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    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.

    Major alerts

    A broad collection of discussions that could lead to significant changes of related articles

    Did you know

    Articles for deletion

    • 21 Nov 2024 – Neoauthoritarianism (China) (talk · edit · hist) was AfDed by Simonm223 (t · c); see discussion (11 participants; relisted)
    • 21 Nov 2024 – The Trump Economic Miracle (talk · edit · hist) AfDed by PARAKANYAA (t · c) was closed as draftify (deleted) by OwenX (t · c) on 28 Nov 2024; see discussion (8 participants)

    Redirects for discussion

    Good article nominees

    Good article reassessments

    Requests for comments

    Peer reviews

    Requested moves

    Articles to be merged

    Articles to be split

    Articles for creation

    Watchlists

    WatchAll (Excerpt)
    Excerpt from watchlist concerning all the articles in the project's scope
    Note that your own edits, minor edits, and bot edits are hidden in this tab

    List of abbreviations (help):
    D
    Edit made at Wikidata
    r
    Edit flagged by ORES
    N
    New page
    m
    Minor edit
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    Bot edit
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    2 December 2024

    1 December 2024

    30 November 2024

    29 November 2024

    For this watchlist but about 3X in length, visit: Wikipedia:WikiProject Conservatism/All recent changes
    WatchHot (Excerpt)
    A list of 10 related articles with the most (recent) edits total
    275 edits Donald Trump
    197 edits Călin Georgescu
    108 edits Zionism
    96 edits Second presidential transition of Donald Trump
    91 edits Chuck Woolery
    88 edits Vasile Stroescu
    81 edits Vox (political party)
    42 edits Republican Party (United States)
    41 edits Kamala is for they/them
    39 edits Matt Gaetz

    These are the articles that have been edited the most within the last seven days. Last updated 1 December 2024 by HotArticlesBot.


    List of abbreviations (help):
    D
    Edit made at Wikidata
    r
    Edit flagged by ORES
    N
    New page
    m
    Minor edit
    b
    Bot edit
    (±123)
    Page byte size change

    2 December 2024

    1 December 2024

    30 November 2024

    29 November 2024

    28 November 2024

    For this watchlist but about 5X in length, visit: Wikipedia:WikiProject Conservatism/Hot articles recent changes
    WatchPop (Excerpt)
    A list of 500 related articles with the most (recent) views total

    This is a list of pages in the scope of Wikipedia:WikiProject Conservatism along with pageviews.

    To report bugs, please write on the Community tech bot talk page on Meta.

    List

    Period: 2024-10-01 to 2024-10-31

    Total views: 66,755,923

    Updated: 19:23, 5 November 2024 (UTC)

