any given article. It investigates simply

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Thanks for the above WBG. So in terms of current safe spaces it refers to off-wiki online (fb, mainly) and offline (women-only edit-a-thons) areas. They moot the creation of an on-wiki women-only space, though they don't consider the fairly substantial issues with that (verification, reporting of

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It seems inaccurate to say there's a "composite measurement" being used in the regression or to suggest that including multiple measures in regression analysis is less valid than just considering one of the measures (H-index) alone. H-index is very much part of the regression analysis and neither

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The important sentence comes after that one: "Women’s estimated odds of having a Knowledge (XXG) page after taking into account differences in rank, length of career, and notability measured with H-index and departmental reputation are still 25 points lower than men’s." But "length of career" and

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The Knowledge (XXG) criteria for notability of academics include references to making a 'significant impact on the field' and being an 'elected member of a highly selective and prestigious scholarly society or association' or the 'highest-level elected or appointed administrative post at a major

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is actually a general umbrella term that includes the h-index and has the advantage of being easier to understand (also, it was still being used in the body of the review after your edit, so changing it only in the title seemed a bit pointless anyway), 2) "similar careers" seems overstating the

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In more detail, the researchers "sampled 100 Knowledge (XXG) articles from the Musician Biography Wiki-Project (a project focused on editing musician biographies in Knowledge (XXG)). we selected four ‘Stub’ class articles and four ‘Start’ class articles as our low and high-quality deliverables

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True for some of the studies, but the first study might make us question our views of NPROF, the third can lead us to embracing a more careful writing style with regard to how we talk about men and women and the fourth is a damning indictment of the toxicity of our behaviour around contentious

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Having now read the Adams et al. article more carefully I must note that my comments above make too much of the sentence "Examining only sociologists with Knowledge (XXG) pages, men’s median H-index (27) is higher than women’s (22)" and don't take their Table 2 into account. I think there's a

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The paper's literature review explored how user-generated content contains systemic and structural biases, and the implications of this for the representation of women on Knowledge (XXG), both as subjects and as contributors, helping to understand the dominant discourse along with "continued

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2019 paper "People Who Can Take It: How Women Wikipedians Negotiate and Navigate Safety" by Amanda Menking, Ingrid Erickson, and Wanda Pratt, the gender gap is examined through interviews with 25 experienced women editors on Knowledge (XXG) (purposefully including several women who were more

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The results indicate that female and nonwhite scholars are disproportionately less likely to have articles covering them than scholars of similar seniority, prestige, or citation impact who are male and/or white. The analysis finds no evidence of differential deletion across male and female

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and classifications of institutional status are limited in many ways, they provide clear empirical grounds upon which to compare scholars who may or may not have received coverage on Knowledge (XXG). The evidence points clearly to persistent and disproportionate inequities, suggesting that

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Therese F. Triump, Kimberly M. Henze: "Women and Knowledge (XXG). Diversifying Editors and Enhancing Content through Library Edit-a-Thons". In: Gender Issues and the Library: Case Studies of Innovative Programs and Resources, ed. Lura Sanborn, McFarland, 2017, ISBN 9781476630342,

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Good point. Conceivably, women might tend to work in subfields with lower citation averages. I've been thinking of possible explanations for the results here and there are so many possibilities. I've requested the data mentioned in footnotes 20-22 from the corresponding author.

765:"We analyze movie plots and posters for all movies released since 1970 ... We have extracted movies pages of all the Hindi movies released from 1970- present from Knowledge (XXG). We also employ deep image analytics to capture such bias in movie posters and previews." 423:

I highly encourage reading this paper in full though – I have only highlighted a few of the points contained within. Notably, it has a very well-written summary of the gender gap on Knowledge (XXG) and the vignettes are much much richer than my summarization can be.

