Respectability politics, or the politics of respectability, is a political strategy wherein members of a marginalized community will consciously abandon or punish controversial aspects of their cultural-political identity as a method of assimilating, achieving social mobility,[1] and gaining the respect of the majority culture.[2]
Recently I’ve been thinking a lot about this 2015 observatio...
Recently I’ve been thinking a lot about this 2015 observation on Tumblr about the dangerous conflation of respect of personhood and the respect of authority.
Metanorms generate stable yet adaptable normative social order in a politically decentralized society
Abstract Norms are essential for social stability but can hinder adaptability in changing environments. Yet human societies have found ways to modify existing norms or create new ones in response to novel challenges. This paper proposes a framework for understanding adaptive norm evolution. First, drawing on a theory of legal order, we posit that societies balance normative stability and adaptability through metanorms—rules that govern the process by which norms are interpreted, changed and enforced. Second, we test this idea in the context of customary dispute resolution by elders among the Turkana, a pastoralist society in Kenya. Based on vignette experiments with 369 participants, we found that community members were significantly more willing to enforce decisions when elders aligned their conduct with metanorms. Elders are constrained in their ability to alter long-standing customs, but by following metanorms, they can create new rules for novel situations. These findings support our proposed mechanism: in the absence of centralized authority, metanorms governing normative institutions allow for adaptive norm change while preserving cultural continuity. We conclude by suggesting that group-level selection acts on cultural variation in metanorms, shaping the evolvability of normative systems and enabling societies to sustain adaptive legal order without coercive centralized power. This article is part of the theme issue ‘Transforming cultural evolution research and its application to global futures’.
Recuperation (politics)
In the sociological sense, recuperation is the process by which politically radical ideas and images are twisted, co-opted, absorbed, defused, incorporated, annexed or commodified within media culture and bourgeois society, and thus become interpreted through a neutralized, innocuous or more socially conventional perspective. More broadly, it may refer to the cultural appropriation of any subversive symbols or ideas by mainstream culture.
Think Like a Commoner | A Short Introduction to the Life of the Commons
In our age of predatory markets and make-believe democracy, our troubled political institutions have lost sight of real people and practical realities. But if you look to the edges, ordinary people are reinventing governance and provisioning on their own terms. The commons is arising as a serious, practical alternative to the corrupt Market/State.
Children’s Sense of Fairness as Equal Respect
One influential view holds that children’s sense of fairness emerges at age 8 and is rooted in the development of an aversion to unequal resource distributions. Here, we suggest two amendments to this view. First, we argue and present evidence that children’s sense of fairness emerges already at age 3 in (and only in) the context of collaborative activities. This is because, in our theoretical view, collaboration creates a sense of equal respect among partners. Second, we argue and present evidence that children’s judgments about what is fair are essentially judgments about the social meaning of the distributive act; for example, children accept unequal distributions if the procedure gave everyone an equal chance (so-called distributive justice). Children thus respond to unequal (and other) distributions not based on material concerns, but rather based on interpersonal concerns: they want equal respect.
Community by Design
Social media empower distributed content creation by algorithmically harnessing "the social fabric" (explicit and implicit signals of association) to serve this content. While this overcomes the bottlenecks and biases of traditional gatekeepers, many believe it has unsustainably eroded the very social fabric it depends on by maximizing engagement for advertising revenue. This paper participates in open and ongoing considerations to translate social and political values and conventions, specifically social cohesion, into platform design. We propose an alternative platform model that includes the social fabric an explicit output as well as input. Citizens are members of communities defined by explicit affiliation or clusters of shared attitudes. Both have internal divisions, as citizens are members of intersecting communities, which are themselves internally diverse. Each is understood to value content that bridge (viz. achieve consensus across) and balance (viz. represent fairly) this internal diversity, consistent with the principles of the Hutchins Commission (1947). Content is labeled with social provenance, indicating for which community or citizen it is bridging or balancing. Subscription payments allow citizens and communities to increase the algorithmic weight on the content they value in the content serving algorithm. Advertisers may, with consent of citizen or community counterparties, target them in exchange for payment or increase in that party's algorithmic weight. Underserved and emerging communities and citizens are optimally subsidized/supported to develop into paying participants. Content creators and communities that curate content are rewarded for their contributions with algorithmic weight and/or revenue. We discuss applications to productivity (e.g. LinkedIn), political (e.g. X), and cultural (e.g. TikTok) platforms.
Commoning as a Transformative Social Paradigm | David Bollier
Every so often I am invited to write a piece that in effect answers the question, “Why the commons?” I invariably find new answers to that question each time that I re-engage with it. My latest attempt is an essay, “Commoning as a Transformative Social Paradigm,” which I wrote for the Next System Project as part of its series of proposals for systemic alternatives.
