[1812.00681] Numerical computation of rare events via large deviation theory
An overview of rare events algorithms based on large deviation theory (LDT) is presented. It covers a range of numerical schemes to compute the large deviation minimizer in various setups, and discusses best practices, common pitfalls, and implementation trade-offs. Generalizations, extensions, and improvements of the minimum action methods are proposed. These algorithms are tested on example problems which illustrate several common difficulties which arise e.g. when the forcing is degenerate or multiplicative, or the systems are infinite-dimensional. Generalizations to processes driven by non-Gaussian noises or random initial data and parameters are also discussed, along with the connection between the LDT-based approach reviewed here and other methods, such as stochastic field theory and optimal control. Finally, the integration of this approach in importance sampling methods using e.g. genealogical algorithms is explored.
rare-event_simulation  large_deviation  eric.vanden-eijnden 
21 hours ago
Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks
The performance of neural networks on high-dimensional data distributions suggests that it may be possible to parameterize a representation of a given high-dimensional function with controllably small errors, potentially outperforming standard interpolation methods. We demonstrate, both theoretically and numerically, that this is indeed the case. We map the parameters of a neural network to a system of particles relaxing with an interaction potential determined by the loss function. We show that in the limit that the number of parameters n is large, the landscape of the mean-squared error becomes convex and the representation error in the function scales as O(n−1). In this limit, we prove a dynamical variant of the universal approximation theorem showing that the optimal representation can be attained by stochastic gradient descent, the algorithm ubiquitously used for parameter optimization in machine learning. In the asymptotic regime, we study the fluctuations around the optimal representation and show that they arise at a scale O(n−1). These fluctuations in the landscape identify the natural scale for the noise in stochastic gradient descent. Our results apply to both single and multi-layer neural networks, as well as standard kernel methods like radial basis functions.
interating_particle_system  neural_networks  learning  eric.vanden-eijnden 
22 hours ago
Closing the Gap: The Effect of a Targeted, Tuition-Free Promise on College Choices of High-Achieving, Low-Income Students
Low-income students, even those with strong academic credentials, are unlikely to attend a highly selective college. With a field experiment, we test an intervention to increase enrollment of low-income students at the highly selective University of Michigan. We contact students (as well as their parents and principals) with an encouragement to apply and a promise of four years of free tuition and fees upon admission. Materials emphasize that this offer is not contingent on completing aid applications (e.g., the FAFSA or PROFILE). Treated students were more than twice as likely to apply to (67 percent vs. 26 percent) and enroll at (27 percent vs. 12 percent) the University of Michigan. There was no diversion from schools as (or more) selective as UM. The enrollment effect of 15 percentage points (pp) comprises students who would otherwise attend a less selective, four-year college (7 pp), a community college (4 pp), or no college (4 pp). Effects persist through two years of follow-up. The intervention closed by half the income gaps in college choice among Michigan's high-achieving students. We conclude that an encouragement to apply, paired with a promise of aid, when communicated to students and influential adults, can substantially close income gaps in college choices.
intervention  experimental_design  education  inequality  susan.dynarski 
22 hours ago
Hall of Mirrors: Corporate Philanthropy and Strategic Advocacy
Politicians and regulators rely on feedback from the public when setting policies. For-profit corporations and non-pro t entities are active in this process and are arguably expected to provide independent viewpoints. Policymakers (and the public at large), however, may be unaware of the financial ties between some firms and non-profits - ties that are legal and tax-exempt, but difficult to trace. We identify these ties using IRS forms submitted by the charitable arms of large U.S. corporations, which list all grants awarded to non-pro fits. We document three patterns in a comprehensive sample of public commentary made by firms and non-profits within U.S. federal rulemaking between 2003 and 2015. First, we show that, shortly after a firm donates to a non-profit, the grantee is more likely to comment on rules for which the firm has also provided a comment. Second, when a firm comments on a rule, the comments by non-profits that recently received grants from the firm's foundation are systematically closer in content similarity to the firm's own comments than to those submitted by other non-profits commenting on that rule. This content similarity does not result from similarly-worded comments that express divergent sentiment. Third, when a firm comments on a new rule, the discussion of the final rule is more similar to the firm's comments when the firm's recent grantees also comment on that rule. These patterns, taken together, suggest that corporations strategically deploy charitable grants to induce non-pro fit grantees to make comments that favor their benefactors, and that this translates into regulatory discussion that is closer to the firm's own comments
lobbying_complex  corruption  governance  regulation  political_economy  natural_language_processing  via:nyhan 
22 hours ago
Phys. Rev. Lett. 121, 228301 (2018) - Simplicial Activity Driven Model
Many complex systems find a convenient representation in terms of networks: structures made by pairwise interactions (links) of elements (nodes). For many biological and social systems, elementary interactions involve, however, more than two elements, and simplicial complexes are more adequate to describe such phenomena. Moreover, these interactions often change over time. Here, we propose a framework to model such an evolution: the simplicial activity driven model, in which the building block is a simplex of nodes representing a multiagent interaction. We show analytically and numerically that the use of simplicial structures leads to crucial structural differences with respect to the activity driven model, a paradigmatic temporal network model involving only binary interactions. It also impacts the outcome of paradigmatic processes modeling disease propagation or social contagion. In particular, fluctuations in the number of nodes involved in the interactions can affect the outcome of models of simple contagion processes, contrarily to what happens in the activity driven model.
hypergraph  networks  dynamical_system  for_friends 
2 days ago
Brain-wide Organization of Neuronal Activity and Convergent Sensorimotor Transformations in Larval Zebrafish - ScienceDirect
Simultaneous recordings of large populations of neurons in behaving animals allow detailed observation of high-dimensional, complex brain activity. However, experimental approaches often focus on singular behavioral paradigms or brain areas. Here, we recorded whole-brain neuronal activity of larval zebrafish presented with a battery of visual stimuli while recording fictive motor output. We identified neurons tuned to each stimulus type and motor output and discovered groups of neurons in the anterior hindbrain that respond to different stimuli eliciting similar behavioral responses. These convergent sensorimotor representations were only weakly correlated to instantaneous motor activity, suggesting that they critically inform, but do not directly generate, behavioral choices. To catalog brain-wide activity beyond explicit sensorimotor processing, we developed an unsupervised clustering technique that organizes neurons into functional groups. These analyses enabled a broad overview of the functional organization of the brain and revealed numerous brain nuclei whose neurons exhibit concerted activity patterns.

