Experimental Evidence on Partisan Bias in Grading
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Studying Political Bias Via Word Embeddings
Studying Political Bias via Word Embeddings Josh Gordon Marzieh Babaeianjelodar Jeanna Matthews Clarkson University jogordo,babaeim,[email protected] ABSTRACT 1 INTRODUCTION Machine Learning systems learn bias in addition to other patterns In 2016, Bolukbasi et al. [1] published an influential paper demon- from input data on which they are trained. Bolukbasi et al. pio- strating a method to quantify and remove gender bias that a ma- neered a method for quantifying gender bias learned from a corpus chine learning (ML) model learned from a corpus of human text. of text. Specifically, they compute a gender subspace into which This is important for revealing bias in human text as well as re- words, represented as word vectors, can be placed and compared ducing the impact biased ML systems can have on hiring, housing, with one another. In this paper, we apply a similar methodology and credit. In this paper, we explore how we might use a similar to a different type of bias, political bias. Unlike with gender bias, methodology to model other kinds of bias such as political bias. it is not obvious how to choose a set of definitional word pairs to As with gender, we begin as Bolukbasi et al. did with attempting compute a political bias subspace. We propose a methodology for to model political bias as simply two binary extremes along a single doing so that could be used for modeling other types of bias as well. axis. Neither gender nor political bias is as simple in the real world We collect and examine a 26 GB corpus of tweets from Republican as two points on a single axis, but we wanted to see how useful and Democratic politicians in the United States (presidential candi- this model could be in the case of political bias. -
The Culture of Wikipedia
Good Faith Collaboration: The Culture of Wikipedia Good Faith Collaboration The Culture of Wikipedia Joseph Michael Reagle Jr. Foreword by Lawrence Lessig The MIT Press, Cambridge, MA. Web edition, Copyright © 2011 by Joseph Michael Reagle Jr. CC-NC-SA 3.0 Purchase at Amazon.com | Barnes and Noble | IndieBound | MIT Press Wikipedia's style of collaborative production has been lauded, lambasted, and satirized. Despite unease over its implications for the character (and quality) of knowledge, Wikipedia has brought us closer than ever to a realization of the centuries-old Author Bio & Research Blog pursuit of a universal encyclopedia. Good Faith Collaboration: The Culture of Wikipedia is a rich ethnographic portrayal of Wikipedia's historical roots, collaborative culture, and much debated legacy. Foreword Preface to the Web Edition Praise for Good Faith Collaboration Preface Extended Table of Contents "Reagle offers a compelling case that Wikipedia's most fascinating and unprecedented aspect isn't the encyclopedia itself — rather, it's the collaborative culture that underpins it: brawling, self-reflexive, funny, serious, and full-tilt committed to the 1. Nazis and Norms project, even if it means setting aside personal differences. Reagle's position as a scholar and a member of the community 2. The Pursuit of the Universal makes him uniquely situated to describe this culture." —Cory Doctorow , Boing Boing Encyclopedia "Reagle provides ample data regarding the everyday practices and cultural norms of the community which collaborates to 3. Good Faith Collaboration produce Wikipedia. His rich research and nuanced appreciation of the complexities of cultural digital media research are 4. The Puzzle of Openness well presented. -
Qanon • 75 Years of the Bomb • Vaccine History • Raising
SQANON • K75 YEARS OF ETHE BOMB P• VACCINE HISTORYT • RAISINGI CTHE DEAD? Extraordinary Claims, Revolutionary Ideas & the Promotion of Science—Vol.25Science—Vol.25 No.4No.4 2020 $6.95 USA and Canada www.skeptic.com • WHAT IS QANON? • HOW QANON RECYCLES CENTURIES-OLD CONSPIRACY BELIEFS • HOW QANON HURTS THEIR OWN CAUSE • QANON IN CONSPIRATORIAL CONTEXT watch or listen for free Hear leading scientists, scholars, and thinkers discuss the most important issues of our time. Hosted by Michael Shermer. #146 Dr. DonalD Prothero— # 130 Dr. DeBra Soh—the end # 113 Dave ruBIn— # 106 Dr. DanIel ChIrot— Weird earth: Debunking Strange of Gender: Debunking the Myths Don’t Burn this Book: you Say you Want a revolution? Ideas about our Planet about Sex & Identity in our Society thinking for yourself