Welcome to WikiProject Conservatism! Whether you're a newcomer or regular, you'll receive encouragement and recognition for your achievements with conservatism-related articles. This project does not extol any point of view, political or otherwise, other than that of a neutral documentarian.
Partly due to this, the project's scope has long become that of conservatism broadly construed, taking in a healthy periphery of (e.g., more academic) articles for contextualization.
diffhistDepartment of Government Efficiency04:38+1,115Soibanglatalkcontribs(Musk asserts all DOGE actions are "maximally transparent," though its X account often posts false or misleading information and its website is blank; Trump granted DOGE an exemption from public disclosure of its activities)
diffhistDepartment of Government Efficiency03:38−138ByVaryingtalkcontribs(The vast majority of RS refer to "Elon Musk's Department [etc.]," very often refer to actions of Musk not DOGE, and do not emphasize (let alone predict) its future persistence as an actual agency of the US govt. Therefore neither should we, and Musk's role should be brought up in the first sentence.)
diffhistDepartment of Government Efficiency02:32−46ByVaryingtalkcontribs(It's not accurate based on the sources given that "DOGE" is slated to operate for 18 months. Rather, there is an organization within "DOGE" of, thus far, unknown significance, which will.)Tags: RevertedMobile editMobile web editAdvanced mobile edit
diffhistDonald Trump02:29+1LJF2019talkcontribs(This portrait was not produced by the White House, it was produced by Trump's inauguration team. There will be another portrait released in the coming months.)
diffhistDepartment of Government Efficiency01:55+504Soibanglatalkcontribs(→top: Twenty-four days after DOGE began, The New York Times reported Trump had claimed he and Musk had found "billions and billions of dollars" in corrupt spending, though they had not provided evidence.)
diffhistElon Musk13:21−45SNUGGUMStalkcontribs(If you aren't going to fill fields with text that can actually be seen outside of edit mode, then don't bother adding to infobox)
diffhistDepartment of Government Efficiency09:02+1,490AnomieBOTtalkcontribs(Rescuing orphaned refs ("Severi" from rev 1275315166; "Elliott" from rev 1275314691; "ap-hb-25-krause" from rev 1275314691; "nyt-doge-krause-25" from rev 1275314691; "Talking Points" from rev 1275314691))
diffhistDepartment of Government Efficiency05:36+13Alphiustalkcontribs(Corrected pronunciation (not sure where the other one came from; this is the one used by Musk himself and multiple news organizations, though a citation could possibly be added))
diffhistZionism10:51−671DancingOwltalkcontribs(→Hebraization of names: the truncated quote is taken from Dayan's speech where he talks about necessity of co-existence between Arabs and Jews and Hebraization of *some* of the names is only mentioned in passing, so its seems to be less relevant in this specific context)
diffhistVictor Davis Hanson08:47−1,260Hob Gadlingtalkcontribs(→Race relations: stilted, Rube-Goldberg-ish, editorializing wording: "Arthur Stern, writing, called something something, stating Stern's opinion that x"? Better before: "Stern called something something and wrote x")
diffhistVictor Davis Hanson07:45+1,23698.226.86.66talk(→Race relations: Slightly upgraded one writer description, for Kelefa Sanneh who has written for the NYT, and downgraded another, Arthur Stern, for whom we could find no support for his description as a "journalist". Moved Sanneh statement, which also elicited a Hanson response, to appear before the ostensibly less impactful and important Stern statement.)
diffhistVictor Davis Hanson06:25+22898.226.86.66talk(→Writing: Noting for the introductory section of the Writing section and beyond, that sentence by sentence, the multiple paragraphs constitute a personal essay on the central messages of a series of Hanson's books, and in the serial presentation of "this book... says..." sentences, SOURCES ACCOMPANY LESS THAN ONE IN THREE SUMMARIES OF THE BOOKS. That is, this is more than half WP:OR, and violates WP:VERIFY.)Tag: possible unreferenced addition to BLP
diffhistPete Hegseth05:41−1,847ElijahPepetalkcontribs(Temporal issues in the "Political positions" section; present perfect is preferred here. I removed the sentence about Hegseth being far-right, as The Guardian is the only publication that occasionally refers to him as such. The "evil regime" comment could not be supported in either reference. Yellow-tagged references at WP:RSP have been replaced.)