Tolerance Norms Across Countries
Democratic theorists consider respect for pluralism, equality, and inclusion as cornerstones of good democratic citizenship. But what do ordinary citizens belie
How social norms emerge: The interindividual actor–critic.
Evolutionary Political Economy: Content and Methods
In this paper we present the major theoretical and methodological pillars of evolutionary political economy. We proceed in four steps. Aesthetics: In chapter 1 the immediate appeal of evolutionary ...
Fairness is what the powerful ‘can get away with’ study shows
The willingness of those in power to act fairly depends on how easily others can collectively push back against unfair treatment
Ignoring the Unreasonable
Illiberal and antidemocratic political forces, for example, in the form of far-right populism, are on the rise. Such politics, commonly referred to as ‘unreasonable’ in political philosophy, is widely seen as a threat to democracy. Many argue that an adequate response must involve listening to , that is, understanding and seriously considering the perspective of the unreasonable. I disagree. I argue that as democratic citizens, we should not listen to the unreasonable; we should, in a sense, ignore them, that is, refuse to understand and seriously consider their perspective, although continue to monitor their activities. Listening to the unreasonable is not instrumentally required for countering unreasonable politics. In addition, the unreasonable likely have no moral claim to be listened to. Finally, listening to them is disrespectful to reasonable citizens whose voice is ignored for the sake of paying attention to the unreasonable. For these reasons, we should ignore the unreasonable.
The Dispersion of Power: A Critical Realist Theory of Democracy
Abstract The Dispersion of Power is an urgent call to rethink centuries of conventional wisdom about what democracy is, why it matters, and how to make it better. Drawing from history, social science, psychology, and critical theory, it explains why elections do not and cannot realize the classic ideal of popular rule, and why prevailing strategies of democratic reform often make things worse. Instead, Bagg argues, we should see democracy as a way of protecting public power from capture—an alternative vision that is at once more realistic and more inspiring. Despite their many shortcomings, real-world elections do prevent the most extreme forms of tyranny, and are therefore indispensable. In dealing with the vast inequalities that remain, however, we cannot rely on standard solutions such as electoral reform, direct democracy, deliberation, and participatory governance. Instead, Bagg shows, protecting and enriching democracy requires addressing underlying inequalities of power directly. In part, this entails substantive policies attacking the advantages of wealthy elites. Even more crucially, deepening democracy requires the organization of oppositional, countervailing power among ordinary people. Neither task is easy, but historical precedents exist in both cases—and if democracy is to survive contemporary crises, leaders and citizens alike must find ways to revive and reinvent these essential democratic practices for the twenty-first century.
Against Modesty’s Bailey
Modesty arguments often say that you should mostly or entirely bow to ‘expert consensus’ or the views of particular others, and who are you to disagree.
Political Neutrality in AI Is Impossible- But Here Is How to Approximate It
AI systems often exhibit political bias, influencing users' opinions and decisions. While political neutrality-defined as the absence of bias-is often seen as an ideal solution for fairness and safety, this position paper argues that true political neutrality is neither feasible nor universally desirable due to its subjective nature and the biases inherent in AI training data, algorithms, and user interactions. However, inspired by Joseph Raz's philosophical insight that "neutrality [...] can be a matter of degree" (Raz, 1986), we argue that striving for some neutrality remains essential for promoting balanced AI interactions and mitigating user manipulation. Therefore, we use the term "approximation" of political neutrality to shift the focus from unattainable absolutes to achievable, practical proxies. We propose eight techniques for approximating neutrality across three levels of conceptualizing AI, examining their trade-offs and implementation strategies. In addition, we explore two concrete applications of these approximations to illustrate their practicality. Finally, we assess our framework on current large language models (LLMs) at the output level, providing a demonstration of how it can be evaluated. This work seeks to advance nuanced discussions of political neutrality in AI and promote the development of responsible, aligned language models.
Political Neutrality in AI Is Impossible- But Here Is How to Approximate It
AI systems often exhibit political bias, influencing users' opinions and decisions. While political neutrality-defined as the absence of bias-is often seen as an ideal solution for fairness and safety, this position paper argues that true political neutrality is neither feasible nor universally desirable due to its subjective nature and the biases inherent in AI training data, algorithms, and user interactions. However, inspired by Joseph Raz's philosophical insight that "neutrality [...] can be a matter of degree" (Raz, 1986), we argue that striving for some neutrality remains essential for promoting balanced AI interactions and mitigating user manipulation. Therefore, we use the term "approximation" of political neutrality to shift the focus from unattainable absolutes to achievable, practical proxies. We propose eight techniques for approximating neutrality across three levels of conceptualizing AI, examining their trade-offs and implementation strategies. In addition, we explore two concrete applications of these approximations to illustrate their practicality. Finally, we assess our framework on current large language models (LLMs) at the output level, providing a demonstration of how it can be evaluated. This work seeks to advance nuanced discussions of political neutrality in AI and promote the development of responsible, aligned language models.