Search

Begin New Search Topic Bias Political Geography Global Focus

1. From Media-Party Linkages to Ownership Concentration: Causes of Cross-National Variation in Media Outlets’ Economic Positioning

Author:
Erik Neimanns and Nils Blossey
Publication Date:
08-2022
Content Type:
Working Paper
Institution:
Max Planck Institute for the Study of Societies
Abstract:
A sizable literature on media bias suggests that media coverage is frequently biased towards certain political and economic positions. However, we know little about what drives variation in political and ideological bias in news coverage across countries. In this paper, we argue that increasingly commercialized and concentrated media markets are likely to be associated with media coverage leaning more favorably towards economically more right-wing positions. Media bias should reflect the preferences of media owners and should be a result of a reduced diversity of news media content. In contrast, where media outlets continue to be oriented more closely along partisan lines, often referred to as political parallelism, bias on economic issues should be more likely to cancel out at the aggregate level. To test these claims, we combine expert survey data on partisan attachments of media outlets, party ideologies, and media ownership concentration for twenty-four European countries. Results from multilevel regression models support our theoretical expectations. With media framing potentially affecting individual-level preferences and perceptions, high and rising levels of media ownership concentration may help to explain why governments in the affluent Western democracies often do remarkably little to counter trends of rising income inequality.
Topic:
Politics, Media, News Analysis, and Bias
Political Geography:
Global Focus

2. Women, Peace & Security, and the Digital Ecosystem: Five Emerging Trends in the Technology and Gender Policy Landscape

Author:
Sahana Dharmapuri and Jolynn Shoemaker
Publication Date:
01-2021
Content Type:
Policy Brief
Institution:
Our Secure Future
Abstract:
While technology offers immense potential for humanity, the digital ecosystem has also revealed a darker side - and it is closely intertwined with gender inequality. From lack of participation and access to gender-based bias, harassment, and abuse, women’s experiences in the technology space and with digital platforms are often amplifying inequalities. These issues are not central priorities for technology leaders or policymakers, much like other facets of society. There are pockets of attention on gender dynamics, but they are siloed from one another, and this has prevented a full picture of the landscape or its broader implications. Despite some calls for values-driven or human-centered technology development, and for embedding human rights into technology policy, international policy frameworks that underscore human rights and gender equality are largely missing from the conversation. The proliferation of disinformation, targeting of women political candidates, or marginalized groups such as LGBTQ+ communities on Twitter, Facebook, TikTok, and other platforms, are repeating patterns and events in the digital ecosystem that have significant consequences for society. We were able to identify these system failures as repeating events that affect at least 50% of technology companies’ end-users--and half of the world’s population. For policymakers, the costs of ignoring these trends could lead to new technology, peace and security structures, processes that weaken core human rights, and gender equality norms and obligations around the world.
Topic:
Science and Technology, Women, Digitalization, WPS, Bias, and Gender
Political Geography:
Global Focus

3. Let's Take the Bias Out of Econometrics

Author:
Duo Qin
Publication Date:
12-2016
Content Type:
Working Paper
Institution:
School of Oriental and African Studies - University of London
Abstract:
This study exposes the cognitive flaws of ‘endogeneity bias’. It reviews how conceptualisation of the bias has evolved to embrace all major econometric problems, despite extensive lack of hard evidence. It reveals the crux of the bias – a priori rejection of causal variables as conditionally valid ones, and of the bias correction by consistent estimators – modification of those variables by non-uniquely and non-causally generated regressors. It traces the flaws to misconceived error terms in statistical modelling and estimation consistency. It highlights the need to shake off the bias to let statistical learning play an active and formal role in econometrics.
Topic:
Economics, Economic Theory, Models, and Bias
Political Geography:
Global Focus