diffhistDepartment of Government Efficiency04:38+1,115Soibanglatalkcontribs(Musk asserts all DOGE actions are "maximally transparent," though its X account often posts false or misleading information and its website is blank; Trump granted DOGE an exemption from public disclosure of its activities)
diffhistPete Hegseth04:15+7,627BootsEDtalkcontribs(Updated and expanded political positions section with several references from child Political positions of Pete Hegseth article in a more condensed, summary style.)Tags: harv-errorDisambiguation links added
diffhistDepartment of Government Efficiency03:38−138ByVaryingtalkcontribs(The vast majority of RS refer to "Elon Musk's Department [etc.]," very often refer to actions of Musk not DOGE, and do not emphasize (let alone predict) its future persistence as an actual agency of the US govt. Therefore neither should we, and Musk's role should be brought up in the first sentence.)
diffhistNancy Mace03:27+5,641Kizortalkcontribs(+her statement on Gaza. +references re: the ethnic cleansing. Bit of a chonker, but them's the breaks. According to the source Trump said he'd only send in troops "if necessary", so tweaked that bit accordingly.)Tag: Reverted
diffhistDepartment of Government Efficiency02:32−46ByVaryingtalkcontribs(It's not accurate based on the sources given that "DOGE" is slated to operate for 18 months. Rather, there is an organization within "DOGE" of, thus far, unknown significance, which will.)Tags: RevertedMobile editMobile web editAdvanced mobile edit
diffhistJD Vance02:29+1LJF2019talkcontribs(This portrait was not produced by the White House, it was produced by Trump's inauguration team. There will be another portrait released in the coming months.)Tags: Manual revertReverted
diffhistDonald Trump02:29+1LJF2019talkcontribs(This portrait was not produced by the White House, it was produced by Trump's inauguration team. There will be another portrait released in the coming months.)
diffhistVictor Davis Hanson01:56+1398.226.86.66talk(After review of the biographical material appearing, it is clear that most derives from the title subject's own self-descriptive contributions. As this WP article is substantially autobiography, the {{third party}} tag is placed to warn readers until the article becomes substantially WP:VERIFY compliant.)
diffhistDepartment of Government Efficiency01:55+504Soibanglatalkcontribs(→top: Twenty-four days after DOGE began, The New York Times reported Trump had claimed he and Musk had found "billions and billions of dollars" in corrupt spending, though they had not provided evidence.)
diffhistUnitary executive theory01:36+129Superb Owltalkcontribs(Updating the lead to remove 1 weasel word, flag another and move a specific quote that discusses the vesting clause to the vesting clause section (already mentioned that the Supreme Court has shown increasing support in the above paragraph - this seems like redundant and overly detailed sentence for the lead section))Tag: Visual edit
diffhistVictor Davis Hanson01:29+1,13298.226.86.66talk(→Works: Created a Further reading section for independent, third-party sources not yet utilised fully to contribute to the independent scholarship on the title subject.)
diffhistVictor Davis Hanson01:25+1,59598.226.86.66talk(→Academic career: 1985–2004: Sorry to split this edit, but we were slow to realize how poorly sourced the rest of this paragraph would be. Adding {{cn}} tags so we comply with WP:VERIFY for the host of non-sky-is-blue purported facts appearing.)
diffhistPete Hegseth21:10−3,857ElijahPepetalkcontribs(Restore previous section with content from the old article; I have gone through and made sure that no detail from the previous revision was removed. There is a purpose in merging these three events together, as they are both allegations that the reader is looking for and are previously linked in the article.)Tag: harv-error
diffhist m Reform UK15:26+47Charliepheretalkcontribs(WP:EW Undid revision once again removing something that has been in the article for ages that I have added back, and that left a rude message as if this was a new addition I've brought in.)Tags: UndoReverted
diffhistStrom Thurmond14:16+3898.175.89.51talk(Added category American anti-communists as the article indicateshe was critical of the Communist government of China and warned of military strength of the Soviet Union and other Communist countries,)
diffhistElon Musk13:21−45SNUGGUMStalkcontribs(If you aren't going to fill fields with text that can actually be seen outside of edit mode, then don't bother adding to infobox)
diffhistThe American Spectator00:07−292a02:c7c:ee9b:b100:a127:d870:fa05:3463talk(I changed 'what it's supporters think is the consensus on global warming' to 'the consensus on global warming', considering the widespread acceptance of the consensus. I also considering changing global warming to climate change but wasn't sure whether to do this or not.)Tags: Mobile editMobile web edit
diffhistVictor Davis Hanson08:47−1,260Hob Gadlingtalkcontribs(→Race relations: stilted, Rube-Goldberg-ish, editorializing wording: "Arthur Stern, writing, called something something, stating Stern's opinion that x"? Better before: "Stern called something something and wrote x")
diffhistVictor Davis Hanson07:45+1,23698.226.86.66talk(→Race relations: Slightly upgraded one writer description, for Kelefa Sanneh who has written for the NYT, and downgraded another, Arthur Stern, for whom we could find no support for his description as a "journalist". Moved Sanneh statement, which also elicited a Hanson response, to appear before the ostensibly less impactful and important Stern statement.)