    Rank Page title Views Daily average Assessment Importance
    1 Donald Trump 1,795,484 57,918 B High
    2 JD Vance 1,464,779 47,250 B Mid
    3 Tony Hinchcliffe 1,146,545 36,985 B Low
    4 Benjamin Netanyahu 729,080 23,518 B Mid
    5 Ronald Reagan 597,503 19,274 FA Top
    6 Project 2025 584,346 18,849 B Mid
    7 Vladimir Putin 486,672 15,699 B High
    8 George W. Bush 470,197 15,167 B High
    9 Family of Donald Trump 433,549 13,985 B Low
    10 Kemi Badenoch 408,860 13,189 C Unknown
    11 George H. W. Bush 401,045 12,936 B High
    12 Republican Party (United States) 395,338 12,752 B Top
    13 Dick Cheney 392,077 12,647 GA Mid
    14 Liz Cheney 387,571 12,502 B High
    15 Zionism 380,958 12,288 B Low
    16 Theodore Roosevelt 357,471 11,531 B High
    17 Richard Nixon 352,231 11,362 FA High
    18 Red states and blue states 335,687 10,828 C Mid
    19 Winston Churchill 325,540 10,501 GA Top
    20 Gerald Ford 318,354 10,269 C High
    21 Dwight D. Eisenhower 291,343 9,398 B High
    22 Candace Owens 282,410 9,110 B Low
    23 Robert Jenrick 278,835 8,994 C Unknown
    24 Shigeru Ishiba 277,093 8,938 B Low
    25 Charlie Kirk 259,812 8,381 C Low
    26 Ted Cruz 234,355 7,559 B Mid
    27 Margaret Thatcher 232,942 7,514 GA Top
    28 2024 Conservative Party leadership election 214,251 6,911 B Low
    29 Bharatiya Janata Party 210,595 6,793 GA Low
    30 List of Donald Trump 2024 presidential campaign endorsements 210,095 6,777 List Low
    31 Jordan Peterson 205,939 6,643 C Low
    32 Rishi Sunak 201,922 6,513 B High
    33 Cold War 201,097 6,487 C Top
    34 Lara Trump 195,581 6,309 C Low
    35 John McCain 194,422 6,271 FA Mid
    36 Rupert Murdoch 192,570 6,211 B Low
    37 Fyodor Dostoevsky 191,367 6,173 B Low
    38 French Revolution 191,347 6,172 B Unknown
    39 Chuck Norris 190,975 6,160 B Low
    40 Ben Shapiro 190,436 6,143 C Mid
    41 Rudy Giuliani 188,867 6,092 B Mid
    42 Taft–Hartley Act 188,639 6,085 B Low
    43 Woke 187,067 6,034 B Top
    44 Steve Bannon 186,395 6,012 B Mid
    45 Mike Pence 184,944 5,965 B Mid
    46 Kelsey Grammer 179,040 5,775 B Low
    47 Mary Matalin 177,149 5,714 C Low
    48 Tucker Carlson 173,959 5,611 B High
    49 Ron DeSantis 173,305 5,590 B Mid
    50 Hillbilly Elegy 173,139 5,585 B Low
    51 Marjorie Taylor Greene 172,052 5,550 GA Low
    52 William McKinley 170,380 5,496 FA Low
    53 1964 United States presidential election 168,766 5,444 C Mid
    54 John Wayne 168,401 5,432 B Low
    55 QAnon 167,161 5,392 GA Mid
    56 Jon Voight 167,082 5,389 C Low
    57 Boris Johnson 166,135 5,359 B High
    58 Linda McMahon 157,062 5,066 B Low
    59 James Cleverly 154,890 4,996 C Low
    60 Grover Cleveland 153,642 4,956 FA Mid
    61 Mitt Romney 148,649 4,795 FA High
    62 Imran Khan 147,448 4,756 B Low
    63 Ben Carson 147,038 4,743 C Low
    64 Liberal Democratic Party (Japan) 146,799 4,735 C High
    65 Robert Duvall 145,107 4,680 B Low
    66 Herbert Hoover 143,275 4,621 B Mid
    67 Constitution of the United States 142,292 4,590 B High
    68 James Caan 142,046 4,582 C Low
    69 Kari Lake 138,354 4,463 C Low
    70 Condoleezza Rice 137,851 4,446 B Mid
    71 Shinzo Abe 137,257 4,427 B Mid
    72 Nayib Bukele 137,044 4,420 GA Low
    73 Shirley Temple 135,292 4,364 B Low
    74 Sarah Palin 128,934 4,159 C Mid
    75 Taliban 128,255 4,137 B High
    76 Warren G. Harding 126,903 4,093 FA Low
    77 James A. Garfield 125,632 4,052 FA Low
    78 Liz Truss 124,917 4,029 FA Mid
    79 Stephen Baldwin 123,625 3,987 B Low
    80 William Howard Taft 121,330 3,913 FA Mid
    81 Calvin Coolidge 121,169 3,908 FA High
    82 Mike Johnson 120,005 3,871 C Mid
    83 Mitch McConnell 119,959 3,869 B Mid
    84 Libertarianism 118,533 3,823 B High
    85 Benjamin Harrison 117,668 3,795 FA Low
    86 Chiang Kai-shek 117,597 3,793 C Low
    87 Nick Fuentes 117,536 3,791 B Low
    88 Nikki Haley 117,397 3,787 B Low
    89 Curtis Yarvin 116,340 3,752 C High
    90 Francisco Franco 115,977 3,741 C Mid
    91 Critical race theory 115,839 3,736 C Low
    92 Mark Rutte 114,862 3,705 C High
    93 Laura Ingraham 114,763 3,702 C Mid
    94 Muhammad Ali Jinnah 114,625 3,697 FA High
    95 John Malkovich 113,593 3,664 C Low
    96 Ayn Rand 113,510 3,661 GA Mid
    97 Agenda 47 112,434 3,626 C Top
    98 James Stewart 111,916 3,610 GA Low
    99 James Woods 111,751 3,604 Start Low
    100 Javier Milei 111,518 3,597 B Mid
    101 Shiv Sena 110,147 3,553 C Unknown