data  neuroscience  neural_coding_and_decoding  neural_data_analysis  spatio-temporal_statistics  big_data  for_friends  via:? 
2 days ago
[1709.06005v2] TikZ-network manual
TikZ-network is an open source software project for visualizing graphs and networks in LaTeX. It aims to provide a simple and easy tool to create, visualize and modify complex networks. The packaged is based on the PGF/TikZ languages for producing vector graphics from a geometric/algebraic description. Particular focus is made on the software usability and interoperability with other tools. Simple networks can be directly created within LaTeX, while more complex networks can be imported from external sources (e.g. igraph, networkx, QGIS, ...). Additionally, tikz-network supports visualization of multilayer networks in two and three dimensions. The software is available at: this https URL.
latex  packages  networks 
2 days ago
The Violence Trap: A Political-Economic Approach to the Problems of Development by Gary W. Cox, Douglass C. North, Barry R. Weingast :: SSRN
Why do developing countries fail to adopt the institutions and policies that promote development? Our answer is the violence trap. Key political reforms — opening access and reducing rents — are typically feasible only when the domestic economy reaches a given level of complexity (for reasons we specify); yet complex economies typically can emerge only when key political reforms are already in place (for standard reasons). The interdependence of political reform and economic complexity entails violence because, as we show, unreformed polities lack adaptive efficiency. The literature sparked by Lipset’s modernization thesis has operationalized “economic development” as a higher GDP per capita. Building on Steuart, we view development as creating a more complex economy whose workings will be more seriously disrupted by political violence. Empirically, we show that economic complexity (as measured by the Hidalgo-Hausmann index) strongly deters coups, even controlling for GDP per capita and level of democracy.
book  political_economy  economic_history  institutions  social_structure  world_trends 
3 days ago
Violence and Social Orders
All societies must deal with the possibility of violence, and they do so in different ways. This book integrates the problem of violence into a larger social science and historical framework, showing how economic and political behavior are closely linked. Most societies, which we call natural states, limit violence by political manipulation of the economy to create privileged interests. These privileges limit the use of violence by powerful individuals, but doing so hinders both economic and political development. In contrast, modern societies create open access to economic and political organizations, fostering political and economic competition. The book provides a framework for understanding the two types of social orders, why open access societies are both politically and economically more developed, and how some 25 countries have made the transition between the two types.
book  political_economy  economic_history  institutions  social_structure  world_trends 
3 days ago
Random Matrices, Vicious Walkers and Yang-Mills Gauge Theory
-- gist of their argument established over the course of several papers with adequately exhaustive citations with missing references on this work's connections to combinatorics and representation theory.
random_matrix  random_walk  brownian  stochastic_processes  satya.majumdar 
4 days ago
Input–output maps are strongly biased towards simple outputs | Nature Communications
Many systems in nature can be described using discrete input–output maps. Without knowing details about a map, there may seem to be no a priori reason to expect that a randomly chosen input would be more likely to generate one output over another. Here, by extending fundamental results from algorithmic information theory, we show instead that for many real-world maps, the a priori probability P(x) that randomly sampled inputs generate a particular output x decays exponentially with the approximate Kolmogorov complexity 𝐾̃ (𝑥) of that output. These input–output maps are biased towards simplicity. We derive an upper bound P(x) ≲ 2−𝑎𝐾̃ (𝑥)−𝑏, which is tight for most inputs. The constants a and b, as well as many properties of P(x), can be predicted with minimal knowledge of the map. We explore this strong bias towards simple outputs in systems ranging from the folding of RNA secondary structures to systems of coupled ordinary differential equations to a stochastic financial trading model.

--interesting but cannot understand the buzz around this paper.
complexity  information_theory  algorithms  macro_from_micro  ? 
6 days ago
Quantum theory cannot consistently describe the use of itself | Nature Communications
Quantum theory provides an extremely accurate description of fundamental processes in physics. It thus seems likely that the theory is applicable beyond the, mostly microscopic, domain in which it has been tested experimentally. Here, we propose a Gedankenexperiment to investigate the question whether quantum theory can, in principle, have universal validity. The idea is that, if the answer was yes, it must be possible to employ quantum theory to model complex systems that include agents who are themselves using quantum theory. Analysing the experiment under this presumption, we find that one agent, upon observing a particular measurement outcome, must conclude that another agent has predicted the opposite outcome with certainty. The agents’ conclusions, although all derived within quantum theory, are thus inconsistent. This indicates that quantum theory cannot be extrapolated to complex systems, at least not in a straightforward manner.

-- commentary from Aaronson
foundations  quantum_mechanics  quantum_computing 
8 days ago
Opinion | Twitter’s Caste Problem - The New York Times
--post-colonialism meets intersectionality meets multi-culturalism meets international affairs meets...; truly 21st century news article
india  caste_system  gender_studies  queer_studies  post-colonialism  networked_public_sphere  NYTimes 
9 days ago
[1705.02212] Group invariance principles for causal generative models
The postulate of independence of cause and mechanism (ICM) has recently led to several new causal discovery algorithms. The interpretation of independence and the way it is utilized, however, varies across these methods. Our aim in this paper is to propose a group theoretic framework for ICM to unify and generalize these approaches. In our setting, the cause-mechanism relationship is assessed by comparing it against a null hypothesis through the application of random generic group transformations. We show that the group theoretic view provides a very general tool to study the structure of data generating mechanisms with direct applications to machine learning.
causal_inference  groups  machine_learning  statistics 
9 days ago
Are Ideas Getting Harder to Find?
In many growth models, economic growth arises from people creating ideas, and the long-run growth rate is the product of two terms: the effective number of researchers and their research productivity. We present a wide range of evidence from various industries, products, and firms showing that research effort is rising substantially while research productivity is declining sharply. A good example is Moore's Law. The number of researchers required today to achieve the famous doubling every two years of the density of computer chips is more than 18 times larger than the number required in the early 1970s. Across a broad range of case studies at various levels of (dis)aggregation, we find that ideas — and in particular the exponential growth they imply — are getting harder and harder to find. Exponential growth results from the large increases in research effort that offset its declining productivity.