diffhistVictor Davis Hanson06:25+22898.226.86.66talk(→Writing: Noting for the introductory section of the Writing section and beyond, that sentence by sentence, the multiple paragraphs constitute a personal essay on the central messages of a series of Hanson's books, and in the serial presentation of "this book... says..." sentences, SOURCES ACCOMPANY LESS THAN ONE IN THREE SUMMARIES OF THE BOOKS. That is, this is more than half WP:OR, and violates WP:VERIFY.)Tag: possible unreferenced addition to BLP
diffhistVictor Davis Hanson01:56+1398.226.86.66talk(After review of the biographical material appearing, it is clear that most derives from the title subject's own self-descriptive contributions. As this WP article is substantially autobiography, the {{third party}} tag is placed to warn readers until the article becomes substantially WP:VERIFY compliant.)
diffhistVictor Davis Hanson01:29+1,13298.226.86.66talk(→Works: Created a Further reading section for independent, third-party sources not yet utilised fully to contribute to the independent scholarship on the title subject.)
diffhistVictor Davis Hanson01:25+1,59598.226.86.66talk(→Academic career: 1985–2004: Sorry to split this edit, but we were slow to realize how poorly sourced the rest of this paragraph would be. Adding {{cn}} tags so we comply with WP:VERIFY for the host of non-sky-is-blue purported facts appearing.)
A list of semi-related articles that were recently created
This list was generated from these rules. Questions and feedback are always welcome! The search is being run daily with the most recent ~14 days of results. Note: Some articles may not be relevant to this project.
WikiProject Conservatism was a topic of discussion at the Administrators' Noticeboard/Incident (AN/I). Objective3000 started a thread where he expressed concern regarding the number of RFC notices posted on the Discussion page suggesting that such notices "could result in swaying consensus by selective notification." Several editors participated in the relatively abbreviated six hour discussion. The assertion that the project is a "club for conservatives" was countered by editors listing examples of users who "profess no political persuasion." It was also noted that notification of WikiProjects regarding ongoing discussions is explicitly permitted by the WP:Canvassing guideline.
At one point the discussion segued to feedback about The Right Stuff. Member SPECIFICO wrote: "One thing I enjoy about the Conservatism Project is the handy newsletter that members receive on our talk pages." Atsme praised the newsletter as "first-class entertainment...BIGLY...first-class...nothing even comes close...it's amazing." Some good-natured sarcasm was offered with Objective3000 observing, "Well, they got the color right" and MrX's followup, "Wow. Yellow is the new red."
Admin Oshwah closed the thread with the result "definitely not an issue for ANI" and directing editors to the project Discussion page for any further discussion.
Editor's note: originally the design and color of The Right Stuff was chosen to mimic an old, paper newspaper.
Margaret Thatcher is the first article promoted at the new WikiProject Conservatism A-Class review. Congratulations to Neveselbert. A-Class is a quality rating which is ranked higher than GA (Good article) but the criteria are not as rigorous as FA (Featued article). WikiProject Conservatism is one of only two WikiProjects offering A-Class review, the other being WikiProject Military History. Nominate your article here. (Discuss this story)
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Out of over one hundred questioned editors, only twenty-seven (27%) are happy with the way reports of conflicts between editors are handled on the Administrators' Incident Noticeboard (AN/I), according to a recent survey . The survey also found that dissatisfaction has varied reasons including "defensive cliques" and biased administrators as well as fear of a "boomerang effect" due to a lacking rule for scope on AN/I reports. The survey also included an analysis of available quantitative data about AN/I. Some notable takeaways:
53% avoided making a report due to fearing it would not be handled appropriately
"Otherwise 'popular' users often avoid heavy sanctions for issues that would get new editors banned."
"Discussions need to be clerked to keep them from raising more problems than they solve."
In the wake of Zarasophos' article editors discussed the AN/I survey at The Signpost and also at AN/I. Ironically a portion of the AN/I thread was hatted due to "off-topic sniping." To follow-up the problems identified by the research project the Wikimedia Foundation Anti-Harassment Tools team and Support and Safety team initiated a discussion. You can express your thoughts and ideas here.
A monthly overview of recent academic research about Wikipedia and other Wikimedia projects, also published as the Wikimedia Research Newsletter.