    102 Jeanine Pirro 109,783 3,541 B Low
    103 Matt Walsh (political commentator) 109,272 3,524 C Low
    104 Dan Quayle 107,136 3,456 B Mid
    105 Recep Tayyip Erdoğan 107,040 3,452 B High
    106 Donald Trump 2024 presidential campaign 106,861 3,447 B Low
    107 Spiro Agnew 106,818 3,445 FA Mid
    108 Meredith Sasso 106,656 3,440 Start Low
    109 Greg Gutfeld 106,462 3,434 C Low
    110 Am I Racist? 104,892 3,383 Start Mid
    111 Stephen Miller (political advisor) 104,050 3,356 B Low
    112 Fox News 103,331 3,333 C Mid
    113 Charles de Gaulle 103,282 3,331 B Mid
    114 Rick Scott 99,807 3,219 C Low
    115 Menachem Begin 99,562 3,211 B Mid
    116 Conservative Party (UK) 99,023 3,194 B High
    117 Otto von Bismarck 97,562 3,147 B High
    118 Randall Terry 97,443 3,143 C Unknown
    119 Nancy Reagan 96,943 3,127 B Mid
    120 Pat Sajak 96,562 3,114 C Low
    121 Kristi Noem 96,202 3,103 B Low
    122 Generation 94,724 3,055 B Mid
    123 Clark Gable 94,252 3,040 B Low
    124 False or misleading statements by Donald Trump 93,290 3,009 B Low
    125 Gary Sinise 92,500 2,983 C Low
    126 David Duke 91,518 2,952 B Mid
    127 Patricia Heaton 91,389 2,948 C Low
    128 John Bolton 90,874 2,931 C Mid
    129 John Locke 90,705 2,925 B Top
    130 Neoliberalism 90,667 2,924 B Top
    131 Roger Stone 90,433 2,917 C Low
    132 Nippon Ishin no Kai 90,302 2,912 Start Mid
    133 Whig Party (United States) 90,063 2,905 C Low
    134 Bing Crosby 88,873 2,866 B Low
    135 Iran–Contra affair 88,511 2,855 GA Low
    136 George Santos 88,085 2,841 B Low
    137 Viktor Orbán 87,904 2,835 C Mid
    138 Dave Ramsey 87,062 2,808 C Unknown
    139 Deng Xiaoping 86,420 2,787 B Low
    140 Likud 85,977 2,773 C Low
    141 Angela Merkel 85,735 2,765 GA High
    142 Katie Britt 85,350 2,753 C Low
    143 David Cameron 85,085 2,744 B Top
    144 Far-right politics 84,730 2,733 B Low
    145 Dana Perino 84,659 2,730 C Low
    146 Laura Loomer 84,518 2,726 C Low
    147 Charles Lindbergh 84,415 2,723 B Low
    148 Charlton Heston 84,038 2,710 B Low
    149 Kellyanne Conway 83,838 2,704 B Low
    150 Trump derangement syndrome 83,047 2,678 C Mid
    151 Joe Scarborough 82,699 2,667 B Low
    152 Lindsey Graham 82,492 2,661 C Low
    153 Neoconservatism 82,309 2,655 C Top
    154 George Wallace 82,193 2,651 B Mid
    155 Chester A. Arthur 82,162 2,650 FA Low
    156 Clarence Thomas 81,239 2,620 B Mid
    157 Arthur Wellesley, 1st Duke of Wellington 81,224 2,620 B Low
    158 Proud Boys 81,113 2,616 C Low
    159 Bo Derek 80,774 2,605 Start Low
    160 Kayleigh McEnany 80,648 2,601 C Low
    161 Gadsden flag 80,504 2,596 B Low
    162 Douglas Murray (author) 80,390 2,593 C Low
    163 Anders Behring Breivik 80,053 2,582 C Low
    164 Left–right political spectrum 79,208 2,555 C Top
    165 Craig T. Nelson 78,999 2,548 Start Unknown
    166 Alternative for Germany 78,820 2,542 C Low
    167 Presidency of Donald Trump 78,272 2,524 B Low
    168 Falun Gong 78,267 2,524 B Mid
    169 Paul von Hindenburg 78,149 2,520 C Mid
    170 McCarthyism 78,034 2,517 C High
    171 Anna Paulina Luna 77,393 2,496 B Low
    172 Dmitry Medvedev 74,561 2,405 C High
    173 Barry Goldwater 74,337 2,397 B High
    174 The Heritage Foundation 74,046 2,388 B High
    175 Komeito 73,826 2,381 C Low
    176 Lee Hsien Loong 73,712 2,377 C Mid
    177 Conservative Party of Canada 73,688 2,377 B High
    178 Make America Great Again 73,439 2,369 B Low
    179 Theresa May 73,212 2,361 B Mid
    180 Sean Hannity 72,819 2,349 B Mid
    181 Nigel Farage 71,957 2,321 B Mid
    182 Lauren Boebert 70,887 2,286 B Low
    183 BC United 70,724 2,281 C Mid
    184 The Epoch Times 70,290 2,267 B Low
    185 Melissa Joan Hart 70,238 2,265 B Low
    186 Kevin McCarthy 69,925 2,255 C Low
    187 Naftali Bennett 69,627 2,246 B Mid
    188 1924 United States presidential election 69,247 2,233 C Low
    189 Adam Kinzinger 69,152 2,230 B Low
    190 Paul Ryan 68,846 2,220 C Mid
    191 Byron Donalds 68,829 2,220 C Low
    192 Anthony Scaramucci 68,591 2,212 C Low
    193 T. S. Eliot 68,203 2,200 B Low
    194 Neville Chamberlain 68,063 2,195 FA Mid
    195 Tom Tugendhat 67,894 2,190 B Low
    196 Right-wing politics 67,661 2,182 C Top
    197 John Roberts 67,511 2,177 B High
    198 Greg Abbott 67,466 2,176 B Mid
    199 Newt Gingrich 67,393 2,173 GA High
    200 Dave Mustaine 67,021 2,161 C Low
    201 Milton Friedman 66,385 2,141 GA High