1685:(later note – my initial comments here overlook table 2 in the Adams et al. article, see later comments) The first article reviewed has this sentence: "Examining only sociologists with Knowledge (XXG) pages, men’s median H-index (27) is higher than women’s (22)". 727:"The results confirm that information accuracy, stability, and validity are significantly related to users’ intentions to adopt information from Knowledge (XXG), but objectivity is not. Meanwhile, moderating role for gender on some of these effects is confirmed." 314:

The suggestions to increase the number of Indian women editors include in-person meetings for new and existing editors, sensitization to be a more inclusive, the outreach to mothers and simplifying the editor interface for people with lack of access to devices.

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Also note how our current article says "Female and nonwhite US sociologists less likely to have Knowledge (XXG) articles than scholars of similar citation impact" which is not at all the conclusion reached in that research paper. We'd better correct this.

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notes that the cultural issues mostly lie outside WP's ambit. One of the problems with being a major site on the internet is that WP becomes a mechanism for pursuit of agendas, regardless of its actual relevance to the overall issue. To paraphrase a

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The authors identify a set of barriers, particularly for Indian women editors, which they describe as “socio-cultural challenges which hinder participation of women not only from contributing to Knowledge (XXG) but also accessing the internet”.

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Among the motivations to contribute are to democratize the knowledge, share knowledge in the editors’ native language, increase the number of articles about India in the Wikiverse and bridging the gap between oral and written knowledge.

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We know that there is something different about the way male and female biographies created before ~2017 experience the deletion process, but we don’t have clear data to indicate exactly what is going on, and there are multiple potential

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academic institution,' There are gendered and racialized patterns and criteria already embedded in these judgments. Some of the highly prestigious academic societies overwhelmingly elect white men into their ranks for example ...

237:, Hannah Brückner, and Cambria Naslund analyze articles about contemporary U.S. sociologists on English Knowledge (XXG) to investigate whether demographic gaps in coverage exist. The paper, published in the open access journal 345:" by MetaMind (Merity, Xiong, Bradbury, & Socher, 2016), (b) 463,820 English Knowledge (XXG) articles with 20 or more daily page views from "The Unknown Perils of Mining Knowledge (XXG)" by Lateral (Wilson, 2017). 412:

heir decision not to edit has less to do with the content of the articles themselves and their skills and knowledge in relation to those topics, but rather to do with the culture of Knowledge (XXG) and their sense of

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Any data about h-index is highly skewed by the difference in fields and other factors. Even within sociology, there may be vast differences: an h-index of 27 may be exceptional in some areas and ordinary elsewhere.

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While the paper points to some evidence in support of both supply and demand perspectives, the authors conclude that some elements of both explanations seem likely and leave it to future work to disentangle them.

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There is no gender or race bias in readers' rating of the quality of Knowledge (XXG) article text (when led to believe its author is male/female/black/white). This is the result of an experimental study that had

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ratio of white men then Knowledge (XXG) actually had. So the idea that Knowledge (XXG) has a bias against writing articles on female sociologists is really not, in my view, supported by this dataset.

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at the University of California, San Diego used two Knowledge (XXG) corpora: (a) 25,951 articles verified as "Good" or "Featured" by editorial scrutiny on Knowledge (XXG), provided by "

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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,

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purely self-selection. It is a product of the environment too and, at least for women editors, might look much different if the spaces were perceived as being safer. From the paper:

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Special issue on gender gap and gender bias research: A roundup of many recent publications examining Wikpedia's gender gaps in participation and content, and their possible reasons

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individuals and their background. General audiences have a harder time reading these articles. This makes it less likely for these articles to be included in the "Featured" list.

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Anwesha Chakraborty and Netha Hussain: Mapping and Bridging the Gender Gap: An Ethnographic Study of Indian Wikipedians and Their Motivations to Contribute (extended abstract).

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Konieczny, Piotr; Klein, Maximilian (2018-12-01). "Gender gap through time and space: A journey through Knowledge (XXG) biographies via the Wikidata Human Gender Indicator".