h\t http://slatestarcodex.com/2018/11/26/is-science-slowing-down-2/
science_of_science  science_as_a_social_process  economics  institutions  collective_intention 
10 days ago
How the entire scientific community can confront gender bias in the workplace | Nature Ecology & Evolution
-- At some point, scholars worrying about these issues must take a look at how such policies were implemented in post-independence India. They may not like what they find but at least they can avoid mistakes that we made. Overall, a good summary of existing findings.
gender  discrimination  sociology_of_science  united_states_of_america 
10 days ago
The Model Thinker by Scott E. Page | Basic Books
From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren’t enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models–from linear regression to random walks and far beyond–that can turn anyone into a genius. At the core of the book is Page’s “many-model paradigm,” which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.
book  complexity  methods  scott.page 
11 days ago
Scientific communication in a post-truth society | PNAS
Within the scientific community, much attention has focused on improving communications between scientists, policy makers, and the public. To date, efforts have centered on improving the content, accessibility, and delivery of scientific communications. Here we argue that in the current political and media environment faulty communication is no longer the core of the problem. Distrust in the scientific enterprise and misperceptions of scientific knowledge increasingly stem less from problems of communication and more from the widespread dissemination of misleading and biased information. We describe the profound structural shifts in the media environment that have occurred in recent decades and their connection to public policy decisions and technological changes. We explain how these shifts have enabled unscrupulous actors with ulterior motives increasingly to circulate fake news, misinformation, and disinformation with the help of trolls, bots, and respondent-driven algorithms. We document the high degree of partisan animosity, implicit ideological bias, political polarization, and politically motivated reasoning that now prevail in the public sphere and offer an actual example of how clearly stated scientific conclusions can be systematically perverted in the media through an internet-based campaign of disinformation and misinformation. We suggest that, in addition to attending to the clarity of their communications, scientists must also develop online strategies to counteract campaigns of misinformation and disinformation that will inevitably follow the release of findings threatening to partisans on either end of the political spectrum.

-- restricts itself to a smaller subset of of problems; ignores the fact that politically motivated disinformation and misinformation coexist along side the more innocuous looking, socially sanctioned campaigns of hype conducted researchers and universities themselves.
science_journalism  misinformation  disinformation  public_perception_of_science  review  via:nyhan 
11 days ago
The Theory of Dyadic Morality: Reinventing Moral Judgment by Redefining Harm - Chelsea Schein, Kurt Gray, 2018
The nature of harm—and therefore moral judgment—may be misunderstood. Rather than an objective matter of reason, we argue that harm should be redefined as an intuitively perceived continuum. This redefinition provides a new understanding of moral content and mechanism—the constructionist Theory of Dyadic Morality (TDM). TDM suggests that acts are condemned proportional to three elements: norm violations, negative affect, and—importantly—perceived harm. This harm is dyadic, involving an intentional agent causing damage to a vulnerable patient (A→P). TDM predicts causal links both from harm to immorality (dyadic comparison) and from immorality to harm (dyadic completion). Together, these two processes make the “dyadic loop,” explaining moral acquisition and polarization. TDM argues against intuitive harmless wrongs and modular “foundations,” but embraces moral pluralism through varieties of values and the flexibility of perceived harm. Dyadic morality impacts understandings of moral character, moral emotion, and political/cultural differences, and provides research guidelines for moral psychology.

-- directly positions itself against Rozin's disgust based approach to moral judgments.
moral_psychology  judea.pearl  taboo-_trade-offs  debates 
11 days ago
Fairness and Abstraction in Sociotechnical Systems by Andrew D. Selbst, danah boyd, Sorelle Friedler, Suresh Venkatasubramanian, Janet Vertesi :: SSRN
A key goal of the FAT* community is to develop machine-learning based systems that, once introduced into a social context, can achieve social and legal outcomes such as fairness, justice, and due process. Bedrock concepts in computer science—such as abstraction and modular design—are used to define notions of fairness and discrimination, to produce fairness-aware learning algorithms, and to intervene at different stages of a decision-making pipeline to produce "fair" outcomes. In this paper, however, we contend that these concepts render technical interventions ineffective, inaccurate, and sometimes dangerously misguided when they enter the societal context that surrounds decision-making systems. We outline this mismatch with five "traps" that fair-ML work can fall into even as it attempts to be more context-aware in comparison to traditional data science. We draw on studies of sociotechnical systems in Science and Technology Studies to explain why such traps occur and how to avoid them. Finally, we suggest ways in which technical designers can mitigate the traps through a refocusing of design in terms of process rather than solutions, and by drawing abstraction boundaries to include social actors rather than purely technical ones.
algorithms  machine_learning  ethics  technology  dana.boyd 
12 days ago
[1804.10068] Quantum machine learning for data scientists
This text aims to present and explain quantum machine learning algorithms to a data scientist in an accessible and consistent way. The algorithms and equations presented are not written in rigorous mathematical fashion, instead, the pressure is put on examples and step by step explanation of difficult topics. This contribution gives an overview of selected quantum machine learning algorithms, however there is also a method of scores extraction for quantum PCA algorithm proposed as well as a new cost function in feed-forward quantum neural networks is introduced. The text is divided into four parts: the first part explains the basic quantum theory, then quantum computation and quantum computer architecture are explained in section two. The third part presents quantum algorithms which will be used as subroutines in quantum machine learning algorithms. Finally, the fourth section describes quantum machine learning algorithms with the use of knowledge accumulated in previous parts.