    202 Thomas Sowell 66,336 2,139 C Mid
    203 Constitution Party (United States) 66,091 2,131 C Low
    204 Rutherford B. Hayes 65,755 2,121 FA Low
    205 Bob Dole 65,493 2,112 B Low
    206 Reform UK 65,440 2,110 C High
    207 Gary Cooper 65,265 2,105 FA Mid
    208 Deep state in the United States 64,800 2,090 Start Low
    209 Itamar Ben-Gvir 63,792 2,057 C Mid
    210 Donald Rumsfeld 63,598 2,051 B Mid
    211 Jeb Bush 63,251 2,040 B Low
    212 Brett Kavanaugh 62,813 2,026 B High
    213 John Major 62,448 2,014 B High
    214 Scott Presler 62,052 2,001 B Low
    215 Sheldon Adelson 61,973 1,999 C Low
    216 Conservatism 61,661 1,989 B Top
    217 Capitalism 61,455 1,982 C Top
    218 Brett Cooper (commentator) 60,975 1,966 Start Low
    219 Karl Malone 60,885 1,964 Start Low
    220 W. B. Yeats 60,861 1,963 FA Low
    221 House of Bourbon 60,422 1,949 B High
    222 Ray Bradbury 60,217 1,942 B Low
    223 Laura Bush 59,791 1,928 GA Low
    224 Larry Hogan 59,687 1,925 B Low
    225 Conservative Party of British Columbia 59,598 1,922 C Mid
    226 Buck Sexton 58,880 1,899 Start Low
    227 Pat Buchanan 58,626 1,891 B Mid
    228 Tom Clancy 58,524 1,887 C Low
    229 Great Replacement 58,119 1,874 C Top
    230 Brooks Brothers riot 57,882 1,867 Start Low
    231 Frank Bruno 57,776 1,863 Start Unknown
    232 Trumpism 57,608 1,858 B Mid
    233 Aleksandr Solzhenitsyn 57,265 1,847 B Mid
    234 Anthony Eden 57,168 1,844 B Mid
    235 2024 Liberal Democratic Party (Japan) presidential election 57,099 1,841 C Unknown
    236 Clint Bolick 56,665 1,827 C Mid
    237 Federalist Party 56,475 1,821 C Low
    238 Mike Lindell 56,107 1,809 C Low
    239 Reform Party of the United States of America 55,514 1,790 C Low
    240 Angie Harmon 55,109 1,777 C Low
    241 Gretchen Carlson 55,098 1,777 B Low
    242 Stephen Harper 54,915 1,771 GA High
    243 Strom Thurmond 54,843 1,769 B Mid
    244 Amy Coney Barrett 54,478 1,757 C Low
    245 Rush Limbaugh 53,720 1,732 B High
    246 Scott Baio 53,647 1,730 Start Low
    247 John Layfield 53,547 1,727 B Low
    248 Bill O'Reilly (political commentator) 53,496 1,725 B Mid
    249 Springfield pet-eating hoax 53,260 1,718 B Low
    250 The Wall Street Journal 53,252 1,717 B Mid
    251 Bob Hope 53,090 1,712 B Low
    252 Mahathir Mohamad 52,958 1,708 GA High
    253 Trump fake electors plot 52,601 1,696 B High
    254 Dinesh D'Souza 52,222 1,684 B Mid
    255 Federalist Society 52,193 1,683 B High
    256 Benjamin Disraeli 52,044 1,678 FA Top
    257 Moshe Dayan 51,793 1,670 B Mid
    258 Jack Kemp 51,757 1,669 GA Mid
    259 Jair Bolsonaro 51,540 1,662 B Mid
    260 Shiv Sena (UBT) 51,414 1,658 C Mid
    261 Jackson Hinkle 51,111 1,648 B Low
    262 Daily Mail 51,026 1,646 B Mid
    263 The Daily Telegraph 51,000 1,645 C Low
    264 Harmeet Dhillon 50,800 1,638 Start Low
    265 Nicolas Sarkozy 50,328 1,623 B High
    266 Gavin McInnes 50,295 1,622 C Low
    267 Sanseitō 50,130 1,617 Stub Low
    268 Riley Gaines 50,078 1,615 B Mid
    269 Marco Rubio 50,014 1,613 B Mid
    270 Christian nationalism 49,975 1,612 Start High
    271 Ron Paul 49,695 1,603 C Mid
    272 New York Post 49,673 1,602 C Low
    273 Liberty University 49,418 1,594 B Mid
    274 Matt Gaetz 49,365 1,592 C Low
    275 Barbara Stanwyck 49,326 1,591 B Low
    276 Franklin Graham 49,137 1,585 B Low
    277 Victor Davis Hanson 48,894 1,577 B Mid
    278 Sarah Huckabee Sanders 48,728 1,571 C Low
    279 Curtis Sliwa 48,689 1,570 C Unknown
    280 Trump wall 48,339 1,559 C Low
    281 The Daily Wire 48,179 1,554 C Low
    282 Ted Nugent 48,063 1,550 C Low
    283 Kelly Ayotte 47,623 1,536 C Low
    284 Don King 47,347 1,527 B Low
    285 Meghan McCain 47,317 1,526 C Low
    286 Milo Yiannopoulos 47,275 1,525 C Low
    287 White supremacy 47,161 1,521 B Low
    288 Nancy Mace 46,810 1,510 B Low
    289 Right-wing populism 46,723 1,507 C Low
    290 Marsha Blackburn 46,712 1,506 C Low
    291 Deb Fischer 46,528 1,500 B Unknown
    292 Park Chung Hee 46,504 1,500 C Low
    293 The Fountainhead 46,380 1,496 FA Low
    294 Dan Crenshaw 46,149 1,488 B Low
    295 Martin Heidegger 46,146 1,488 C Low
    296 Antonin Scalia 46,127 1,487 FA High
    297 Grooming gang moral panic in the United Kingdom 46,017 1,484 Redirect NA
    298 Dan Bongino 45,746 1,475 C Mid
    299 List of Donald Trump 2024 presidential campaign non-political endorsements 45,684 1,473 List Low
    300 Turning Point USA 45,517 1,468 C Low