Report by conservative think-tank presents ample quantitative evidence for "mild to moderate" "left-leaning bias" on Wikipedia
A paper titled "Is Wikipedia Politically Biased?"[1] answers that question with a qualified yes:
[...] this report measures the sentiment and emotion with which political terms are used in [English] Wikipedia articles, finding that Wikipedia entries are more likely to attach negative sentiment to terms associated with a right-leaning political orientation than to left-leaning terms. Moreover, terms that suggest a right-wing political stance are more frequently connected with emotions of anger and disgust than those that suggest a left-wing stance. Conversely, terms associated with left-leaning ideology are more frequently linked with the emotion of joy than are right-leaning terms.
Our findings suggest that Wikipedia is not entirely living up to its neutral point of view policy, which aims to ensure that content is presented in an unbiased and balanced manner.
The author (David Rozado, an associate professor at Otago Polytechnic) has published ample peer-reviewed research on related matters before, some of which was featured e.g. in The Guardian and The New York Times. In contrast, the present report is not peer-reviewed and was not posted in an academic venue, unlike most research we cover here usually. Rather, it was published (and possibly commissioned) by the Manhattan Institute, a conservative US think tank, which presumably found its results not too objectionable. (Also, some – broken – URLs in the PDF suggest that Manhattan Institute staff members were involved in the writing of the paper.) Still, the report indicates an effort to adhere to various standards of academic research publications, including some fairly detailed descriptions of the methods and data used. It is worth taking it more seriously than, for example, another recent report that alleged a different form of political bias on Wikipedia, which had likewise been commissioned by an advocacy organization and authored by an academic researcher, but was met with severe criticism by the Wikimedia Foundation (who called it out for "unsubstantiated claims of bias") and volunteer editors (see prior Signpost coverage).
That isn't to say that there can't be some questions about the validity of Rozado's results, and in particular about how to interpret them. But let's first go through the paper's methods and data sources in more detail.
Determining the sentiment and emotion in Wikipedia's coverage
The report's main results regarding Wikipedia are obtained as follows:
"We first gather a set of target terms (N=1,628) with political connotations (e.g., names of recent U.S. presidents, U.S. congressmembers, U.S. Supreme Court justices, or prime ministers of Western countries) from external sources. We then identify all mentions in English-language Wikipedia articles of those terms.
We then extract the paragraphs in which those terms occur to provide the context in which the target terms are used and feed a random sample of those text snippets to an LLM (OpenAI’s gpt-3.5-turbo), which annotates the sentiment/emotion with which the target term is used in the snippet. To our knowledge, this is the first analysis of political bias in Wikipedia content using modern LLMs for annotation of sentiment/emotion."
The sentiment classification rates the mention of a terms as negative, neutral or positive. (For the purpose of forming averages this is converted into a quantitative scale from -1 to +1.) See the end of this review for some concrete examples from the paper's published dataset.
The emotion classification uses "Ekman’s six basic emotions (anger, disgust, fear, joy, sadness, and surprise) plus neutral."
The annotation method used appears to be an effort to avoid the shortcomings of popular existing sentiment analysis techniques, which often only rate the overall emotional stance of a given text overall without determining whether it actually applies to a specific entity mentioned in it (or in some cases even fail to handle negations, e.g. by classifying "I am not happy" as a positive emotion). Rozado justifies the "decision to use automated annotation" (which presumably rendered considerable cost savings, also by resorting to OpenAI's older GPT 3.5 model rather than the more powerful but more expensive GPT-4 API released in March 2023) citing "recent evidence showing how top-of-the-rank LLMs outperform crowd workers for text-annotation tasks such as stance detection." This is indeed becoming a more widely used choice for text classification. But Rozado appears to have skipped the usual step of evaluating the accuracy of this automated method (and possibly improving the prompts it used) against a gold standard sample from (human) expert raters.
Selecting topics to examine for bias
As for the selection of terms whose Wikipedia coverage to annotate with this classifier, Rozado does a lot of due diligence to avoid cherry-picking: "To reduce the degrees of freedom of our analysis, we mostly use external sources of terms [including Wikipedia itself, e.g. its list of members of the 11th US Congress] to conceptualize a political category into left- and right-leaning terms, as well as to choose the set of terms to include in each category." This addresses an important source of researcher bias.
Overall, the study arrives at 12 different groups of such terms:
8 of these refer to people (e.g. US presidents, US senators, UK members of parliament, US journalists).
Two are about organizations (US think tanks and media organizations).