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Knowledge (XXG) is dynamic, citing a learned article from 2009 in a current work is not useful to describe the current state of WIkipedia or the community. All the best:

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I reviewed the breastfeeding study and it really surprised me to find such a poorly done piece. My take on it was so similar to your thoughts that you might like to read

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saying, "Other websites are available". And as I keep saying, it isn't our job to change the world but rather to reflect it in all its contrasting beauty and ugliness. -

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Madaan, Nishtha; Mehta, Sameep; Agrawaal, Taneea S.; Malhotra, Vrinda; Aggarwal, Aditi; Saxena, Mayank (2017-10-11). "Analyzing Gender Stereotyping in Bollywood Movies".

245:) decisions impacting any matches they can identify from their sample. They compare coverage and deletion rates across categories of race, gender, and other variables. 387: 360:

The researchers also applied a topic modeling method, called "Latent Semantic Indexing" or LSI, to study which pronoun tends to be seen in which particular topics, by

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Zagovora, Olga; Flöck, Fabian; Wagner, Claudia (2017-06-12). ""(Weitergeleitet von Journalistin)": The Gendered Presentation of Professions on Knowledge (XXG)".

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Adams, Julia; Brückner, Hannah; Naslund, Cambria (2019-01-01). "Who Counts as a Notable Sociologist on Knowledge (XXG)? Gender, Race, and the "Professor Test"".

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I think is reasonably summarized as "career" and I don't see what is gained by a switch to "seniority, institutional status, publication count, and H-index".

499:), with the Knowledge (XXG) texts being one of four such examples. Student essays (submissions to the SAT) formed the basis of the other three experiments. 2222: 2217: 2212: 1827:

suggests that female and nonwhite U.S. Sociologists are less likely to be the subject of EN:WP articles. These interpretations are mutually compatible.

2064:) give some more detail on what they're suggesting with "internal safe spaces". As in, parts of the encyclopedia with very high civility requirements? 1965: 2207: 1028:

Thebault-Spieker, Jacob; Kluver, Daniel; Klein, Maximilian A.; Halfaker, Aaron; Hecht, Brent; Terveen, Loren; Konstan, Joseph A. (December 2017).

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could be a confounding factor here - there may well be many sociologists on the authors' list whose Knowledge (XXG) notability did not rest on

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Ford, Heather; Mai, Jens-Erik; Salor, Erinc; Søgaard, Anders; Adler, Melissa; Washko, Angela; Ping-Huang, Marianne; Ørum, Kristoffer (2016).

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We know the gender breakdown : skewed male, but growing slowly more balanced over time, and better for living people than historical ones.

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Menking, Amanda; Erickson, Ingrid; Pratt, Wanda (2019). "People Who Can Take It: How Women Wikipedians Negotiate and Navigate Safety".

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notability policy as one of "the factors that transmit existing inequalities into the encyclopedia and magnify them informationally":

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We know the article lengths; slightly longer for women than men for recent articles, about equal for those created a long time ago.

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Jun Huang; Si Shi; Yang Chen; Wing S. Chow (2016-09-27). "How do students trust Knowledge (XXG)? An examination across genders".

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those studying new editors but is an incredibly important to remember when considering the experiences of more long-term editors.

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it's an interesting observation that the differences in the median go the other way, if I understood that correctly, but as

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Alison M. Lukowski, Erika M. Sparby: Breastfeeding, Authority, and Genre: Women's Ethos in Knowledge (XXG) and Blogs. In:

752:). The described non-fictional incident was a part of my seven-year anthropological fieldwork project on Knowledge (XXG)." 617:"Gender gap through time and space: A journey through Knowledge (XXG) biographies via the Wikidata Human Gender Indicator" 1298: 219:

Female and nonwhite US sociologists less likely to have Knowledge (XXG) articles than scholars of similar citation impact

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A monthly overview of recent academic research about Knowledge (XXG) and other Wikimedia projects, also published as the

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topics. And there are plenty more interesting conclusions which are relevant to an editor's regular editing patterns. —

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The authors of this study focused on a 2015 editathon that occurred at the University of Edinburgh on the topic of the

288:"Mapping and Bridging the Gender Gap: An Ethnographic Study of Indian Wikipedians and Their Motivations to Contribute" 598:

We also know that deletion activity seems to be more balanced for articles in both groups created from ~2017 onwards

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relatively clear indicators of notability exist. While, as the authors point out, measures like citation count and

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points out, this might not undermine the overall result. In any case, log transforms are frequently used and even

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This month's edition focuses on recent research about Knowledge (XXG)'s gender gaps and potential gender biases.