    301 RealClearPolitics 45,371 1,463 C Mid
    302 Jacobitism 45,360 1,463 B High
    303 Manosphere 45,273 1,460 Start Low
    304 Bezalel Smotrich 45,209 1,458 C Mid
    305 America PAC 45,172 1,457 Start Mid
    306 The Times of India 44,965 1,450 C Mid
    307 Groypers 44,965 1,450 B Low
    308 Tea Party movement 44,892 1,448 C Mid
    309 Harold Macmillan 44,789 1,444 B High
    310 Denis Leary 44,468 1,434 C NA
    311 John C. Calhoun 44,363 1,431 FA Top
    312 Chris Christie 43,855 1,414 C Low
    313 National Rally 43,820 1,413 GA High
    314 Rachel Campos-Duffy 43,685 1,409 Start Low
    315 Bret Stephens 43,569 1,405 C Low
    316 Joe Kent 43,562 1,405 C Low
    317 Paul Manafort 43,550 1,404 C Low
    318 Kataeb Party 43,129 1,391 B Low
    319 Conservatism in the United States 43,062 1,389 B Top
    320 Booker T. Washington 42,901 1,383 B Low
    321 John Kennedy (Louisiana politician) 42,691 1,377 C Low
    322 Jemima Goldsmith 42,680 1,376 C Unknown
    323 Edward Teller 42,538 1,372 FA Low
    324 Robert Kagan 42,464 1,369 C Low
    325 Morgan Ortagus 42,456 1,369 C Unknown
    326 United Russia 42,410 1,368 B High
    327 Laissez-faire 42,360 1,366 C Top
    328 Basket of deplorables 42,018 1,355 GA Low
    329 Truth Social 41,837 1,349 B Low
    330 Lillian Gish 41,781 1,347 C Low
    331 Marc Andreessen 41,664 1,344 C Mid
    332 Ann Coulter 41,590 1,341 B Mid
    333 Dave Rubin 41,520 1,339 C Low
    334 Roger Ailes 41,503 1,338 C Mid
    335 Patriots for Europe 41,319 1,332 C Low
    336 Lynne Cheney 41,316 1,332 C Low
    337 Jane Russell 40,844 1,317 B Low
    338 Mullah Omar 40,659 1,311 B High
    339 William F. Buckley Jr. 40,626 1,310 C Top
    340 Rumble (company) 40,477 1,305 Start Low
    341 Pat Boone 40,465 1,305 C Low
    342 Last Man Standing (American TV series) 40,100 1,293 B Low
    343 Edmund Burke 39,952 1,288 B Top
    344 Comparisons between Donald Trump and fascism 39,891 1,286 B Mid
    345 Oliver North 39,837 1,285 C Mid
    346 Brothers of Italy 39,827 1,284 B Mid
    347 Michael Steele 39,605 1,277 B Low
    348 Stacey Dash 39,566 1,276 C Low
    349 Michael Reagan 39,552 1,275 C Low
    350 Nawaz Sharif 39,524 1,274 B Unknown
    351 2016 Republican Party presidential primaries 39,520 1,274 B Mid
    352 Glenn Beck 39,467 1,273 B Mid
    353 2024 United Kingdom riots 39,385 1,270 B Low
    354 Ustaše 39,320 1,268 C High
    355 2024 Trump rally at Madison Square Garden 39,273 1,266 Start Low
    356 The Gateway Pundit 39,159 1,263 C Unknown
    357 Mark Levin 39,156 1,263 Start High
    358 Elise Stefanik 39,149 1,262 B Low
    359 Neil Gorsuch 38,917 1,255 B Mid
    360 Robert Peel 38,848 1,253 B High
    361 American Independent Party 38,355 1,237 C Low
    362 Jacob Rees-Mogg 38,279 1,234 C Low
    363 Classical liberalism 38,183 1,231 B Top
    364 Geert Wilders 38,040 1,227 C Low
    365 Terri Schiavo case 37,828 1,220 GA Low
    366 Bible Belt 37,741 1,217 C Low
    367 American Solidarity Party 37,511 1,210 C Low
    368 Tradwife 37,441 1,207 B Low
    369 Edward Heath 37,423 1,207 B High
    370 Michel Houellebecq 37,341 1,204 C Low
    371 Norman Tebbit 37,325 1,204 B Mid
    372 Tommy Tuberville 37,220 1,200 B Low
    373 Drudge Report 37,190 1,199 B Mid
    374 Samuel Alito 37,067 1,195 C Mid
    375 Jeff Flake 37,050 1,195 C Mid
    376 Friedrich Hayek 37,035 1,194 B Top
    377 Gary Johnson 36,913 1,190 GA High
    378 Tom Cotton 36,793 1,186 C Low
    379 Rand Paul 36,767 1,186 GA Mid
    380 Conservative Party of Japan 36,709 1,184 C Low
    381 Leader of the Conservative Party (UK) 36,589 1,180 List Low
    382 Redneck 36,336 1,172 C Low
    383 United National Movement 36,219 1,168 C Low
    384 Social stratification 36,087 1,164 C High
    385 Michelle Steel 36,053 1,163 C Low
    386 Saskatchewan Party 36,015 1,161 B Mid
    387 John Birch Society 35,957 1,159 C Low
    388 Promised Land 35,872 1,157 C Low
    389 Fianna Fáil 35,869 1,157 B Low
    390 Mike Gabbard 35,859 1,156 Start Unknown
    391 D. H. Lawrence 35,832 1,155 B Unknown
    392 Anita Bryant 35,763 1,153 B High
    393 Thomas Massie 35,344 1,140 B Low
    394 Dark Enlightenment 34,825 1,123 Start Mid
    395 Ginger Rogers 34,525 1,113 C Unknown
    396 Breitbart News 34,440 1,110 C Mid
    397 Honoré de Balzac 34,164 1,102 FA High
    398 History of the Republican Party (United States) 33,919 1,094 B High
    399 Trey Gowdy 33,898 1,093 C Mid