The other two groups contain "Terms that describe political orientation", i.e. expressions that carry a left-leaning or right-leaning meaning themselves:
18 "political leanings" (where "Rightists" receives the lowest average sentiment and "Left winger" the highest), and
21 "extreme political ideologies" (where "Ultraconservative" scores lowest and "radical-left" has the highest – but still slightly negative – average sentiment)
What is "left-leaning" and "right-leaning"?
As discussed, Rozado's methods for generating these lists of people and organizations seem reasonably transparent and objective. It gets a bit murkier when it comes to splitting them into "left-leaning" and "right-leaning", where the chosen methods remain unclear and/or questionable in some cases. Of course there is a natural choice available for US Congress members, where the confines of the US two-party system mean that the left-right spectrum can be easily mapped easily to Democrats vs. Republicans (disregarding a small number of independents or libertarians).
But for example the
list of UK MPs used contains politicians from 14 different parties (plus independents). Even if one were to confine the left vs. right labels to the two largest groups in the UK House of Commons (Tories vs. Labour and Co-operative Party, which appears to have been the author's choice judging from Figure 5), the presence of a substantial number of parliamentarians from other parties to the left or right of those would make the validity of this binary score more questionable than in the US case. Rozado appears to acknowledge a related potential issue in a side remark when trying to offer an explanation for one of the paper's negative results (no bias) in this case: "The disparity of sentiment associations in Wikipedia articles between U.S. Congressmembers and U.K. MPs based on their political affiliation may be due in part to the higher level of polarization in the U.S. compared to the U.K."
Most negative sentiment among Western leaders: Former Australian PM Tony Abbott
Most positive sentiment among Western leaders: Former Australian PM Scott Morrison
This kind of question become even more complicated for the "Leaders of Western Countries" list (where Tony Abbott scored the most negative average sentiment, and José Luis Rodríguez Zapatero and Scott Morrison appear to be in a tie for the most positive average sentiment). Most of these countries do not have a two-party system either. Sure, their leaders usually (like in the UK case) hail from one of the two largest parties, one of which is more to the left and the another more to the right. But it certainly seems to matter for the purpose of Rozado's research question whether that major party is more moderate (center-left or center-right, with other parties between it and the far left or far right) or more radical (i.e. extending all the way to the far-left or far-right spectrum of elected politicians).
What's more, the analysis for this last group compares political orientations across multiple countries. Which brings us to a problem that Wikipedia's Jimmy Wales had already pointed to back in 2006 in response a conservative US blogger who had argued that there was "a liberal bias in many hot-button topic entries" on English Wikipedia:
"The Wikipedia community is very diverse, from liberal to conservative to libertarian and beyond. If averages mattered, and due to the nature of the wiki software (no voting) they almost certainly don't, I would say that the Wikipedia community is slightly more liberal than the U.S. population on average, because we are global and the international community of English speakers is slightly more liberal than the U.S. population. ... The idea that neutrality can only be achieved if we have some exact demographic matchup to [the] United States of America is preposterous."
We already discussed this issue in our earlier reviews of a notable series of papers by Greenstein and Zhu (see e.g.: "Language analysis finds Wikipedia's political bias moving from left to right", 2012), which had relied on a US-centric method of defining left-leaning and right-leaning (namely, a corpus derived from the US Congressional Record). Those studies form a large part of what Rozado cites as "[a] substantial body of literature [that]—albeit with some exceptions—has highlighted a perceived bias in Wikipedia content in favor of left-leaning perspectives." (The cited exception is a paper[2] that had found "a small to medium size coverage bias against [members of parliament] from the center-left parties in Germany and in France", and identified patterns of "partisan contributions" as a plausible cause.)
Similarly, 8 out of the 10 groups of people and organizations analyzed in Rozado's study are from the US (the two exceptions being the aforementioned lists of UK MPs and leaders of Western countries).
In other words, one potential reason for the disparities found by Rozado might simply be that he is measuring an international encyclopedia with a (largely) national yardstick of fairness. This shouldn't let us dismiss his findings too easily. But it is a bit disappointing that this possibility is nowhere addressed in the paper, even though Rozado diligently discusses some other potential limitations of the results. E.g. he notes that "some research has suggested that conservatives themselves are more prone to negative emotions and more sensitive to threats than liberals", but points out that the general validity of those research results remains doubtful.