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the idea that U.S. Sociologists with higher H-indices are more likely to be the subject of EN:WP articles. It

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English Knowledge (XXG) biased against conservative and female topics, at least when compared to US magazines

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Who Wants to Read This?: A Method for Measuring Topical Representativeness in User Generated Content Systems

1706:– If you don't understand the reasoning of the authors, how can you be so confident that they are wrong? — 1133: 1867: 1482: 1434: 1324: 1283: 1216: 492: 2138: 2113: 2069: 1966:

Wikipedia_talk:Notability_(academics)#Recent_study:_"Who_Counts_as_a_Notable_Sociologist_on_Wikipedia?"

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in the data. I'm going to think more about this and maybe see if I can get the data from the authors.

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and It Is Not Going Away", "Archival Biases and Cross-Sharing", "The Gift of Mutual Misunderstanding"

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misbehaviour, canvassing risks, as well as any disagreements on the fundamental nature of wikipedia)

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In "Who Counts as a Notable Sociologist on Knowledge (XXG)? Gender, Race, and the 'Professor Test'",

1521: 1339: 685:"Women and Knowledge (XXG). Diversifying Editors and Enhancing Content through Library Edit-a-Thons" 1832: 867: 1896: 770:

Contrary to expectations, "no evidence of discrimination of female users based on their usernames"

457:"'(Weitergeleitet von Journalistin)': The Gendered Presentation of Professions on Knowledge (XXG)" 1949: 1847: 1791: 1766: 1758: 1747: 1732: 1694: 1500: 1472: 1390: 1364: 1206: 1181: 1059: 1011: 976: 914: 850: 338: 1078:"It's Not What You Think: Gender Bias in Information about Fortune 1000 CEOs on Knowledge (XXG)" 204: 197: 103: 2130: 1659: 1465: 1424: 1266: 1243: 1199: 1113: 1052: 1002: 954: 905: 843: 123: 1900: 2156: 2134: 2109: 2080: 2065: 2047: 2012: 1994: 1714: 1686: 1457: 1416: 1382: 1191: 1105: 1044: 994: 944: 897: 835: 379: 348:

The study revealed that the articles contain biases towards "he" words. The authors write:

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Special issue of the "Nordic journal for information science and dissemination of culture"

443: 153: 1378: 1299:"Cyberfeminism on Knowledge (XXG): Visibility and deliberation in feminist Wikiprojects" 990: 672:"Cyberfeminism on Knowledge (XXG): Visibility and deliberation in feminist Wikiprojects" 476:"Striking result": No bias against contributions by female editors in quality assessment 1973: 1908: 1881: 1828: 933:"Hacking History: Redressing Gender Inequities on Knowledge (XXG) Through an Editathon" 676:

From the English abstract (paper is in Portuguese, but about English Knowledge (XXG)):

428:"Hacking History: Redressing Gender Inequities on Knowledge (XXG) Through an Editathon" 226: 167: 643: 2240: 1945: 1863: 1843: 1787: 1777: 1762: 1743: 1728: 1690: 1393: 1355:

Vitulli, Marie A. (2017-10-30). "Writing Women in Mathematics into Knowledge (XXG)".

917: 853: 693:"Similar Gaps, Different Origins? Women Readers and Editors at Greek Knowledge (XXG)" 295: 171: 1475: 1209: 1062: 1014: 802:"Female scientists' pages keep disappearing from Knowledge (XXG) – what's going on?" 1903:

but on media coverage or their authorship of (popular or academic) books. Regards,

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Similar Gaps, Different Origins? Women Readers and Editors at Greek Knowledge (XXG)

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Jemielniak, Dariusz (July 2016). "breaking the glass ceiling on Knowledge (XXG)".