in an radical Idealism and its tragic age of unreason Consequences #145 GreG lukIanoff—Mighty # 129 Dr. Mona Sue WeISSMark Ira: the aClu’s controversial involve- —the Science of Diversity # 112 ann Druyan—Cosmos: # 105 Dr. DIana PaSulka— ment in the Skokie case of 1977. Possible Worlds. how science and american Cosmic: ufos, # 128 MIChael ShellenBerGer civilization grew up together religion, and technology #144 Dr. aGuStIn fuenteS— —apocalypse never: Why environ- Why We Believe: evolution and the mental alarmism hurts us all human Way of Being # 127 Dr. WIllIaM Perry and #143 Dr. nICholaS ChrIStakIS— toM CollIna—the Button: the apollo’s arrow: the Profound and new nuclear arms race and Presi- enduring Impact of Coronavirus on dential Power from truman to trump the Way We live # 126 Sarah SColeS—they are #142 Dr. -
Mitigating Political Bias in Language Models Through Reinforced Calibration
Mitigating Political Bias in Language Models Through Reinforced Calibration Ruibo Liu,1 Chenyan Jia, 2 Jason Wei, 3 Guangxuan Xu, 1 Lili Wang, 1 Soroush Vosoughi 1 1 Department of Computer Science, Dartmouth College 2 Moody College of Communication, University of Texas at Austin 3 ProtagoLabs [email protected], [email protected] Abstract with particular keywords of the aforementioned attributes, and 2) Direct Bias, which measures bias in texts generated Current large-scale language models can be politically bi- using prompts that have directly ideological triggers (e.g., ased as a result of the data they are trained on, potentially causing serious problems when they are deployed in real- democrat, republican) in addition to keywords of aforemen- world settings. In this paper, we describe metrics for mea- tioned attributes. Table 1 shows four samples of text gen- suring political bias in GPT-2 generation and propose a re- erated by off-the-shelf GPT-2 with different attribute key- inforcement learning (RL) framework for mitigating political words in the prompts—all samples exhibit political bias. biases in generated text. By using rewards from word em- For example, when triggered with a prompt including mar- beddings or a classifier, our RL framework guides debiased ijuana, the generated text tends to present a favorable atti- generation without having access to the training data or re- tude (e.g., “I believe it should be legal and not regulated.”), quiring the model to be retrained. In empirical experiments which is mostly a liberal stance. More interestingly, even on three attributes sensitive to political bias (gender, loca- a prompt including a conservative trigger (republican) re- tion, and topic), our methods reduced bias according to both sults in generation which leans to the liberal side (“vote for our metrics and human evaluation, while maintaining read- ability and semantic coherence. -
1 Does Political Affiliation Trump Outcome Bias? Evan D. Lester
Does Political Affiliation Trump Outcome Bias? 1 Does Political Affiliation Trump Outcome Bias? Evan D. Lester Department of Psychology Hampden-Sydney College Does Political Affiliation Trump Outcome Bias? 2 Abstract Research in the field of judgment and decision making has consistently shown that information pertaining to the outcome of a decision has a significant impact on people’s attitudes of the decision itself. This effect is referred to as outcome bias. Data was collected from approximately equal numbers of Republicans and Democrats. Participants were presented with descriptions and outcomes of decisions made by a hypothetical politician. The decisions concerned public policies in response to the Coronavirus (COVID-19) pandemic. Participants evaluated the quality of the thinking that went into each decision. Results showed that policies that yielded successful outcomes received significantly better evaluations than policies that yielded failures. Democrats exhibited this tendency to a greater extent compared to Republicans. Conversely, Republicans exhibited a greater bias toward their own political party than did Democrats. The findings of this project are discussed within the context of classic and contemporary findings in the field of judgment and decision making. Keywords: Outcome Bias, Hindsight Bias, Political Affiliation Does Political Affiliation Trump Outcome Bias? 3 Does Political Affiliation Trump Outcome Bias? Individuals make countless decisions every day. Some decisions are trivial (i.e. what to eat) while other decisions can impact many people (i.e. public policy decisions). But how do individuals decide what makes a good or bad decision? In explaining how individuals evaluate decision quality, expected utility theory (EUT) suggests that individuals are rational and deliberate in their estimates of the options available. -