-- Ah, even before they have anything useful to offer, there is an article aimed at the data scientists! Not recommended (I did not read it)
quantum_computing  machine_learning  review 
13 days ago
Quantum machine learning | Nature
Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

-- recommend Aaronson's moderation along with this paper
quantum_computing  machine_learning  review 
13 days ago
Why Do Women Earn Less Than Men? Evidence from Bus and Train Operators (Job Market Paper) | Valentin Bolotnyy
Even in a unionized environment where work tasks are similar, hourly wages are identical, and tenure dictates promotions, female workers earn $0.89 on the male-worker dollar (weekly earnings). We use confidential administrative data on bus and train operators from the Massachusetts Bay Transportation Authority (MBTA) to show that the weekly earnings gap can be explained entirely by the workplace choices that women and men make. Women value time and flexibility more than men, possibly due to a combination of preferences and personal life constraints. Women take more unpaid time off using the Family Medical Leave Act (FMLA) and work fewer overtime hours than men. When overtime hours are scheduled three months in advance, men and women work a similar number of hours; but when those hours are offered at the last minute, men work nearly twice as many overtime hours. When selecting work schedules, women try to avoid weekend, holiday, and split shifts more than men. To avoid unfavorable work times, women prioritize their schedules over route safety and select routes with a higher probability of accidents. Women are less likely than men to game the scheduling system by trading off work hours at regular wages for overtime hours at premium wages. Conditional on seniority, which dictates choice sets, the weekly earnings gap can be explained entirely by differences in operator choices of hours, schedules, and routes. These results suggest that some policies that increase workplace flexibility, like shift swapping, can reduce the gender earnings gap and disproportionately increase the well-being of female workers.
gender  income  discrimination  debates  economic_sociology  econometrics 
14 days ago
Common-Knowledge Attacks on Democracy by Henry Farrell, Bruce Schneier :: SSRN
Existing approaches to cybersecurity emphasize either international state-to-state logics (such as deterrence theory) or the integrity of individual information systems. Neither provides a good understanding of new “soft cyber” attacks that involve the manipulation of expectations and common understandings. We argue that scaling up computer security arguments to the level of the state, so that the entire polity is treated as an information system with associated attack surfaces and threat models, provides the best immediate way to understand these attacks and how to mitigate them. We demonstrate systematic differences between how autocracies and democracies work as information systems, because they rely on different mixes of common and contested political knowledge. Stable autocracies will have common knowledge over who is in charge and their associated ideological or policy goals, but will generate contested knowledge over who the various political actors in society are, and how they might form coalitions and gain public support, so as to make it more difficult for coalitions to displace the regime. Stable democracies will have contested knowledge over who is in charge, but common knowledge over who the political actors are, and how they may form coalitions and gain public support. These differences are associated with notably different attack surfaces and threat models. Specifically, democracies are vulnerable to measures that “flood” public debate and disrupt shared decentralized understandings of actors and coalitions, in ways that autocracies are not.
democracy  collective_cognition  common_knowledge  cybernetics  distributed_computing  henry.farrell 
14 days ago
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
We put forth a deep learning approach for discovering nonlinear partial differential equations from scattered and potentially noisy observations in space and time. Specifically, we approximate the unknown solution as well as the nonlinear dynamics by two deep neural networks. The first network acts as a prior on the unknown solution and essentially enables us to avoid numerical differentiations which are inherently ill-conditioned and unstable. The second network represents the nonlinear dynamics and helps us distill the mechanisms that govern the evolution of a given spatiotemporal data-set. We test the effectiveness of our approach for several benchmark problems spanning a number of scientific domains and demonstrate how the proposed framework can help us accurately learn the underlying dynamics and forecast future states of the system. In particular, we study the Burgers', Korteweg-de Vries (KdV), Kuramoto-Sivashinsky, nonlinear Schrödinger, and Navier-Stokes equations.

-- Too good to be true... but then again, I have not read the details of this nano-industry. Maybe there is something worthwhile hidden...
deep_learning  machine_learning  pde  nonlinear_dynamics  i_remain_skeptical 
15 days ago
The Effect of Media Coverage on Mass Shootings | IZA - Institute of Labor Economics
Can media coverage of shooters encourage future mass shootings? We explore the link between the day-to-day prime time television news coverage of shootings on ABC World News Tonight and subsequent mass shootings in the US from January 1, 2013 to June 23, 2016. To circumvent latent endogeneity concerns, we employ an instrumental variable strategy: worldwide disaster deaths provide an exogenous variation that systematically crowds out shooting-related coverage. Our findings consistently suggest a positive and statistically significant effect of coverage on the number of subsequent shootings, lasting for 4-10 days. At its mean, news coverage is suggested to cause approximately three mass shootings in the following week, which would explain 55 percent of all mass shootings in our sample. Results are qualitatively consistent when using (i) additional keywords to capture shooting-related news coverage, (ii) alternative definitions of mass shootings, (iii) the number of injured or killed people as the dependent variable, and (iv) an alternative, longer data source for mass shootings from 2006-2016.

--Is it really this easy?
crime  contagion  social_influence  econometrics  causal_inference  i_remain_skeptical  media_studies 
16 days ago
The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility
We construct a publicly available atlas of children's outcomes in adulthood by Census tract using anonymized longitudinal data covering nearly the entire U.S. population. For each tract, we estimate children's earnings distributions, incarceration rates, and other outcomes in adulthood by parental income, race, and gender. These estimates allow us to trace the roots of outcomes such as poverty and incarceration back to the neighborhoods in which children grew up. We find that children's outcomes vary sharply across nearby areas: for children of parents at the 25th percentile of the income distribution, the standard deviation of mean household income at age 35 is $5,000 across tracts within counties. We illustrate how these tract-level data can provide insight into how neighborhoods shape the development of human capital and support local economic policy using two applications. First, the estimates permit precise targeting of policies to improve economic opportunity by uncovering specific neighborhoods where certain subgroups of children grow up to have poor outcomes. Neighborhoods matter at a very granular level: conditional on characteristics such as poverty rates in a child's own Census tract, characteristics of tracts that are one mile away have little predictive power for a child's outcomes. Our historical estimates are informative predictors of outcomes even for children growing up today because neighborhood conditions are relatively stable over time. Second, we show that the observational estimates are highly predictive of neighborhoods' causal effects, based on a comparison to data from the Moving to Opportunity experiment and a quasi-experimental research design analyzing movers' outcomes. We then identify high-opportunity neighborhoods that are affordable to low- income families, providing an input into the design of affordable housing policies. Our measures of children's long-term outcomes are only weakly correlated with traditional proxies for local economic success such as rates of job growth, showing that the conditions that create greater upward mobility are not necessarily the same as those that lead to productive labor markets.