Another limitation is that a simple binary left vs. right classification might be hiding factors that can shed further light on bias findings. Even in the US with its two-party system, political scientists and analysts have long moved to less simplistic measures of political orientations. A widely used one is the NOMINATE method which assigns members of the US Congress continuous scores based on their detailed voting record, one of which corresponds to the left-right spectrum as traditionally understood. One finding based on that measure that seems relevant in context of the present study is the (widely discussed but itself controversial) asymmetric polarization thesis, which argues that "Polarization among U.S. legislators is asymmetric, as it has primarily been driven by a substantial rightward shift among congressional Republicans since the 1970s, alongside a much smaller leftward shift among congressional Democrats" (as summarized in the linked Wikipedia article). If, for example, higher polarization was associated with negative sentiments, this could be a potential explanation for Rozado's results. Again, this has to remain speculative, but it seems another notable omission in the paper's discussion of limitations.
What does "bias" mean here?
A fundamental problem of this study, which, to be fair, it shares with much fairness and bias research (in particular on Wikipedia's gender gap, where many studies similarly focus on binary comparisons that are likely to successfully appeal to an intuitive sense of fairness) consists of justifying its answers to the following two basic questions:
What would be a perfectly fair baseline, a result that makes us confident to call Wikipedia unbiased?
If there are deviations from that baseline (often labeled disparities, gaps or biases), what are the reasons for that – can we confidently assume they were caused by Wikipedia itself (e.g. demographic imbalances in Wikipedia's editorship), or are they more plausibly attributed to external factors?
Regarding 1 (defining a baseline of unbiasedness), Rozado simply assumes that this should imply statistically indistinguishable levels of average sentiment between left and right-leaning terms. However, as cautionedby one leading scholar on quantitative measures of bias, "the 'one true fairness definition' is a wild goose chase" – there are often multiple different definitions available that can all be justified on ethical grounds, and are often contradictory. Above, we already alluded to two potentially diverging notions of political unbiasedness for Wikipedia (using an international instead of US metric for left vs right leaning, and taking into account polarization levels for politicians).
But yet another question, highly relevant for Wikipedians interested in addressing the potential problems reported in this paper, is how much its definition lines up with Wikipedia's own definition of neutrality. Rozado clearly thinks that it does:
Wikipedia’s neutral point of view (NPOV) policy aims for articles in Wikipedia to be
written in an impartial and unbiased tone. Our results suggest that Wikipedia’s NPOV
policy is not achieving its stated goal of political-viewpoint neutrality in Wikipedia articles.
WP:NPOV indeed calls for avoiding subjective language and expressing judgments and opinions in Wikipedia's own voice, and Rozado's findings about the presence of non-neutral sentiments and emotions in Wikipedia articles are of some concern in that regard. However, that is not the core definition of NPOV. Rather, it refers to "representing fairly, proportionately, and, as far as possible, without editorial bias, all the significant views that have been published by reliable sources on a topic." What if the coverage of the terms examined by Rozado (politicians, etc.) in those reliable sources, in their aggregate, were also biased in the sense of Rozado's definition? US progressives might be inclined to invoke the snarky dictum "reality has a liberal bias" by comedian Stephen Colbert. Of course, conservatives might object that Wikipedia's definition of reliable sources (having "a reputation for fact-checking and accuracy") is itself biased, or applied in a biased way by Wikipedians. For some of these conservatives (at least those that are not also conservative feminists) it may be instructive to compare examinations of Wikipedia's gender gaps, which frequently focus on specific groups of notable people like in Rozado's study. And like him, they often implicitly assume a baseline of unbiasedness that implies perfect symmetry in Wikipedia's coverage – i.e. the absence of gaps or disparities. Wikipedians often object that this is in tension with the aforementioned requirement to reflect coverage in reliable sources. For example,
Wikipedia's list of Fields medalists (the "Nobel prize of Mathematics") is 97% male – not because of Wikipedia editors' biases against women, but because of a severe gender imbalance in the field of mathematics that is only changing slowly, i.e. factors outside Wikipedia's influence.
All this brings us to question 2. above (causality). While Rozado uses carefully couched language in this regard ("suggests" etc, e.g. "These trends constitute suggestive evidence of political bias embedded in Wikipedia articles"), such qualifications are unsurprisingly absent in much of the media coverage of this study (see also this issue's In the media). For example, the conservative magazine The American Spectator titled its article about the paper "Now We've Got Proof that Wikipedia is Biased."
Commendably, the paper is accompanied by a published dataset, consisting of the analyzed Wikipedia text snippets together with the mentioned term and the sentiment or emotion identified by the automated annotation. For illustration, below are the sentiment ratings for mentions of the Yankee Institute for Public Policy (the last term in the dataset, as a non-cherry-picked example), with the term bolded:
Dataset excerpt: Wikipedia paragraphs with sentiment for "Yankee Institute for Public Policy"
positive
"Carol Platt Liebau is president of the Yankee Institute for Public Policy.Liebau named new president of Yankee Institute She is also an attorney, political analyst, and conservative commentator. Her book Prude: How the Sex-Obsessed Culture Damages Girls (and America, Too!) was published in 2007."
neutral
"Affiliates
Regular members are described as ""full-service think tanks"" operating independently within their respective states.