Reliability of Wikipedia 1 Reliability of Wikipedia
Reliability of Wikipedia 1 Reliability of Wikipedia The reliability of Wikipedia (primarily of the English language version), compared to other encyclopedias and more specialized sources, is assessed in many ways, including statistically, through comparative review, analysis of the historical patterns, and strengths and weaknesses inherent in the editing process unique to Wikipedia. [1] Because Wikipedia is open to anonymous and collaborative editing, assessments of its Vandalism of a Wikipedia article reliability usually include examinations of how quickly false or misleading information is removed. An early study conducted by IBM researchers in 2003—two years following Wikipedia's establishment—found that "vandalism is usually repaired extremely quickly — so quickly that most users will never see its effects"[2] and concluded that Wikipedia had "surprisingly effective self-healing capabilities".[3] A 2007 peer-reviewed study stated that "42% of damage is repaired almost immediately... Nonetheless, there are still hundreds of millions of damaged views."[4] Several studies have been done to assess the reliability of Wikipedia. A notable early study in the journal Nature suggested that in 2005, Wikipedia scientific articles came close to the level of accuracy in Encyclopædia Britannica and had a similar rate of "serious errors".[5] This study was disputed by Encyclopædia Britannica.[6] By 2010 reviewers in medical and scientific fields such as toxicology, cancer research and drug information reviewing Wikipedia against professional and peer-reviewed sources found that Wikipedia's depth and coverage were of a very high standard, often comparable in coverage to physician databases and considerably better than well known reputable national media outlets. -
Details of Module and Its Structure
Details of Module and its Structure Module Detail Subject Name Sociology Paper Name Development, Globalisation and Society Module Name/Title Religious Resurgence Pre-requisites Understanding implications of globalisation on religion Objectives The module aims to understand the impact of globalisation on religion; initially religion losing its significance and then resurging with new dimensions. Keywords globalisation, secularisation and religious resurgence Structure of Module / Syllabus of a module (Define Topic / Sub-topic of module) Globalisation and its Impacts – Religious Resurgence Role Name Affiliation Principal Investigator Prof Sujata Patel Department of Sociology, University of Hyderabad Paper Coordinator Prof Sherry Sabbarwal Department of Sociology, Panjab University, Chandigarh Content Writer/Author (CW) Veenat Department of Sociology, Post Graduate Government College for Girls, Sector-11, Chandigarh Content Reviewer (CR) Prof Sherry Sabbarwal Department of Sociology, Panjab University, Chandigarh Language Editor (LE) Prof Sherry Sabbarwal Department of Sociology, Panjab University, Chandigarh 1 Course: Development, Globalisation and Society Unit: Globalisation and its Impacts Module Title: Religious Resurgence Introduction In the present times, religious terrorism, love jihad, religious conversions and re-conversions (ghar wapsi), fundamentalists’ agendas, etc. are the buzzwords. Interestingly, this is happening in midst of the phase that is supposedly the most advanced stage of civilisation where human beings are acquainted with best of scientific innovations and information technology and the whole world has shrunk, to what McLuhan calls a ‘global village’. When the process of globalisation gained momentum in the twentieth century, affecting almost all facets of human life like economy, politics, intellect and culture, surpassing all constraints of time and space, it also had a significant impact on religion. -
Watchdog Or Loyalservant? Political Media Bias in Us Newscasts