    400 First impeachment of Donald Trump 33,773 1,089 B High
    401 Christopher Luxon 33,711 1,087 B Unknown
    402 Betsy DeVos 33,661 1,085 C Mid
    403 Dennis Miller 33,597 1,083 Start Low
    404 Kalergi Plan 33,415 1,077 Start Mid
    405 Alt-right 33,383 1,076 C Mid
    406 William Barr 33,315 1,074 B Unknown
    407 Steele dossier 33,290 1,073 B Low
    408 Views of Elon Musk 33,188 1,070 B Mid
    409 Original sin 33,163 1,069 C Low
    410 Fred Thompson 33,117 1,068 B Low
    411 António de Oliveira Salazar 33,031 1,065 B Unknown
    412 Thomas Mann 32,994 1,064 C Mid
    413 Otzma Yehudit 32,989 1,064 B Mid
    414 Natural law 32,966 1,063 C Top
    415 Enoch Powell 32,963 1,063 B High
    416 Elisabeth Hasselbeck 32,862 1,060 C Low
    417 Nuclear family 32,750 1,056 Start Low
    418 Homeland Union 32,745 1,056 Start High
    419 Mike Braun 32,671 1,053 B Low
    420 Lil Pump 32,662 1,053 B Low
    421 David Mamet 32,630 1,052 C Low
    422 Fine Gael 32,616 1,052 B High
    423 Austrian People's Party 32,528 1,049 Start High
    424 James Cagney 32,510 1,048 GA Low
    425 Political spectrum 32,344 1,043 C Top
    426 Mike DeWine 32,192 1,038 B Low
    427 Tomi Lahren 32,174 1,037 Start Low
    428 Robert Davi 32,125 1,036 Start Low
    429 Franz von Papen 32,113 1,035 B Low
    430 InfoWars 32,085 1,035 C Low
    431 Michael Farmer, Baron Farmer 32,067 1,034 C Low
    432 Progressivism 31,862 1,027 C Mid
    433 Bill Kristol 31,805 1,025 B High
    434 Louis B. Mayer 31,628 1,020 C Low
    435 Islamism 31,578 1,018 B High
    436 Patriarchy 31,572 1,018 B Low
    437 Islamophobia 31,556 1,017 C Mid
    438 Facebook–Cambridge Analytica data scandal 31,538 1,017 C Unknown
    439 Elaine Chao 31,474 1,015 B Low
    440 Samuel Taylor Coleridge 31,416 1,013 C Top
    441 Fred MacMurray 31,390 1,012 C Low
    442 Johnny Ramone 31,267 1,008 C Low
    443 Chuck Grassley 31,254 1,008 C Mid
    444 Rick Perry 31,186 1,006 B Mid
    445 Bourbon Restoration in France 31,126 1,004 C High
    446 LaRouche movement 30,910 997 C Low
    447 Enrique Peña Nieto 30,898 996 B Low
    448 Christian Democratic Union of Germany 30,818 994 C High
    449 Éamon de Valera 30,798 993 B High
    450 Koch family 30,773 992 Start High
    451 Flannery O'Connor 30,733 991 A Low
    452 Muhammad Zia-ul-Haq 30,678 989 B High
    453 Leonard Leo 30,186 973 C Mid
    454 Grey Wolves (organization) 30,150 972 B Mid
    455 Mike Huckabee 30,118 971 B Mid
    456 2008 California Proposition 8 30,093 970 B Mid
    457 Broken windows theory 29,928 965 C Low
    458 Doug Ford 29,905 964 C Low
    459 Steven Crowder 29,905 964 C Mid
    460 Fairness doctrine 29,904 964 C Mid
    461 GypsyCrusader 29,838 962 C Low
    462 T. D. Jakes 29,810 961 C Unknown
    463 Alessandra Mussolini 29,695 957 B Unknown
    464 Tim Scott 29,644 956 C Low
    465 Michael Knowles (political commentator) 29,508 951 Start Low
    466 Norma McCorvey 29,496 951 C Unknown
    467 Law and Justice 29,494 951 C High
    468 Southern strategy 29,400 948 B High
    469 Meir Kahane 29,325 945 B High
    470 Illegal immigration to the United States 29,312 945 B Low
    471 Charlie Crist 29,254 943 B Low
    472 Newsmax 29,153 940 Start Low
    473 Kelly Loeffler 29,143 940 B Low
    474 Frank Luntz 29,126 939 B Low
    475 Twitter under Elon Musk 28,989 935 B Mid
    476 William Rehnquist 28,967 934 B High
    477 Barack Obama citizenship conspiracy theories 28,935 933 B Low
    478 Hillsdale College 28,901 932 C Low
    479 John Warner 28,851 930 C Low
    480 Jim Jordan 28,773 928 B Low
    481 Blaire White 28,567 921 Start Low
    482 Profumo affair 28,534 920 FA Mid
    483 Phil Robertson 28,490 919 C Low
    484 Jacob Chansley 28,416 916 B Low
    485 Liberal Party of Australia 28,408 916 C High
    486 Frankfurt School 28,400 916 B Low
    487 Loretta Young 28,318 913 C Low
    488 Richard B. Spencer 28,282 912 C Low
    489 Rule of law 28,220 910 C Top
    490 Primogeniture 28,054 904 Start Low
    491 Charles Koch 27,999 903 B Low
    492 John Rocker 27,991 902 C Unknown
    493 Jack Posobiec 27,985 902 C Low
    494 John Cornyn 27,984 902 B Low
    495 UK Independence Party 27,961 901 B Low
    496 Herbert Kickl 27,919 900 Stub Mid
    497 Liberal National Party of Queensland 27,855 898 Start Low
    498 Julius Evola 27,786 896 B Low
    499 Jerry Falwell 27,775 895 B High
    500 Jeff Sessions 27,724 894 Start Unknown