Alabama: Alabama Policy Institute
Alaska: Alaska Policy Forum
[...]
Connecticut: Yankee Institute for Public Policy
[...]
Wisconsin: MacIver Institute for Public Policy, Badger Institute, Wisconsin Institute for Law and Liberty, Institute for Reforming Government
Wyoming: Wyoming Liberty Group"
positive
"The Yankee Institute for Public Policy is a free market, limited government American think tank based in Hartford, Connecticut, that researches Connecticut public policy questions. Organized as a 501(c)(3), the group's stated mission is to ""develop and advocate for free market, limited government public policy solutions in Connecticut."" Yankee was founded in 1984 by Bernard Zimmern, a French entrepreneur who was living in Norwalk, Connecticut, and Professor Gerald Gunderson of Trinity College. The organization is a member of the State Policy Network."
neutral
"He is formerly Chairman of the Yankee Institute for Public Policy. On November 3, 2015, he was elected First Selectman in his hometown of Stonington, Connecticut, which he once represented in Congress. He defeated the incumbent, George Crouse. Simmons did not seek reelection in 2019."
negative
"In Connecticut the union is closely identified with liberal Democratic politicians such as Governor Dannel Malloy and has clashed frequently with fiscally conservative Republicans such as former Governor John G. Rowland as well as the Yankee Institute for Public Policy, a free-market think tank."
positive
"In 2021, after leaving elective office, she was named a Board Director of several organizations. One is the Center for Workforce Inclusion, a national nonprofit in Washington, DC, that works to provide meaningful employment opportunities for older individuals. Another is the William F. Buckley Program at Yale, which aims to promote intellectual diversity, expand political discourse on campus, and expose students to often-unvoiced views at Yale University. She also serves on the Board of the Helicon Foundation, which explores chamber music in its historical context by presenting and producing period performances, including an annual subscription series of four Symposiums in New York featuring both performance and discussion of chamber music. She is also a Board Director of the American Hospital of Paris Foundation, which provides funding support for the operations of the American Hospital of Paris and functions as the link between the Hospital and the United States, funding many collaborative and exchange programs with New York-Presbyterian Hospital. She is also a Fellow of the Yankee Institute for Public Policy, a research and citizen education organization that focuses on free markets and limited government, as well as issues of transparency and good governance."
positive
"He was later elected chairman of the New Hampshire Republican State Committee, a position he held from 2007 to 2008. When he was elected he was 34 years old, making him the youngest state party chairman in the history of the United States at the time. His term as chairman included the 2008 New Hampshire primary, the first primary in the 2008 United States presidential election. He later served as the executive director of the Yankee Institute for Public Policy for five years, beginning in 2009. He is the author of a book about the New Hampshire primary, entitled Granite Steps, and the founder of the immigration reform advocacy group Americans By Choice."
Briefly
Wiki Workshop 2024: The eleventh annual Wiki Workshop (formerly part of The Web Conference), organized by the Wikimedia Foundation's research department, took place as an online event on June 20. Extended abstracts (non-archival), video presentations, notes from the event are now available.
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.
How English Wikipedia mediates East Asian historical disputes with Habermasian communicative rationality
"We compare the portrayals of Balhae, an ancient kingdom with contested contexts between [South Korea and China]. By comparing Chinese, Korean, and English Wikipedia entries on Balhae, we identify differences in narrative construction and framing. Employing Habermas’s typology of human action, we scrutinize related talk pages on English Wikipedia to examine the strategic actions multinational contributors employ to shape historical representation. This exploration reveals the dual role of online platforms in both amplifying and mediating historical disputes. While Wikipedia’s policies promote rational discourse, our findings indicate that contributors often vacillate between strategic and communicative actions. Nonetheless, the resulting article approximates Habermasian ideals of communicative rationality."
From the paper:
"The English Wikipedia presents Balhae as a multi-ethnic kingdom, refraining from emphasizing the dominance of a single tribe. In comparison to the two aforementioned excerpts [from Chinese and Korean Wikipedia], the lead section of the English Wikipedia concentrates more on factual aspects of history, thus excluding descriptions that might entail divergent interpretations. In other words, this account of Balhae has thus far proven acceptable to a majority of Wikipedians from diverse backgrounds. [...] Compared to other language versions, the English Wikipedia forthrightly acknowledges the potential disputes regarding Balhae's origin, ethnic makeup, and territorial boundaries, paving the way for an open and transparent exploration of these contested historical subjects. The separate 'Balhae controversies' entry is dedicated to unpacking the contentious issues. In essence, the English article adopts a more encyclopedic tone, aligning closely with Wikipedia's mission of providing information without imposing a certain perspective."