inequality  geography  economics  spatio-temporal_statistics  raj.chetty 
18 days ago
The Oversocialized Conception of Man in Modern Sociology on JSTOR
"Sociological theory originates in the asking of general questions about man and society. The answers lose their meaning if they are elaborated without reference to the questions, as has been the case in much contemporary theory. An example is the Hobbesian question of how men become tractable to social controls. The two-fold answer of contemporary theory is that man 'internalizes' social norms and seeks a favorable self-image by conforming to the 'expectations' of others. Such a model of man denies the very possibility of his being anything but a thoroughly socialized being and thus denies the reality of the Hobbesian question. The Freudian view of man, on the other hand, which sociologists have misrepresented, sees man as a social though never a fully socialized creature. Sociologists need to develop a more complex, dialectical conception of human nature." Man's nature is the source of conflicts creating resistances to socialization.

sociology  critique  nature-nurture  debates 
19 days ago
Bots increase exposure to negative and inflammatory content in online social systems | PNAS
Social media can deeply influence reality perception, affecting millions of people’s voting behavior. Hence, maneuvering opinion dynamics by disseminating forged content over online ecosystems is an effective pathway for social hacking. We propose a framework for discovering such a potentially dangerous behavior promoted by automatic users, also called “bots,” in online social networks. We provide evidence that social bots target mainly human influencers but generate semantic content depending on the polarized stance of their targets. During the 2017 Catalan referendum, used as a case study, social bots generated and promoted violent content aimed at Independentists, ultimately exacerbating social conflict online. Our results open challenges for detecting and controlling the influence of such content on society.
bots  misinformation  disinformation  networked_public_sphere  journalism  via:nyhan 
21 days ago
How Political Opinions Change - Scientific American
-- the article is framed to suggest that people's opinion can be manipulated. Deeper political beliefs and attitudes may still be resilient to superficial interventions. Also, the results suggest that in the current media environment, public opinion swings might be a result of such mechanisms.

-- one swallow doesn't make a summer
political_psychology  public_opinion  via:nyhan 
21 days ago
Phys. Rev. A 8, 1429 (1973) - Rotational Brownian Motion. II. Fourier Transforms for a Spherical Body with Strong Interactions
Laplace and Fourier transforms of the distribution function for orientation, and related correlation functions, for a spherical body undergoing rotational Brownian motion are calculated by solving partial differential equations governing their behavior. Also calculated is the Fourier transform of a correlation function involving both the orientation and angular velocity of a spherical body, which occurs in the theory of spin relaxation by spin-rotational interactions. The solutions obtained are the first few terms of infinite series, which appear to converge rapidly if the frictional retarding torque acting on the body is sufficiently large. The first term in each series is identical to results obtained by use of a rotational diffusion equation. From experimental values of the correlation times for reorientation of fairly small molecules in liquids, it is inferred that the solutions obtained here are probably applicable, and that the higher-order terms calculated here may be important.
diffusion  differential_geometry  fokker-planck 
22 days ago
Phys. Rev. A 6, 2421 (1972) - Rotational Brownian Motion
A Fokker-Planck equation for the joint probability density of the orientation and angular velocity of a body of general shape is derived by use of a rotational Langevin equation. Equations governing the seperate distributions of orientation and angular velocity are deduced from the equation for the joint probability density. For the special case of a spherical body, two expressions for the orientation distribution are calculated, one valid for small values of the frictional constant occurring in the rotational Langevin equation, and the other valid for large values of the frictional constant. The latter expression includes previously presented results of rotational-diffusion theory and Steele's modification of rotational-diffusion theory, and the calculation provides conditions of validity for these theories. Expressions are calculated for time-correlation functions of spherical tensors, such as spherical harmonics, which involve functions of the orientation of a body.
diffusion  differential_geometry  fokker-planck 
22 days ago
Rotational Brownian motion - IOPscience
A survey of the present state of the theory of rotational Brownian motion is given. Chapters 1 and 2 expound the theory of rotational diffusion and the solution of the problem of rotational random walks. The probability distributions for the orientations of Brownian particles are written in terms of generalized spherical functions, which are matrix elements of irreducible representations of the rotation group. Methods are discussed for the experimental determination of the nature of Brownian rotation by the use of nuclear magnetic resonance, dielectric relaxation, and the Rayleigh scattering of light. Chapter 3 gives an exposition of generalized rotational diffusion, taking account of inertial effects in the Brownian motion. The influence of inertial effects on dielectric magnetic relaxation and on the scattering of light is discussed. The conclusion of the review gives a discussion of precession effects in Brownian motion.
diffusion  differential_geometry  fokker-planck 
22 days ago
Mean first-passage times of Brownian motion and related problems | Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences
The theory of first-passage times of Brownian motion is developed in general, and it is shown that for certain special boundaries—the only ones of any importance—mean first-passage times can be derived very simply, avoiding the usual method involving series. Moreover, these formulae have a close analytical relationship to the better-known type of formulae for average 'displacements’ in given intervals; there exist certain pairs of reciprocal relations. Some new formulae, of mathematical interest, for translational Brownian motion are given. The main application of the general theory, however, lies in the derivation of experimentally particularly useful formulae for rotational Brownian motion. Special cases when external forces are present, and mean reciprocal first-passage times are discussed briefly, and finally it is shown how finite times of observation modify the mean first-passage time formulae of free Brownian motion.
diffusion  differential_geometry  fokker-planck 
22 days ago
Phys. Rev. 119, 53 (1960) - Theory of the Rotational Brownian Motion of a Free Rigid Body
The orientation of a rigid body is specified by the Cayley-Klein parameters. A system of such bodies subject to small random changes in orientation but not subject to any externally applied torque is then considered in some detail. A diffusion equation is derived with certain linear combinations of the Cayley-Klein parameters as independent variables. This equation is expressed in terms of quantum-mechanical angular momentum operators and a Green's function for the equation is obtained as an expansion in angular momentum eigenfunctions. This expansion can be used to calculate averages of various physical quantities in a nonequilibrium distribution of orientations. It may also be used to calculate the spectral density of fluctuating quantities in an equilibrium distribution. Illustrative examples of both of these applications are given.
diffusion  differential_geometry  fokker-planck 
22 days ago
[1811.05008] Choosing to grow a graph: Modeling network formation as discrete choice
We provide a framework for modeling social network formation through conditional multinomial logit models from discrete choice and random utility theory, in which each new edge is viewed as a "choice" made by a node to connect to another node, based on (generic) features of the other nodes available to make a connection. This perspective on network formation unifies existing models such as preferential attachment, triadic closure, and node fitness, which are all special cases, and thereby provides a flexible means for conceptualizing, estimating, and comparing models. The lens of discrete choice theory also provides several new tools for analyzing social network formation; for example, mixtures of existing models can be estimated by adapting known expectation-maximization algorithms, and the significance of node features can be evaluated in a statistically rigorous manner. We demonstrate the flexibility of our framework through examples that analyze a number of synthetic and real-world datasets. For example, we provide rigorous methods for estimating preferential attachment models and show how to separate the effects of preferential attachment and triadic closure. Non-parametric estimates of the importance of degree show a highly linear trend, and we expose the importance of looking carefully at nodes with degree zero. Examining the formation of a large citation graph, we find evidence for an increased role of degree when accounting for age.