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    New articles

    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.

    Rules | Match log | Results page (for watching) | Last updated: 2024-12-01 20:09 (UTC)

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    In The Signpost

    One of various articles to this effect
    The Right Stuff
    July 2018
    DISCUSSION REPORT
    WikiProject Conservatism Comes Under Fire

    By Lionelt

    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.

    Add the Project Discussion page to your watchlist for the "latest RFCs" at WikiProject Conservatism Watch (Discuss this story)
    ARTICLES REPORT
    Margaret Thatcher Makes History Again

    By Lionelt

    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)
    RECENT RESEARCH
    Research About AN/I

    By Lionelt

    Reprinted in part from the April 26, 2018 issue of The Signpost; written by Zarasophos

    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.

    (Discuss this story)

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    Is Wikipedia Politically Biased? Perhaps

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    By Tilman Bayer


    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).

    In other cases, Rozado was able to use external data about political leanings, e.g. "a list of politically aligned U.S.-based journalists" from Politico. There may be questions about construct validity here (e.g. it classifies Glenn Greenwald or Andrew Sullivan as "journalists with the left"), but at least this data is transparent and determined by a source not invested in the present paper's findings.

    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."

    Tony Abbott.
    Most negative sentiment among Western leaders: Former Australian PM Tony Abbott
    Scott Morrison.
    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:

    1. What would be a perfectly fair baseline, a result that makes us confident to call Wikipedia unbiased?
    2. 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 cautioned by 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


    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

    From the abstract: [3]

    "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."

    (See also excerpts)

    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."