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workers rate the quality of simulated "gig work" (as typical for platfoms such as

659:"Breastfeeding, Authority, and Genre: Women's Ethos in Knowledge (XXG) and Blogs" 2152: 2126: 2043: 2035: 2006: 1990: 1708: 1030:"Simulation Experiments on (the Absence of) Ratings Bias in Reputation Systems" 949: 932: 741: 113: 272:

initiatives to support more equitable coverage may be important correctives.

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Protonotarios, Ioannis; Sarimpei, Vasiliki; Otterbacher, Jahna (2016-04-16).

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Using Knowledge (XXG) for "Analyzing Gender Stereotyping in Bollywood Movies"

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I'll quote from comments by Terri Apter, psychologist and Fellow Emerita of

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Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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suggest solutions to the problem of the gender gap in the Indian editors.

1153: 547:"Unexpected forms of bias" on Knowledge (XXG) favor female over male CEOs 1520:

Ross, Björn; Dado, Marielle; Heisel, Maritta; Cabrera, Benjamin (2018).

268: 1461: 719:"How do students trust Knowledge (XXG)? An examination across genders" 1876: 1386: 981: 937:

The International Review of Research in Open and Distributed Learning

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Research on gender gap in Knowledge (XXG). What has been done so far?

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as standard practice for data that only takes on positive values.)

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Research on gender gap in Knowledge (XXG): What do we know so far?

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Establishing and Evaluating Digital Ethos and Online Credibility

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Nordisk Tidsskrift for Informationsvidenskab og Kulturformidling

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http://wikiworkshop.org/2018/papers/wikiworkshop2018_paper_5.pdf

54: 1986: 1344:. Tenth International AAAI Conference on Web and Social Media. 1561: 631: 34: 343:

The WikiText Long Term Dependency Language Modeling Dataset

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Menking, Amanda; McDonald, David W.; Zachry, Mark (2017).

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Knowledge (XXG) study cited as example of government waste

322:"Investigating the Gender Pronoun Gap in Knowledge (XXG)" 1675: 1668: 1648: 880:

Investigating the Gender Pronoun Gap in Knowledge (XXG)

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Young, Amber; Wigdor, Ari; Kane, Gerald (2016-12-11).

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I think a more interesting question might be whether

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Proceedings of the 2017 ACM on Web Science Conference

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Cuestiones de Género: De la Igualdad y la Diferencia

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Special issue on gender gap and gender bias research

1673:If your comment has not appeared here, you can try 1104:. CSCW '17. New York, NY, USA: ACM. pp. 2068–2081. 783:

Some informative non-research overview publications

706:"Writing Women in Mathematics into Knowledge (XXG)" 658: 394:A couple of excellent points made by this paper: 239:Socius: Sociological Research for a Dynamic World 1297:Matos, Eurico Oliveira; Acker, Isabel de Souza. 732:"Breaking the glass ceiling on Knowledge (XXG)" 410: 350: 276:See also related Signpost coverage from 2014: " 255: 1307:Nº. 12, 2017 – e-ISSN: 2444-0221 - pp. 365-384 931:Hood, Nina; Littlejohn, Allison (2018-11-27). 1522:"Gender Markers in Knowledge (XXG) Usernames" 8: 2062:Safety and women editors on Knowledge (XXG) 792:" (2017) / Netha Hussain, Reem Al-Kashif: " 372:Safety and women editors on Knowledge (XXG) 750:Knowledge (XXG) article on ‘Glass ceiling’ 2247:Knowledge (XXG) Signpost archives 2019-08 1504: 1368: 1185: 980: 948: 2060:Can someone with access to the 4th one ( 2042:the study, not before undertaking it. - 1261:Moe, Folk; Shawn, Apostel (2016-11-09). 1134:"Gender and deletion on Knowledge (XXG)" 583:From the conclusions of this blog post: 579:"Gender and deletion on Knowledge (XXG)" 18:Knowledge (XXG):Knowledge (XXG) Signpost 1676: 1652: 818: 403:Knowledge (XXG) are supportive of them. 70: 1703: 1862:Thanks all for the great discussion! 1232:"NTIK, Tema: Køn & Crowdsourcing" 29: 7: 419:those who are facing these barriers. 1409:Information Technology & People 748:related to a gender-related topic ( 744:present a fieldwork account of an 56: 28: 1658:These comments are automatically 1481: 1433: 1323: 1282: 1215: 796:" Presentation at Wikimania 2018 196: 148: 138: 128: 118: 108: 98: 88: 2197:: doing it for free since 2005. 1037:Proc. ACM Hum.-Comput. Interact 2181:21:57, 20 September 2019 (UTC) 2161:19:21, 12 September 2019 (UTC) 2143:15:21, 12 September 2019 (UTC) 2133:'s page where we discuss it. 2052:19:21, 12 September 2019 (UTC) 1978:19:00, 21 September 2019 (UTC) 1954:20:08, 21 September 2019 (UTC) 1913:19:00, 21 September 2019 (UTC) 1669:add the page to your watchlist 1: 2118:11:29, 3 September 2019 (UTC) 2103:11:19, 3 September 2019 (UTC) 2085:The file may be located over 2074:15:32, 2 September 2019 (UTC) 1875:results quite a bit, because 1852:16:43, 3 September 2019 (UTC) 1837:16:33, 3 September 2019 (UTC) 1796:08:36, 1 September 2019 (UTC) 1781:07:21, 1 September 2019 (UTC) 1152:Manske, Magnus (2019-05-08). 882:. WikiStudies, 1(1), 96-116. 800:Krämer, Katrina (July 2019). 774:From the abstract and paper: 761:From the abstract and paper: 567:From the abstract and paper: 205:Wikimedia Research Newsletter 2020:08:32, 31 August 2019 (UTC) 1999:03:22, 31 August 2019 (UTC) 1771:16:26, 31 August 2019 (UTC) 1752:09:39, 31 August 2019 (UTC) 1737:09:29, 31 August 2019 (UTC) 1722:08:32, 31 August 2019 (UTC) 1699:01:09, 31 August 2019 (UTC) 1132:Gray, Andrew (2019-05-06). 2263: 950:10.19173/irrodl.v19i5.3549 896:. ACM. pp. 472:1–472:14. 632:https://wigi.wmflabs.org/ 518:Other recent publications 1704:I don't get it, but okay 1421:10.1108/ITP-12-2014-0267 1196:10.1177/1461444818779080 840:10.1177/2378023118823946 1174:New Media & Society 1110:10.1145/2998181.2998254 999:10.1145/3091478.3091488 902:10.1145/3290605.3300702 1666:. To follow comments, 1566: 780: 767: 754: 729: 716: 703: 682: 669: 652: 627: 614: 601: 573: 557: 415: 354: 260: 39: 1565: 1154:"Deleted gender wars" 1082:ICIS 2016 Proceedings 776: 763: 738: 725: 712: 699: 678: 665: 648: 623: 610: 604:"Deleted gender wars" 585: 569: 553: 38: 1964:Related discussion: 1662:from this article's 878:Yazdani, M. (2017). 834:: 2378023118823946. 608:From the blog post: 330:Khandaker Tasnim Huq 164:Khandaker Tasnim Huq 2151:Will do, thanks. - 1886:recommended by some 1554:"Recent research" → 1379:2017arXiv171011103V 991:2017arXiv170603848Z 723:From the abstract: 710:From the abstract: 697:From the abstract: 663:From the abstract: 621:From the abstract: 551:From the abstract: 2028:, in her notes on 1653:Discuss this story 1638:On the bright side 1567: 1357:Notices of the AMS 1043:(CSCW): 101:1–25. 975:. 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