--seems related to some of M.O. Jackson's constructions...
networks  dynamics  optimization  game_theory  via:clauset 
25 days ago
The policy consequences of cascade blindness | Behavioural Public Policy | Cambridge Core
One way to reduce waste and to make a system more robust is to allow its components to pool resources. For example, banks might insure each other or share a common capital reserve. Systems whose resources have been pooled in this way are highly prevalent in such diverse domains as finance, infrastructure, health care, emergency response and engineering. However, these systems have a combination of characteristics that leave them vulnerable to poor decision-making: non-linearity of risk; obvious rewards combined with hidden costs; and political and market incentives that encourage inadequate safety margins. Three studies demonstrate a tendency for managers of such systems to underestimate the probability of cascading failures. We describe a series of behaviorally based policy interventions to mitigate the resulting hazards.
risk_assessment  bureaucracy  administrative_state  complex_system  public_policy  for_friends 
25 days ago
The Kinds of Data Scientist
-- they forgot to include the data scientists that call out snake oil salesmanship and the ones who worry about ethics.
big_data  data_science  statistics  machine_learning 
27 days ago
Social Influence Bias: A Randomized Experiment | Science
Our society is increasingly relying on the digitized, aggregated opinions of others to make decisions. We therefore designed and analyzed a large-scale randomized experiment on a social news aggregation Web site to investigate whether knowledge of such aggregates distorts decision-making. Prior ratings created significant bias in individual rating behavior, and positive and negative social influences created asymmetric herding effects. Whereas negative social influence inspired users to correct manipulated ratings, positive social influence increased the likelihood of positive ratings by 32% and created accumulating positive herding that increased final ratings by 25% on average. This positive herding was topic-dependent and affected by whether individuals were viewing the opinions of friends or enemies. A mixture of changing opinion and greater turnout under both manipulations together with a natural tendency to up-vote on the site combined to create the herding effects. Such findings will help interpret collective judgment accurately and avoid social influence bias in collective intelligence in the future.
crowd_sourcing  judgment_decision-making  social_influence  social_networks  teaching  online_experiments  sinan.aral 
27 days ago
Search in External and Internal Spaces: Evidence for Generalized Cognitive Search Processes - Thomas T. Hills, Peter M. Todd, Robert L. Goldstone, 2008
There is compelling molecular and behavioral evidence that goal-directed cognition is an evolutionary descendant of spatial-foraging behavior. Across animal species, similar dopaminergic processes modulate between exploratory and exploitative foraging behaviors and control attention. Consequently, we hypothesized that spatialforaging activity could prime attentional cognitive activity. We examined how searching in physical space influences subsequent search in abstract cognitive space by presenting participants with a spatial-foraging task followed by a repeated Scrabble task involving search for words that could be made from letter sets. Participants who searched through clumpier distributions in space behaved as if words were more densely clumped in the Scrabble task. This was not a function of arousal, but was consistent with predictions of optimal-foraging theory. Furthermore, individual differences in exploratory search were conserved across the two types of tasks. Along with the biological evidence, our results support the idea that there are generalized cognitive search processes.
cognition  cognitive_science  dynamical_system  markov_models  learning  decison_theory 
27 days ago
PsyArXiv Preprints | Rationality without optimality: Bounded and ecological rationality from a Marrian perspective
Ecological rationality provides an alternative to the view that rational responses to environmental uncertainty are optimal probabilistic responses. Focusing on the ecological rationality of simple heuristics, critics have enlisted Marr's levels of analysis and the distinction between function and mechanism to argue that the study of ecological rationality addresses the question of how organisms make decisions, but not the question of what constitutes a rational decision and why. The claim is that the insights of ecological rationality are, after the fact, reducible to instances of optimal Bayesian inference and require principles of Bayesian rationality to explain. Here, I respond to these critiques by clarifying that ecological rationality is more than a set of algorithmic conjectures. It is also driven by statistical commitments governing the treatment of unquantifiable uncertainty. This statistical perspective establishes why ecological rationality is distinct from Bayesian optimality, is incompatible with Marr's levels of analysis, and undermines a strict separation of function and mechanism. This argument finds support in Marr's broader but largely overlooked views on information processing systems and Savage's stance on the limits on Bayesian decision theory. Rationality principles make assumptions, and ecological rationality assumes that environmental uncertainty can render optimal probabilistic responses indeterminable.
bayesian  cognitive_science  rational_choice  rationality  critique 
27 days ago
[1811.02071] Scale-free Networks Well Done
We bring rigor to the vibrant activity of detecting power laws in empirical degree distributions in real-world networks. We first provide a rigorous definition of power-law distributions, equivalent to the definition of regularly varying distributions in statistics. This definition allows the distribution to deviate from a pure power law arbitrarily but without affecting the power-law tail exponent. We then identify three estimators of these exponents that are proven to be statistically consistent -- that is, converging to the true exponent value for any regularly varying distribution -- and that satisfy some additional niceness requirements. Finally, we apply these estimators to a representative collection of synthetic and real-world data. According to their estimates, real-world scale-free networks are definitely not as rare as one would conclude based on the popular but unrealistic assumption that real-world data comes from power laws of pristine purity, void of noise and deviations.