Diskussionspapierreihe Working Paper Series WATCHDOG OR LOYAL SERVANT? POLITICAL MEDIA BIAS IN US NEWSCASTS LEA BERNHARDT RALF DEWENTER TOBIAS THOMAS Nr./ No. 183 AUGUST 2020 Department of Economics Fächergruppe Volkswirtschaftslehre Autoren / Authors Lea Bernhardt Helmut-Schmidt-University Hamburg Department of Economics Holstenhofweg 85, 22043 Hamburg [email protected] Ralf Dewenter Helmut-Schmidt-University Hamburg Department of Economics Holstenhofweg 85, 22043 Hamburg [email protected] Tobias Thomas Düsseldorf Institute for Competition Economics (DICE) at Heinrich-Heine-University Düsseldorf and Centre of Media Data and Society (CMDS) at Central European University (CEU), Hungary [email protected] Redaktion / Editors Helmut Schmidt Universität Hamburg / Helmut Schmidt University Hamburg Fächergruppe Volkswirtschaftslehre / Department of Economics Eine elektronische Version des Diskussionspapiers ist auf folgender Internetseite zu finden / An elec- tronic version of the paper may be downloaded from the homepage: https://www.hsu-hh.de/fgvwl/forschung Koordinator / Coordinator Ralf Dewenter [email protected] Helmut Schmidt Universität Hamburg / Helmut Schmidt University Hamburg Fächergruppe Volkswirtschaftslehre / Department of Economics Diskussionspapier Nr. 183 Working Paper No. 183 Watchdog or Loyal Servant? Political Media Bias in US Newscasts Lea Bernhardt Ralf Dewenter Tobias Thomas Zusammenfassung / Abstract We investigate if four leading, electronic news gathering organizations in the US – ABC News, CBS News, FOX News, and NBC News – fulfill their role as the fourth estate in the US democracy. Our analysis, using the Political Coverage Index (PCI) introduced by Dewenter et al (2020), is based on the tonality of their political coverage using 815,000 human-coded news items from 2001 through 2012. For our econometric analysis, we use panel regressions with media and time fixed effects. -
POLITICAL INTERACTION in WIKIPEDIA Jointly They Edit
JOINTLY THEY EDIT: POLITICAL INTERACTION IN WIKIPEDIA 1 Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia Jessica G. Neff1, David Laniado2, Karolin Eva Kappler2, Yana Volkovich2, Pablo Aragón2 & Andreas Kaltenbrunner2 University of Southern California1 Barcelona Media Foundation2 Abstract In their 2005 study, Adamic and Glance coined the memorable phrase ‘divided they blog’, referring to a trend of cyberbalkanization in the political blogosphere, with liberal and conservative blogs tending to link to other blogs with a similar political slant, and not to one another. As political discussion and activity increasingly moves online, the power of framing political discourses is shifting from mass media to social media. Continued examination of political interactions online is critical, and we extend this line of research by examining the activities of political users within the Wikipedia community. First, we examined how users in Wikipedia choose to display (or not to display) their political affiliation. Next, we more closely examined the patterns of cross-party interaction and community participation among those users proclaiming a political affiliation. In contrast to previous analyses of other social media, we did not find strong trends indicating a preference to interact with members of the same political party within the Wikipedia community. Our results indicate that users who proclaim their political affiliation within the community tend to proclaim their identity as a ‘Wikipedian’ even more loudly. It seems that the shared identity of ‘being Wikipedian’ may be strong enough to triumph over other potentially divisive facets of personal identity, such as political affiliation. JOINTLY THEY EDIT: POLITICAL INTERACTION IN WIKIPEDIA 2 Introduction Online media have become an increasingly important source of political information in recent years. -
June 28-30, 2017 – Singapore
2017 DRAFT paper – not for circulation/ citation without permission [email protected] 3rd International Conference on Public Policy (ICPP3) June 28-30, 2017 – Singapore Panel T03P06 Session * Policy, Values and Human Behaviour Title of the paper Bias, cognition, and post-truth politics: considering the cognitive- political origins of misperceptions to improve evidence use in political arenas Author(s) Justin Parkhurst, London School of Econoimcs and Political Science, London, United Kingdom [email protected] Date of presentation Friday 30 June 2017 2017 DRAFT paper – not for circulation/ citation without permission [email protected] ICPP 2017 Bias, cognition, and post-truth politics: considering the cognitive-political origins of misperceptions to improve evidence use in political arenas Justin Parkhurst Associate Professor, London School of Economics and Political Science Introduction: While calls for evidence to inform policy have grown over recent years, these