Facebook/Meta's "No Language Left Behind" translation model used on Wikipedia
From the abstract of this publication by a large group of researchers (most of them affiliated with Meta AI):[4]
"Focusing on improving the translation qualities of a relatively small group of high-resource languages comes at the expense of directing research attention to low-resource languages, exacerbating digital inequities in the long run. To break this pattern, here we introduce No Language Left Behind—a single massively multilingual model that leverages transfer learning across languages. [...] Compared with the previous state-of-the-art models, our model achieves an average of 44% improvement in translation quality as measured by BLEU. By demonstrating how to scale NMT [neural machine translation] to 200 languages and making all contributions in this effort freely available for non-commercial use, our work lays important groundwork for the development of a universal translation system."
"Naija is the Nigerian-Pidgin spoken by approx. 120M speakers in Nigeria [...]. Although it has mainly been a spoken language until recently, there are currently two written genres (BBC and Wikipedia) in Naija. Through statistical analyses and Machine Translation experiments, we prove that these two genres do not represent each other (i.e., there are linguistic differences in word order and vocabulary) and Generative AI operates only based on Naija written in the BBC genre. In other words, Naija written in Wikipedia genre is not represented in Generative AI."
The paper's findings are consistent with an analysis by the Wikimedia Foundation's research department that compared the number of Wikipedia articles to the number of speakers for the top 20 most-spoken languages, where Naija stood out as one of the most underrepresented.
"[A] surprising tension between Wikipedia's principle of safeguarding against self-promotion and the scholarly norm of 'due credit'"
Although Wikipedia offers guidelines for determining when a scientist qualifies for their own article, it currently lacks guidance regarding whether a scientist should be acknowledged in articles related to the innovation processes to which they have contributed. To explore how Wikipedia addresses this issue of scientific "micro-notability", we introduce a digital method called Name Edit Analysis, enabling us to quantitatively and qualitatively trace mentions of scientists within Wikipedia's articles. We study two CRISPR-related Wikipedia articles and find dynamic negotiations of micro-notability as well as a surprising tension between Wikipedia’s principle of safeguarding against self-promotion and the scholarly norm of “due credit.” To reconcile this tension, we propose that Wikipedians and scientists collaborate to establish specific micro-notability guidelines that acknowledge scientific contributions while preventing excessive self-promotion.
" [...] the quality of Wikipedia articles rises with the number of editors per article as well as a greater diversity among them. Here, we address a not yet documented potential threat to those preconditions: self-selection of Wikipedia editors to articles. Specifically, we expected articles with a clear-cut link to a specific country (e.g., about its highest mountain, "national" article category) to attract a larger proportion of editors of that nationality when compared to articles without any specific link to that country (e.g., "gravity", "universal" article category), whereas articles with a link to several countries (e.g., "United Nations", "international" article category) should fall in between. Across several language versions, hundreds of different articles, and hundreds of thousands of editors, we find the expected effect [...]"
"What do they make us see:" The "cultural bias" of GLAMs is worse on Wikidata
"Large cultural heritage datasets from museum collections tend to be biased and demonstrate omissions that result from a series of decisions at various stages of the collection construction. The purpose of this study is to apply a set of ethical criteria to compare the level of bias of six online databases produced by two major art museums, identifying the most biased and the least biased databases. [...] For most variables the online system database is more balanced and ethical than the API dataset and Wikidata item collection of the two museums."
^Adelani, David Ifeoluwa; Doğruöz, A. Seza; Shode, Iyanuoluwa; Aremu, Anuoluwapo (2024-04-30). "Which Nigerian-Pidgin does Generative AI speak?: Issues about Representativeness and Bias for Multilingual and Low Resource Languages". arXiv:2404.19442 [cs.CL].
^Backman, J. (2022). Radical conservatism and the Heideggerian right : Heidegger, de Benoist, Dugin. Frontiers in Political Science, 4, Article 941799. https://doi.org/10.3389/fpos.2022.941799
Merging ToDo
A list of related articles that may have resulted from a WP:POVFORK or may, at least, look like the functional equivalents of one Note that the exact target of a potential merge must not be provided here and that multiple options (e.g. generous use of Template:Excerpt) might accomplish the same
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