-- academic snark at its best; this is going to fun
networks  statistics  debates 
28 days ago
OSF Preprints | Explanation, prediction, and causality: Three sides of the same coin?
In this essay we make four interrelated points. First, we reiterate previous arguments (Kleinberg et al 2015) that forecasting problems are more common in social science than is often appreciated. From this observation it follows that social scientists should care about predictive accuracy in addition to unbiased or consistent estimation of causal relationships. Second, we argue that social scientists should be interested in prediction even if they have no interest in forecasting per se. Whether they do so explicitly or not, that is, causal claims necessarily make predictions; thus it is both fair and arguably useful to hold them accountable for the accuracy of the predictions they make. Third, we argue that prediction, used in either of the above two senses, is a useful metric for quantifying progress. Important differences between social science explanations and machine learning algorithms notwithstanding, social scientists can still learn from approaches like the Common Task Framework (CTF) which have successfully driven progress in certain fields of AI over the past 30 years (Donoho, 2015). Finally, we anticipate that as the predictive performance of forecasting models and explanations alike receives more attention, it will become clear that it is subject to some upper limit which lies well below deterministic accuracy for many applications of interest (Martin et al 2016). Characterizing the properties of complex social systems that lead to higher or lower predictive limits therefore poses an interesting challenge for computational social science.
social_science  prediction  explanation  forecasting  causality  philosophy_of_science  duncan.watts  for_friends  teaching 
28 days ago
Norms in the Wild - Paperback - Cristina Bicchieri - Oxford University Press
The philosopher Cristina Bicchieri here develops her theory of social norms, most recently explained in her 2006 volume The Grammar of Society. Bicchieri challenges many of the fundamental assumptions of the social sciences. She argues that when it comes to human behavior, social scientists place too much stress on rational deliberation. In fact, many choices occur without much deliberation at all. Bicchieri's theory accounts for these automatic components of behavior, where individuals react automatically to cues--those cues often pointing to the social norms that govern our choices in a social world

Bicchieri's work has broad implications not only for understanding human behavior, but for changing it for better outcomes. People have a strong conditional preference for following social norms, but that also means manipulating those norms (and the underlying social expectations) can produce beneficial behavioral changes. Bicchieri's recent work with UNICEF has explored the applicability of her views to issues of human rights and well-being. Is it possible to change social expectations around forced marriage, genital mutilations, and public health practices like vaccinations and sanitation? If so, how? What tools might we use? This short book explores how social norms work, and how changing them--changing preferences, beliefs, and especially social expectations--can potentially improve lives all around the world.

--To-do: compare with Ullmann-Margalit's work. Don't remember the exact connections...
book  norms  dynamics  social_behavior  homophily  contagion  social_influence  networks  social_networks  teaching 
28 days ago
The Institutional Turn in Comparative Authoritarianism | British Journal of Political Science | Cambridge Core
The institutional turn in comparative authoritarianism has generated wide interest. This article reviews three prominent books on authoritarian institutions and their central theoretical propositions about the origins, functions and effects of dominant party institutions on authoritarian rule. Two critical perspectives on political institutions, one based on rationalist theories of institutional design and the other based on a social conflict theory of political economy, suggest that authoritarian institutions are epiphenomenal on more fundamental political, social and/or economic relations. Such approaches have been largely ignored in this recent literature, but each calls into question the theoretical and empirical claims that form the basis of institutionalist approaches to authoritarian rule. A central implication of this article is that authoritarian institutions cannot be studied separately from the concrete problems of redistribution and policy making that motivate regime behavior.
comparative  political_science  authoritarianism  institutions  review  via:henryfarrell 
4 weeks ago
Nicholas Shea, Representation in Cognitive Science - PhilArchive
"How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences."
via:cshalizi  book  philosophy_of_science  cognitive_science 
4 weeks ago
Relationship of gender differences in preferences to economic development and gender equality | Science
What contributes to gender-associated differences in preferences such as the willingness to take risks, patience, altruism, positive and negative reciprocity, and trust? Falk and Hermle studied 80,000 individuals in 76 countries who participated in a Global Preference Survey and compared the data with country-level variables such as gross domestic product and indices of gender inequality. They observed that the more that women have equal opportunities, the more they differ from men in their preferences.
debates  labor  gender  economics  survey  world_trends  nature-nurture 
4 weeks ago
Glia as architects of central nervous system formation and function | Science
Glia constitute roughly half of the cells of the central nervous system (CNS) but were long-considered to be static bystanders to its formation and function. Here we provide an overview of how the diverse and dynamic functions of glial cells orchestrate essentially all aspects of nervous system formation and function. Radial glia, astrocytes, oligodendrocyte progenitor cells, oligodendrocytes, and microglia each influence nervous system development, from neuronal birth, migration, axon specification, and growth through circuit assembly and synaptogenesis. As neural circuits mature, distinct glia fulfill key roles in synaptic communication, plasticity, homeostasis, and network-level activity through dynamic monitoring and alteration of CNS structure and function. Continued elucidation of glial cell biology, and the dynamic interactions of neurons and glia, will enrich our understanding of nervous system formation, health, and function.
neuroscience  review  philosophy_of_science 
4 weeks ago
The Power of the Normal by Cass R. Sunstein :: SSRN
How do judgments about law and morality shift? Why do we come to see conduct as egregiously wrong, when we had formerly seen it as merely inappropriate or even unobjectionable? Why do shifts occur in the opposite direction? A clue comes from the fact that some of our judgments are unstable, in the sense that they are an artifact of, or endogenous to, what else we see. This is true of sensory perception: Whether an object counts as blue or purple depends on what other objects surround it. It is also true for ethical judgments: Whether conduct counts as unethical depends on what other conduct is on people’s viewscreens. It follows that conduct that was formerly seen as ethical may come to seem unethical, as terrible behavior becomes less common, and also that conduct that was formerly seen as unethical may come to seem ethical, as terrible behavior becomes more common. In these circumstances, law (and enforcement practices) can have an important signaling effect, giving people a sense of what is normal and what is not. There is an important supplemental point, intensifying these effects: Once conduct comes to be seen as part of an unacceptable category – abusiveness, racism, lack of patriotism, microaggression, sexual harassment – real or apparent exemplars that are not so egregious, or perhaps not objectionable at all, might be taken as egregious, because they take on the stigma now associated with the category. Stigmatization by categorization can intensify the process by which formerly unobjectionable behavior becomes regarded as abhorrent. There is a relationship between stigmatization by categorization and “concept creep,” an idea applied in psychology to shifting understandings of such concepts as abuse, bullying, mental illness, and prejudice.