appears to stand in stark contrast to recent high level political events demonstrating that large segments of the population can show minimal regard for evidentiary rigour or expertise in regard to politics. Indeed the creation and belief of misinformation, and the apparent public rejection of corrections, during campaigns such as the British EU referendum and the 2016 US presidential election, has led to many now describing the political environment as having entered an era of ‘post-truth politics’. The proliferation of politically motivated misinformation, and the failure of evidence and fact- checking to correct it, can be seen to many as providing a fundamental challenge to the democratic ideals of rational decision making by a well-informed populace. -
Ideological Diversity, Hostility, and Discrimination in Philosophy
Philosophical Psychology ISSN: 0951-5089 (Print) 1465-394X (Online) Journal homepage: https://www.tandfonline.com/loi/cphp20 Ideological diversity, hostility, and discrimination in philosophy Uwe Peters, Nathan Honeycutt, Andreas De Block & Lee Jussim To cite this article: Uwe Peters, Nathan Honeycutt, Andreas De Block & Lee Jussim (2020): Ideological diversity, hostility, and discrimination in philosophy, Philosophical Psychology, DOI: 10.1080/09515089.2020.1743257 To link to this article: https://doi.org/10.1080/09515089.2020.1743257 Published online: 16 Apr 2020. Submit your article to this journal View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=cphp20 PHILOSOPHICAL PSYCHOLOGY https://doi.org/10.1080/09515089.2020.1743257 ARTICLE Ideological diversity, hostility, and discrimination in philosophy Uwe Petersa,b, Nathan Honeycutt c, Andreas De Blockd and Lee Jussimc aDepartment of Philosophy, University of Southern Denmark, Denmark; bDepartment of Psychology, King's College London, UK; cDepartment of Psychology, Rutgers University, New Brunswick, United States; dCentre for Logic and Philosophy of Science, Leuven, Belgium ABSTRACT ARTICLE HISTORY Members of the field of philosophy have, just as other peo- Received 10 January 2019 ple, political convictions or, as psychologists call them, ideol- Accepted 3 July 2019 ff ogies. How are di erent ideologies distributed and perceived KEYWORDS fi in the eld? Using the familiar distinction between the poli- Ideological bias; diversity; tical left and right, we surveyed an international sample of demographics 794 subjects in philosophy. We found that survey partici- pants clearly leaned left (75%), while right-leaning individuals (14%) and moderates (11%) were underrepresented. -
The IMF As a Biased Global Insurance Mechanism: Asymmetrical Moral
The IMF As a Biased Global Insurance . Mechanism: Asymmetrical Moral Hazard, Reserve Accumulation, and Financial Crises Phillip Y. Lipscy and Haillie Na-Kyung Lee Abstract A large literature has established that the International Monetary Fund (IMF) is heavily politicized. We argue that this politicization has important conse- https://www.cambridge.org/core/terms quences for international reserve accumulation and financial crises. The IMF generates moral hazard asymmetrically, reducing the expected costs of risky lending and policies for states that are politically influential vis-à-vis the institution. Using a panel data set covering 1980 to 2010, we show that proxies for political influence over the IMF are associated with outcomes indicative of moral hazard: lower international reserves and more frequent financial crises. We support our causal claims by applying the synthetic control method to Taiwan, which was expelled from the IMF in 1980. Consistent with our predictions, Taiwan’s expulsion led to a sharp increase in precautionary inter- national reserves and exceptionally conservative financial policies. A large literature has established that the International Monetary Fund (IMF) is heavily politicized.1 Despite considerable shifts in the global balance of economic power, , subject to the Cambridge Core terms of use, available at influence over the IMF has been largely path dependent.2 Several creditor states, particularly the United States and major European countries, continue to exercise out- sized influence over IMF lending.3 This influence exercised by a subset of states in the IMF—through their overrepresented voting shares, personnel, or informal influence— distorts the application of conditional lending, resulting in harsh treatment of some 28 Feb 2019 at 19:11:03 states and lenient policies toward others.