    "Four months after the launch of NLLB-200 [in 2022], Wikimedia reported that our model was the third most used machine translation engine used by Wikipedia editors (accounting for 3.8% of all published translations) (https://web.archive.org/web/20221107181300/https://nbviewer.org/github/wikimedia-research/machine-translation-service-analysis-2022/blob/main/mt_service_comparison_Sept2022_update.ipynb). Compared with other machine translation services and across all languages, articles translated with NLLB-200 has the lowest percentage of deletion (0.13%) and highest percentage of translation modification kept under 10%."

    "Which Nigerian-Pidgin does Generative AI speak?" – only the BBC's, not Wikipedia's

    From the abstract:[5]

    "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'"

    From the abstract:[6]

    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.

    See also coverage of a different paper that likewise analyzed Wikipedia's coverage of CRISPR: "Wikipedia as a tool for contemporary history of science: A case study on CRISPR"

    "How article category in Wikipedia determines the heterogeneity of its editors"

    From the abstract:[7]

    " [...] 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

    From the abstract:[8]

    "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."

    References

    1. ^ Rozado, David (June 2024). "Is Wikipedia Politically Biased?". Manhattan Institute. Dataset: https://doi.org/10.5281/zenodo.10775984
    2. ^ Kerkhof, Anna; Münster, Johannes (2019-10-02). "Detecting coverage bias in user-generated content". Journal of Media Economics. 32 (3–4): 99–130. doi:10.1080/08997764.2021.1903168. ISSN 0899-7764.
    3. ^ Jee, Jonghyun; Kim, Byungjun; Jun, Bong Gwan (2024). "The role of English Wikipedia in mediating East Asian historical disputes: the case of Balhae". Asian Journal of Communication: 1–20. doi:10.1080/01292986.2024.2342822. ISSN 0129-2986. Closed access icon (access for Wikipedia Library users)
    4. ^ Costa-jussà, Marta R.; Cross, James; Çelebi, Onur; Elbayad, Maha; Heafield, Kenneth; Heffernan, Kevin; Kalbassi, Elahe; Lam, Janice; Licht, Daniel; Maillard, Jean; Sun, Anna; Wang, Skyler; Wenzek, Guillaume; Youngblood, Al; Akula, Bapi; Barrault, Loic; Gonzalez, Gabriel Mejia; Hansanti, Prangthip; Hoffman, John; Jarrett, Semarley; Sadagopan, Kaushik Ram; Rowe, Dirk; Spruit, Shannon; Tran, Chau; Andrews, Pierre; Ayan, Necip Fazil; Bhosale, Shruti; Edunov, Sergey; Fan, Angela; Gao, Cynthia; Goswami, Vedanuj; Guzmán, Francisco; Koehn, Philipp; Mourachko, Alexandre; Ropers, Christophe; Saleem, Safiyyah; Schwenk, Holger; Wang, Jeff; NLLB Team (June 2024). "Scaling neural machine translation to 200 languages". Nature. 630 (8018): 841–846. Bibcode:2024Natur.630..841N. doi:10.1038/s41586-024-07335-x. ISSN 1476-4687. PMC 11208141. PMID 38839963.
    5. ^ 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].
    6. ^ Simons, Arno; Kircheis, Wolfgang; Schmidt, Marion; Potthast, Martin; Stein, Benno (2024-02-28). "Who are the "Heroes of CRISPR"? Public science communication on Wikipedia and the challenge of micro-notability". Public Understanding of Science. doi:10.1177/09636625241229923. ISSN 0963-6625. PMID 38419208. blog post
    7. ^ Oeberst, Aileen; Ridderbecks, Till (2024-01-07). "How article category in Wikipedia determines the heterogeneity of its editors". Scientific Reports. 14 (1): 740. Bibcode:2024NatSR..14..740O. doi:10.1038/s41598-023-50448-y. ISSN 2045-2322. PMC 10772120. PMID 38185716.
    8. ^ Zhitomirsky-Geffet, Maayan; Kizhner, Inna; Minster, Sara (2022-01-01). "What do they make us see: a comparative study of cultural bias in online databases of two large museums". Journal of Documentation. 79 (2): 320–340. doi:10.1108/JD-02-2022-0047. ISSN 0022-0418. Closed access icon / freely accessible version


    ToDo List

    Miscellaneous tasks

    A list of articles needing cleanup associated with this project is available. See also the tool's wiki page and the index of WikiProjects.

    Categories to look through

    Conservatism articles needing attention
    Conservatism articles needing expert attention
    Wikipedia requested images of conservatism
    (See also this much larger list of relevant articles without a lead image)
    Conservatism articles needing infoboxes

    Translation ToDo

    A list of related articles particularly good and notable enough to be worthy of a solid translation effort

    Requested articles (in general)

    1. ^ 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
    Retrieved from "https://en.wikipedia.org/w/index.php?title=Wikipedia:WikiProject_Conservatism&oldid=1257023579"