--Sunstein-ian repackaging of really old ideas from psychology of disgust (Rozin) and his & Kuran's work.
cass.sunstein  norms  dynamics  law  moral_psychology  social_movements  cultural_evolution  dmce  social_networks 
4 weeks ago
They saw a game; a case study
When the Dartmouth football team played Princeton in 1951, much controversy was generated over what actually took place during the game. Basically, there was disagreement between the two schools as to what had happened during the game. A questionnaire designed to get reactions to the game and to learn something of the climate of opinion was administered at each school and the same motion picture of the game was shown to a sample of undergraduate at each school, followed by another questionnnaire. Results indicate that the "game" was actually many different games and that each version of the events that transpired was just as "real" to a particular person as other versions were to other people.

groups  judgment_decision-making  collective_cognition  cultural_cognition  dmce  teaching  via:nyhan 
4 weeks ago
The Oxford Handbook of the Science of Science Communication - Kathleen Hall Jamieson; Dan Kahan; Dietram A. Scheufele - Oxford University Press
The proposal to vaccinate adolescent girls against the human papilloma virus ignited political controversy, as did the advent of fracking and a host of other emerging technologies. These disputes attest to the persistent gap between expert and public perceptions. Complicating the communication of sound science and the debates that surround the societal applications of that science is a changing media environment in which misinformation can elicit belief without corrective context and likeminded individuals are prone to seek ideologically comforting information within their own self-constructed media enclaves.

Drawing on the expertise of leading science communication scholars from six countries, The Oxford Handbook of the Science of Science Communication not only charts the media landscape - from news and entertainment to blogs and films - but also examines the powers and perils of human biases - from the disposition to seek confirming evidence to the inclination to overweight endpoints in a trend line. In the process, it draws together the best available social science on ways to communicate science while also minimizing the pernicious effects of human bias.

The Handbook adds case studies exploring instances in which communication undercut or facilitated the access to scientific evidence. The range of topics addressed is wide, from genetically engineered organisms and nanotechnology to vaccination controversies and climate change. Also unique to this book is a focus on the complexities of involving the public in decision making about the uses of science, the regulations that should govern its application, and the ethical boundaries within which science should operate. The Handbook is an invaluable resource for researchers in the communication fields, particularly in science and health communication, as well as to scholars involved in research on scientific topics susceptible to distortion in partisan debate.
cultural_cognition  communication  social_construction_of_ignorance  social_construction_of_knowledge  sociology_of_science  dan.kahan  book 
4 weeks ago
A Duty to Resist - Candice Delmas - Oxford University Press
What are our responsibilities in the face of injustice? How far should we go to fight it? Many would argue that as long as a state is nearly just, citizens have a moral duty to obey the law. Proponents of civil disobedience generally hold that, given this moral duty, a person needs a solid justification to break the law. But activists from Henry David Thoreau and Mohandas Gandhi to the Movement for Black Lives have long recognized that there are times when, rather than having a duty to obey the law, we have a duty to disobey it.

Taking seriously the history of this activism, A Duty to Resist wrestles with the problem of political obligation in real world societies that harbor injustice. Candice Delmas argues that the duty of justice, the principle of fairness, the Samaritan duty, and political association impose responsibility to resist under conditions of injustice. We must expand political obligation to include a duty to resist unjust laws and social conditions even in legitimate states.

For Delmas, this duty to resist demands principled disobedience, and such disobedience need not always be civil. At times, covert, violent, evasive, or offensive acts of lawbreaking can be justified, even required. Delmas defends the viability and necessity of illegal assistance to undocumented migrants, leaks of classified information, distributed denial-of-service (DDoS) attacks, sabotage, armed self-defense, guerrilla art, and other modes of resistance. There are limits: principle alone does not justify law breaking. But uncivil disobedience can sometimes be not only permissible but required in the effort to resist injustice.


-- both the book and the review feels disconnected with how *uncivil disobedience* manifests itself in the real world, I mean the world that is not Europe or North America. *Uncivil Disobedience* without devolution into prolonged violence and terrorism is Utopian fairy tale territory.
book  political_philosophy  political_science  civil_disobidience  protests  terrorism 
5 weeks ago
« earlier      
2016 20th_century 21st_century ? academia active_matter administrative_state algorithms alt-right andrew.gelman anthropology artificial_intelligence autocracy automation bayesian behavior behavioral_economics bias big_data biology black_history blog book book_review brendan.nyhan bureaucracy capitalism causal_inference causality cities civil_rights cognition cognitive_science collective_action collective_cognition collective_dynamics collective_intention comparative complex_system computaional_advertising conspiracy_theories contagion contemporary_culture course crime criminal_justice critical_theory critique cultural_cognition cultural_evolution cultural_history cybersecurity data debates deep_learning democracy differential_geometry discrimination disinformation dmce dynamical_system dynamics econometrics economic_geography economic_history economic_sociology economics education epidemiology ethics european_politics evolutionary_biology evolutionary_psychology experimental_design experiments expert_judgment extremism feminism for_friends freedom_of_speech gafa game_theory gender genetics geography global_politics globalization governance graphical_models groups health heuristics historical_sociology history history_of_ideas homophily human_progress i_remain_skeptical ideology immigration india inequality influence institutions interating_particle_system international_affairs intervention journalism judgment_decision-making labor law learning liberalism machine_learning macroeconomics market_failures market_microstructure mathematics media_studies meta-analysis methods microeconomics misinformation moral_economy moral_psychology nap nationalism nature-nurture network_data_analysis networked_life networked_public_sphere networks neuroscience news_media non-equilibrium norms nytimes online_experiments packages people phase_transition philosophy philosophy_of_biology philosophy_of_science physics polarization policing policy political_economy political_psychology political_science political_sociology post-modernism poverty prediction privacy probability protests psychology public_opinion public_policy public_sphere quanta_mag race rational_choice regulation replication_of_studies report review right-wing_populism russia self_organization sentiment_analysis slavery social_behavior social_construction_of_knowledge social_media social_movements social_networks social_psychology social_science socialism sociology sociology_of_science software statistical_mechanics statistics stochastic_process surveillance survey teaching technology the_atlantic the_civilizing_process time_series trumpism twitter united_states_of_america university us_conservative_thought us_elections us_politics via:? via:cshalizi via:henryfarrell via:noahpinion via:nyhan via:pinker via:sunstein via:wolfers via:zeynep virtue_signaling vox wapo world_trends

Copy this bookmark: