12004
[1503.06772] Assembling thefacebook: Using heterogeneity to understand online social network assembly
"Online social networks represent a popular and highly diverse class of social media systems. Despite this variety, each of these systems undergoes a general process of online social network assembly, which represents the complicated and heterogeneous changes that transform newly born systems into mature platforms. However, little is known about this process. For example, how much of a network's assembly is driven by simple growth? How does a network's structure change as it matures? How does network structure vary with adoption rates and user heterogeneity, and do these properties play different roles at different points in the assembly? We investigate these and other questions using a unique dataset of online connections among the roughly one million users at the first 100 colleges admitted to Facebook, captured just 20 months after its launch. We first show that different vintages and adoption rates across this population of networks reveal temporal dynamics of the assembly process, and that assembly is only loosely related to network growth. We then exploit natural experiments embedded in this dataset and complementary data obtained via Internet archaeology to show that different subnetworks, e.g., among students and among alumni, matured at different rates toward similar end states. These results shed new light on the processes and patterns of online social network assembly, and may facilitate more effective design for online social systems."
12 hours ago
Hundreds of variants clustered in genomic loci and biological pathways affect human height
"Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence phenotype. Genome-wide association (GWA) studies have identified >600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the utility of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P=0.016), and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants, and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented amongst variants that alter amino acid structure of proteins and expression levels of nearby genes. Our data explain ∼10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to ∼16% of phenotypic variation (∼20% of heritable variation). Although additional approaches are needed to fully dissect the genetic architecture of polygenic human traits, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways."
to:NB  genetics  human_genetics  heritability
13 hours ago
Unintended but not unanticipated consequences - Springer
"The concept “unanticipated consequences,” coined by Robert K. Merton (1936), has largely been replaced in current social science by its putative synonym, “unintended consequences.” This conflation suggests that “unintended” consequences are also “unanticipated,” effectively obscuring an interesting and real category of phenomena—consequences that are both unintended and anticipated—that warrant separate attention. The first part of this article traces the conflation of “unintended” and “unanticipated,” and explains why it occurred. The second part argues the need for a clear distinction between what is unintended and what is unanticipated, and it illustrates the failure of the present concept of “unintended consequences” to do so and the consequences that has for social and political analysis."
to:NB  social_theory
2 days ago
On the Directionality Test of Peer Effects in Social Networks
"One interesting idea in social network analysis is the directionality test that utilizes the directions of social ties to help identify peer effects. The null hypothesis of the test is that if contextual factors are the only force that affects peer outcomes, the estimated peer effects should not differ, if the directions of social ties are reversed. In this article, I statistically formalize this test and investigate its properties under various scenarios. In particular, I point out the validity of the test is contingent on the presence of peer selection, sampling error, and simultaneity bias. I also outline several methods that can help provide causal estimates of peer effects in social networks."

- Last tag applies mostly to the last sentence.
to:NB  to_read  network_data_analysis  causal_inference  social_networks  homophily  social_influence  contagion  re:homophily_and_confounding  to_be_shot_after_a_fair_trial
3 days ago
Behavioural Approaches: How Nudges Lead to More Intelligent Policy Design by Peter John :: SSRN
"This paper reviews the use of behavioural ideas to improve public policy. There needs to be a behavioural take on decision-making itself so that policies are designed in more effective ways. it recounts the beginnings of behavioural sciences as currently conceived and then setting out the massive expansion of interest that has come about since that time. It reports on how such ideas have had a large impact on governments at all levels across the world, but also noting how decision-making itself has been influenced by more policy-relevant ideas. The paper discusses the paradox that the very decision-makers themselves are subject to the same biases as the objects of behavioural economics, which might imply limitations in the choices of such interventions. Here the text of the chapter reengages with the classics of decision-making theory. The chapter notes how behavioural sciences need not depend on a top down approach but can incorporate citizen voice. The paper reviews how citizens and other groups can use behavioural cues to alter the behaviour of policy-makers in socially beneficial ways. The paper discusses how behaviourally informed measures could be integrated within the policy making process in ways that advance the effective use of evidence and nudge decision to make better policies."
to:NB  to_read  public_policy  decision-making  re:anti-nudge  via:henry_farrell
4 days ago
[1504.03712] Measuring the Graph Concordance of Locally Dependent Observations
"This paper introduces a simple measure of a concordance pattern among many observed outcomes along a given large network, i.e., the pattern in which adjacent outcomes tend to be more strongly correlated than non-adjacent outcomes. The measure can be generally used to quantify the empirical relevance of a given network in explaining cross-sectional variations of the outcomes, or in the context of studies in social networks, used as a measure of homophily among people. Without presuming any particular functional relationships among observed or unobserved variables, the measure captures a joint dependence pattern of the outcomes along the given network. This paper develops a permutation-based confidence interval for the graph concordance measure. The confidence interval is valid in finite samples when the outcomes are exchangeable, and under regularity conditions, is shown to exhibit asymptotic validity even when the outcomes fail to be exchangeable. Monte Carlo simulation results show that the validity of the permutation method is more robust to various graph configurations than the asymptotic method."
to:NB  network_data_analysis  statistics
4 days ago
[1504.04595] Random projection ensemble classification
"We introduce a very general method for high-dimensional classification, based on careful combination of the results of applying an arbitrary base classifier to random projections of the feature vectors into a lower-dimensional space. In one special case that we study in detail, the random projections are divided into non-overlapping blocks, and within each block we select the projection yielding the smallest estimate of the test error. Our random projection ensemble classifier then aggregates the results of applying the base classifier on the selected projections, with a data-driven voting threshold to determine the final assignment. Our theoretical results elucidate the effect on performance of increasing the number of projections. Moreover, under a boundary condition implied by the sufficient dimension reduction assumption, we show that the test excess risk of the random projection ensemble classifier can be controlled by terms that do not depend on the original data dimension. The classifier is also compared empirically with several other popular high-dimensional classifiers via an extensive simulation study, which reveals its excellent finite-sample performance."
to:NB  random_projections  classifiers  ensemble_methods  statistics
4 days ago
[1503.03515] Bi-cross-validation for factor analysis
"Factor analysis is over a century old, but it is still problematic to choose the number of factors for a given data set. The scree test is popular but subjective. The best performing objective methods are recommended on the basis of simulations. We introduce a method based on bi-cross-validation, using randomly held-out submatrices of the data to choose the number of factors. We find it performs better than the leading methods of parallel analysis (PA) and Kaiser's rule. Our performance criterion is based on recovery of the underlying factor-loading (signal) matrix rather than identifying the true number of factors. Like previous comparisons, our work is simulation based. Recent advances in random matrix theory provide principled choices for the number of factors when the noise is homoscedastic, but not for the heteroscedastic case. The simulations we choose are designed using guidance from random matrix theory. In particular, we include factors too small to detect, factors large enough to detect but not large enough to improve the estimate, and two classes of factors large enough to be useful. Much of the advantage of bi-cross-validation comes from cases with factors large enough to detect but too small to be well estimated. We also find that a form of early stopping regularization improves the recovery of the signal matrix."
to:NB  model_selection  factor_analysis  cross-validation  owen.art  statistics  re:ADAfaEPoV
4 days ago
[1503.05077] Tail index estimation, concentration and adaptivity
"This paper presents an adaptive version of the Hill estimator based on Lespki's model selection method. This simple data-driven index selection method is shown to satisfy an oracle inequality and is checked to achieve the lower bound recently derived by Carpentier and Kim. In order to establish the oracle inequality, we derive non-asymptotic variance bounds and concentration inequalities for Hill estimators. These concentration inequalities are derived from Talagrand's concentration inequality for smooth functions of independent exponentially distributed random variables combined with three tools of Extreme Value Theory: the quantile transform, Karamata's representation of slowly varying functions, and R\'enyi's characterisation of the order statistics of exponential samples. The performance of this computationally and conceptually simple method is illustrated using Monte-Carlo simulations."
4 days ago
[1503.05826] Respondent-driven sampling bias induced by clustering and community structure in social networks
"Sampling hidden populations is particularly challenging using standard sampling methods mainly because of the lack of a sampling frame. Respondent-driven sampling (RDS) is an alternative methodology that exploits the social contacts between peers to reach and weight individuals in these hard-to-reach populations. It is a snowball sampling procedure where the weight of the respondents is adjusted for the likelihood of being sampled due to differences in the number of contacts. In RDS, the structure of the social contacts thus defines the sampling process and affects its coverage, for instance by constraining the sampling within a sub-region of the network. In this paper we study the bias induced by network structures such as social triangles, community structure, and heterogeneities in the number of contacts, in the recruitment trees and in the RDS estimator. We simulate different scenarios of network structures and response-rates to study the potential biases one may expect in real settings. We find that the prevalence of the estimated variable is associated with the size of the network community to which the individual belongs. Furthermore, we observe that low-degree nodes may be under-sampled in certain situations if the sample and the network are of similar size. Finally, we also show that low response-rates lead to reasonably accurate average estimates of the prevalence but generate relatively large biases."
to:NB  network_data_analysis  respondent-driven_sampling  homophily  statistics
4 days ago
[1504.08349] Hidden population size estimation from respondent-driven sampling: a network approach
"Estimating the size of stigmatized, hidden, or hard-to-reach populations is a major problem in epidemiology, demography, and public health research. Capture-recapture and multiplier methods have become standard tools for inference of hidden population sizes, but they require independent random sampling of target population members, which is rarely possible. Respondent-driven sampling (RDS) is a survey method for hidden populations that relies on social link tracing. The RDS recruitment process is designed to spread through the social network connecting members of the target population. In this paper, we show how to use network data revealed by RDS to estimate hidden population size. The key insight is that the recruitment chain, timing of recruitments, and network degrees of recruited subjects provide information about the number of individuals belonging to the target population who are not yet in the sample. We use a computationally efficient Bayesian method to integrate over the missing edges in the subgraph of recruited individuals. We validate the method using simulated data and apply the technique to estimate the number of people who inject drugs in St. Petersburg, Russia."
to:NB  network_data_analysis  network_sampling  respondent-driven_sampling  statistics  crawford.forrest  surveys
4 days ago
[1504.03574] Nonparametric Identification for Respondent-Driven Sampling
"Respondent-driven sampling is a survey method for hidden or hard-to-reach populations in which sampled individuals recruit others in the study population via their social links. The most popular estimator for for the population mean assumes that individual sampling probabilities are proportional to each subject's reported degree in a social network connecting members of the hidden population. However, it remains unclear under what circumstances these estimators are valid, and what assumptions are formally required to identify population quantities. In this short note we detail nonparametric identification results for the population mean when the sampling probability is assumed to be a function of network degree known to scale. Importantly, we establish general conditions for the consistency of the popular Volz-Heckathorn (VH) estimator. Our results imply that the conditions for consistency of the VH estimator are far less stringent than those suggested by recent work on diagnostics for RDS. In particular, our results do not require random sampling or the existence of a network connecting the population."
to:NB  network_data_analysis  respondent-driven_sampling  aronow.peter  statistics  surveys
4 days ago
[1504.00641] A Probabilistic Theory of Deep Learning
"A grand challenge in machine learning is the development of computational algorithms that match or outperform humans in perceptual inference tasks that are complicated by nuisance variation. For instance, visual object recognition involves the unknown object position, orientation, and scale in object recognition while speech recognition involves the unknown voice pronunciation, pitch, and speed. Recently, a new breed of deep learning algorithms have emerged for high-nuisance inference tasks that routinely yield pattern recognition systems with near- or super-human capabilities. But a fundamental question remains: Why do they work? Intuitions abound, but a coherent framework for understanding, analyzing, and synthesizing deep learning architectures has remained elusive. We answer this question by developing a new probabilistic framework for deep learning based on the Deep Rendering Model: a generative probabilistic model that explicitly captures latent nuisance variation. By relaxing the generative model to a discriminative one, we can recover two of the current leading deep learning systems, deep convolutional neural networks and random decision forests, providing insights into their successes and shortcomings, as well as a principled route to their improvement."

- But does this explain the "intriguing findings"?
to:NB  neural_networks  learning_theory
4 days ago
[1504.06706] Penalized Likelihood Estimation in High-Dimensional Time Series Models and its Application
"This paper presents a general theoretical framework of penalized quasi-maximum likelihood (PQML) estimation in stationary multiple time series models when the number of parameters possibly diverges. We show the oracle property of the PQML estimator under high-level, but tractable, assumptions, comprising the first half of the paper. Utilizing these results, we propose in the latter half of the paper a method of sparse estimation in high-dimensional vector autoregressive (VAR) models. Finally, the usability of the sparse high-dimensional VAR model is confirmed with a simulation study and an empirical analysis on a yield curve forecast."
to:NB  time_series  statistics  high-dimensional_statistics
4 days ago
[1504.04941] Fast Moment-Based Estimation for Hierarchical Models
"Hierarchical models allow for heterogeneous behaviours in a population while simultaneously borrowing estimation strength across all subpopulations. Unfortunately, existing likelihood-based methods for fitting hierarchical models have high computational demands, and these demands have limited their adoption in large-scale prediction and inference problems. This paper proposes a moment-based procedure for estimating the parameters of a hierarchical model which has its roots in a method originally introduced by Cochran in 1937. The method trades statistical efficiency for computational efficiency. It gives consistent parameter estimates, competitive prediction error performance, and substantial computational improvements. When applied to a large-scale recommender system application and compared to a standard maximum likelihood procedure, the method delivers competitive prediction performance while reducing the sequential computation time from hours to minutes."
to:NB  to_read  hierarchical_statistical_models  computational_statistics  statistics  perry.patrick_o.
4 days ago
[1504.00494] Minimal class of models for high-dimensional data
"Model selection consistency in the high-dimensional regression setting can be achieved only if strong assumptions are fulfilled. We therefore suggest to pursue a different goal, which we call class of minimal models. The class of minimal models includes models that are similar in their prediction accuracy but not necessarily in their elements. We suggest a random search algorithm to reveal candidate models. The algorithm implements simulated annealing while using a score for each predictor that we suggest to derive using a combination of the Lasso and the Elastic Net. The utility of using a class of minimal models is demonstrated in the analysis of two datasets."
to:NB  statistics  misspecification  high-dimensional_statistics  model_selection
5 days ago
[1504.00091] Learning in the Presence of Corruption
"In supervised learning one wishes to identify a pattern present in a joint distribution P, of instances, label pairs, by providing a function f from instances to labels that has low risk 𝔼Pℓ(y,f(x)). To do so, the learner is given access to n iid samples drawn from P. In many real world problems clean samples are not available. Rather, the learner is given access to samples from a corrupted distribution P~ from which to learn, while the goal of predicting the clean pattern remains. There are many different types of corruption one can consider, and as of yet there is no general means to compare the relative ease of learning under these different corruption processes. In this paper we develop a general framework for tackling such problems as well as introducing upper and lower bounds on the risk for learning in the presence of corruption. Our ultimate goal is to be able to make informed economic decisions in regards to the acquisition of data sets. For a certain subclass of corruption processes (those that are \emph{reconstructible}) we achieve this goal in a particular sense. Our lower bounds are in terms of the coefficient of ergodicity, a simple to calculate property of stochastic matrices. Our upper bounds proceed via a generalization of the method of unbiased estimators appearing in recent work of Natarajan et al and implicit in the earlier work of Kearns."
to:NB  learning_theory
5 days ago
[1503.08234] A Note on the Specific Source Identification Problem in Forensic Science in the Presence of Uncertainty about the Background Population
"A goal in the forensic interpretation of scientific evidence is to make an inference about the source of a trace of unknown origin. The evidence is composed of the following three elements: (a) the trace of unknown origin, (b) a sample from a specific source, and (c) a collection of samples from the alternative source population. The inference process usually considers two propositions. The first proposition is usually referred to as the prosecution hypothesis and states that a given specific source is the actual source of the trace of unknown origin. The second, usually referred to as the defense hypothesis, states that the actual source of the trace of unknown origin is another source from a relevant alternative source population. One approach is to calculate a Bayes Factor for deciding between the two competing hypotheses. This approach commonly assumes that the alternative source population is completely known or uses point estimates for its parameters. Contrary to this common approach, we propose a development that incorporates the uncertainty on the alternative source population parameters in a reasonable and coherent manner into the Bayes Factor. We will illustrate the resulting effects on the calculation of several Bayes Factors for different situations with a well-studied collection of samples of glass fragments."
5 days ago
[1503.06426] High-dimensional inference in misspecified linear models
"We consider high-dimensional inference when the assumed linear model is misspecified. We describe some correct interpretations and corresponding sufficient assumptions for valid asymptotic inference of the model parameters, which still have a useful meaning when the model is misspecified. We largely focus on the de-sparsified Lasso procedure but we also indicate some implications for (multiple) sample splitting techniques. In view of available methods and software, our results contribute to robustness considerations with respect to model misspecification."
to:NB  statistics  linear_regression  high-dimensional_statistics  lasso  buhlmann.peter  van_de_geer.sara
5 days ago
[1505.02475] Foundational principles for large scale inference: Illustrations through correlation mining
"When can reliable inference be drawn in the "Big Data" context? This paper presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics the dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for "Big Data." Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. We demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks."
to:NB  high-dimensional_statistics  statistics
5 days ago
[1505.02456] Graphical Markov models, unifying results and their interpretation
"Graphical Markov models combine conditional independence constraints with graphical representations of stepwise data generating processes.The models started to be formulated about 40 years ago and vigorous development is ongoing. Longitudinal observational studies as well as intervention studies are best modeled via a subclass called regression graph models and, especially traceable regressions. Regression graphs include two types of undirected graph and directed acyclic graphs in ordered sequences of joint responses. Response components may correspond to discrete or continuous random variables and may depend exclusively on variables which have been generated earlier. These aspects are essential when causal hypothesis are the motivation for the planning of empirical studies.
"To turn the graphs into useful tools for tracing developmental pathways and for predicting structure in alternative models, the generated distributions have to mimic some properties of joint Gaussian distributions. Here, relevant results concerning these aspects are spelled out and illustrated by examples. With regression graph models, it becomes feasible, for the first time, to derive structural effects of (1) ignoring some of the variables, of (2) selecting subpopulations via fixed levels of some other variables or of (3) changing the order in which the variables might get generated. Thus, the most important future applications of these models will aim at the best possible integration of knowledge from related studies."
to:NB  graphical_models  statistics  regression  wemuth.nanny
5 days ago
[1505.02452] Design and interpretation of studies: relevant concepts from the past and some extensions
"Principles for the planning and analysis of observational studies, as suggested by W.G Cochran in 1972, are discussed and compared to additional methodological developments since then."
5 days ago
[1505.03481] Relations Between Adjacency and Modularity Graph Partitioning
"In this paper the exact linear relation between the leading eigenvector of the unnormalized modularity matrix and the eigenvectors of the adjacency matrix is developed. Based on this analysis a method to approximate the leading eigenvector of the modularity matrix is given, and the relative error of the approximation is derived. A complete proof of the equivalence between normalized modularity clustering and normalized adjacency clustering is also given. A new metric is defined to describe the agreement of two clustering methods, and some applications and experiments are given to illustrate and corroborate the points that are made in the theoretical development."
to:NB  community_discovery  network_data_analysis  statistics
5 days ago
[1505.01547] Understanding the Heavy Tailed Dynamics in Human Behavior
"The recent availability of electronic datasets containing large volumes of communication data has made it possible to study human behavior on a larger scale than ever before. From this, it has been discovered that across a diverse range of data sets, the inter-event times between consecutive communication events obey heavy tailed power law dynamics. Explaining this has proved controversial, and two distinct hypotheses have emerged. The first holds that these power laws are fundamental, and arise from the mechanisms such as priority queuing that humans use to schedule tasks. The second holds that they are a statistical artifact which only occur in aggregated data when features such as circadian rhythms and burstiness are ignored. We use a large social media data set to test these hypotheses, and find that although models that incorporate circadian rhythms and burstiness do explain part of the observed heavy tails, there is residual unexplained heavy tail behavior which suggests a more fundamental cause. Based on this, we develop a new quantitative model of human behavior which improves on existing approaches, and gives insight into the mechanisms underlying human interactions."
to:NB  to_read  heavy_tails  time_series  point_processes  statistics
5 days ago
[1505.01163] Stationarity Tests for Time Series -- What Are We Really Testing?
"Traditionally stationarity refers to shift invariance of the distribution of a stochastic process. In this paper, we rediscover stationarity as a path property instead of a distributional property. More precisely, we characterize a set of paths denoted as A, which corresponds to the notion of stationarity. On one hand, the set A is shown to be large enough, so that for any stationary process, almost all of its paths are in A. On the other hand, we prove that any path in A will behave in the optimal way under any stationarity test satisfying some mild conditions. The results justify our intuition about how a "typical" stationary process should look like, and potentially lead to new families of stationarity tests."
5 days ago
[1505.00044] Incorporating Contact Network Structure in Cluster Randomized Trials
"Whenever possible, the efficacy of a new treatment, such as a drug or behavioral intervention, is investigated by randomly assigning some individuals to a treatment condition and others to a control condition, and comparing the outcomes between the two groups. Often, when the treatment aims to slow an infectious disease, groups or clusters of individuals are assigned en masse to each treatment arm. The structure of interactions within and between clusters can reduce the power of the trial, i.e. the probability of correctly detecting a real treatment effect. We investigate the relationships among power, within-cluster structure, between-cluster mixing, and infectivity by simulating an infectious process on a collection of clusters. We demonstrate that current power calculations may be conservative for low levels of between-cluster mixing, but failing to account for moderate or high amounts can result in severely underpowered studies. Power also depends on within-cluster network structure for certain kinds of infectious spreading. Infections that spread opportunistically through very highly connected individuals have unpredictable infectious breakouts, which makes it harder to distinguish between random variation and real treatment effects. Our approach can be used before conducting a trial to assess power using network information if it is available, and we demonstrate how empirical data can inform the extent of between-cluster mixing."
to:NB  to_read  network_data_analysis  experimental_design  statistics  ogburn.elizabeth
5 days ago
People: "Game of Thrones" Is Horror!
DeLong is entirely correct in this --- but I think it is an artistic failure of the show that (e.g.) it does not do anything to induce the viewer to feel like they've been made into monsters after Brad's second-worst moment.
5 days ago
Rivera, L.A.: Pedigree: How Elite Students Get Elite Jobs. (eBook and Hardcover)
"Americans are taught to believe that upward mobility is possible for anyone who is willing to work hard, regardless of their social status, yet it is often those from affluent backgrounds who land the best jobs. Pedigree takes readers behind the closed doors of top-tier investment banks, consulting firms, and law firms to reveal the truth about who really gets hired for the nation’s highest-paying entry-level jobs, who doesn’t, and why.
"Drawing on scores of in-depth interviews as well as firsthand observation of hiring practices at some of America’s most prestigious firms, Lauren Rivera shows how, at every step of the hiring process, the ways that employers define and evaluate merit are strongly skewed to favor job applicants from economically privileged backgrounds. She reveals how decision makers draw from ideas about talent—what it is, what best signals it, and who does (and does not) have it—that are deeply rooted in social class. Displaying the “right stuff” that elite employers are looking for entails considerable amounts of economic, social, and cultural resources on the part of the applicants and their parents."
to:NB  books:noted  class_struggles_in_america  economics  inequality  transmission_of_inequality
5 days ago
Why Do Cities Matter? Local Growth and Aggregate Growth
"We study how growth of cities determines the growth of nations. Using a spatial equilibrium model and data on 220 US metropolitan areas from 1964 to 2009, we first estimate the contribution of each U.S. city to national GDP growth. We show that the contribution of a city to aggregate growth can differ significantly from what one might naively infer from the growth of the city’s GDP. Despite some of the strongest rate of local growth, New York, San Francisco and San Jose were only responsible for a small fraction of U.S. growth in this period. By contrast, almost half of aggregate US growth was driven by growth of cities in the South. We then provide a normative analysis of potential growth. We show that the dispersion of the conditional average nominal wage across US cities doubled, indicating that worker productivity is increasingly different across cities. We calculate that this increased wage dispersion lowered aggregate U.S. GDP by 13.5%. Most of the loss was likely caused by increased constraints to housing supply in high productivity cities like New York, San Francisco and San Jose. Lowering regulatory constraints in these cities to the level of the median city would expand their work force and increase U.S. GDP by 9.5%. We conclude that the aggregate gains in output and welfare from spatial reallocation of labor are likely to be substantial in the U.S., and that a major impediment to a more efficient spatial allocation of labor are housing supply constraints. These constraints limit the number of US workers who have access to the most productive of American cities. In general equilibrium, this lowers income and welfare of all US workers."
to:NB  cities  economics  economic_growth  economic_geography  to_be_shot_after_a_fair_trial  via:unfogged  re:urban_scaling_what_urban_scaling
5 days ago
Information flow on graphs | The Information Structuralist
That's a very nice sufficient condition for a cellular automaton to be mixing --- actually it'd work for any Markov random field on a graph...
information_theory  cellular_automata  stochastic_processes  mixing  random_fields  markov_models  to:blog
5 days ago
Data Mining for the Social Sciences - Paul Attewell, David Monaghan - Paperback - University of California Press
"We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages."
to:NB  books:noted  data_mining  social_science_methodology  to_teach:data-mining
5 days ago
Race, Monogamy, and Other Lies They Told You - Agustin Fuentes - Paperback - University of California Press
"There are three major myths of human nature: humans are divided into biological races; humans are naturally aggressive; and men and women are truly different in behavior, desires, and wiring. In an engaging and wide-ranging narrative, Agustín Fuentes counters these pervasive and pernicious myths about human behavior. Tackling misconceptions about what race, aggression, and sex really mean for humans, Fuentes incorporates an accessible understanding of culture, genetics, and evolution, requiring us to dispose of notions of “nature or nurture.” Presenting scientific evidence from diverse fields—including anthropology, biology, and psychology—Fuentes devises a myth-busting toolkit to dismantle persistent fallacies about the validity of biological races, the innateness of aggression and violence, and the nature of monogamy and differences between the sexes. A final chapter plus an appendix provide a set of take-home points on how readers can myth-bust on their own. Accessible, compelling, and original, this book is a rich and nuanced account of how nature, culture, experience, and choice interact to influence human behavior."

--- What makes this more interesting to me is that Fuentes is a _biological_ anthropologist, i.e., a member of a tribe with an enduring and vicious feud with cultural anthropologists.
to:NB  books:noted  anthropology  human_evolution  race  racism  evolutionary_psychology  debunking  practices_relating_to_the_transmission_of_genetic_information
5 days ago
The Hunter, the Stag, and the Mother of Animals - Esther Jacobson-Tepfer - Oxford University Press
"The ancient landscape of North Asia gave rise to a mythic narrative of birth, death, and transformation that reflected the hardship of life for ancient nomadic hunters and herders. Of the central protagonists, we tend to privilege the hero hunter of the Bronze Age and his re-incarnation as a warrior in the Iron Age. But before him and, in a sense, behind him was a female power, half animal, half human. From her came permission to hunt the animals of the taiga, and by her they were replenished. She was, in other words, the source of the hunter's success. The stag was a latecomer to this tale, a complex symbol of death and transformation embedded in what ultimately became a struggle for priority between animal mother and hero hunter.
"From this region there are no written texts to illuminate prehistory, and the hundreds of burials across the steppe reveal little relating to myth and belief before the late Bronze Age. What they do tell us is that peoples and cultures came and went, leaving behind huge stone mounds, altars, and standing stones as well as thousands of petroglyphic images. With The Hunter, the Stag, and the Mother of Animals, Esther Jacobson-Tepfer uses that material to reconstruct the prehistory of myth and belief in ancient North Asia. Her narrative places monuments and imagery within the context of the physical landscape and by considering all three elements as reflections of the archaeology of belief. Within that process, paleoenvironmental forces, economic innovations, and changing social order served as pivots of mythic transformation. With this vividly illustrated study, Jacobson-Tepfer brings together for this first time in any language Russian and Mongolian archaeology with prehistoric representational traditions of South Siberia and Mongolia in order to explore the non-material aspects of these fascinating prehistoric cultures."

--- This looks (how to put it delicately?) like an intriguing fusion of scholarship with mythopoesis.
to:NB  books:noted  archaeology  history_of_religion  central_asia  shamanism  to_be_shot_after_a_fair_trial
5 days ago
Irregularities in LaCour (2014)
"We report a number of irregularities in the replication dataset posted for LaCour and Green (Science, “When contact changes minds: An experiment on transmission of support for gay equality,” 2014) that jointly suggest the dataset (LaCour 2014) was not collected as described. These irregularities include baseline outcome data that is statistically indistinguishable from a national survey and over-time changes that are unusually small and indistinguishable from perfectly normally distributed noise. Other elements of the dataset are inconsistent with patterns typical in randomized experiments and survey responses and/or inconsistent with the claimed design of the study. A straightforward procedure may generate these anomalies nearly exactly: for both studies reported in the paper, a random sample of the 2012 Cooperative Campaign Analysis Project (CCAP) form the baseline data and normally distributed noise are added to simulate follow-up waves."

--- Pretty damning.
fraud  surveys  statistics
5 days ago
Multi-Agent Inference in Social Networks: A Finite Population Learning Approach
"When people in a society want to make inference about some parameter, each person may want to use data collected by other people. Information (data) exchange in social networks is usually costly, so to make reliable statistical decisions, people need to weigh the benefits and costs of information acquisition. Conflicts of interests and coordination problems will arise in the process. Classical statistics does not consider people’s incentives and interactions in the data-collection process. To address this imperfection, this work explores multi-agent Bayesian inference problems with a game theoretic social network model. Motivated by our interest in aggregate inference at the societal level, we propose a new concept, finite population learning, to address whether with high probability, a large fraction of people in a given finite population network can make “good” inference. Serving as a foundation, this concept enables us to study the long run trend of aggregate inference quality as population grows. Supplementary materials for this article are available online."
to:NB  statistics  ensemble_methods  collective_cognition  re:democratic_cognition
5 days ago
Drovandi , Pettitt , Lee : Bayesian Indirect Inference Using a Parametric Auxiliary Model
"Indirect inference (II) is a methodology for estimating the parameters of an intractable (generative) model on the basis of an alternative parametric (auxiliary) model that is both analytically and computationally easier to deal with. Such an approach has been well explored in the classical literature but has received substantially less attention in the Bayesian paradigm. The purpose of this paper is to compare and contrast a collection of what we call parametric Bayesian indirect inference (pBII) methods. One class of pBII methods uses approximate Bayesian computation (referred to here as ABC II) where the summary statistic is formed on the basis of the auxiliary model, using ideas from II. Another approach proposed in the literature, referred to here as parametric Bayesian indirect likelihood (pBIL), uses the auxiliary likelihood as a replacement to the intractable likelihood. We show that pBIL is a fundamentally different approach to ABC II. We devise new theoretical results for pBIL to give extra insights into its behaviour and also its differences with ABC II. Furthermore, we examine in more detail the assumptions required to use each pBII method. The results, insights and comparisons developed in this paper are illustrated on simple examples and two other substantive applications. The first of the substantive examples involves performing inference for complex quantile distributions based on simulated data while the second is for estimating the parameters of a trivariate stochastic process describing the evolution of macroparasites within a host based on real data. We create a novel framework called Bayesian indirect likelihood (BIL) that encompasses pBII as well as general ABC methods so that the connections between the methods can be established."
to:NB  indirect_inference  approximate_bayesian_computation  statistics
5 days ago
Ogburn , VanderWeele : Causal Diagrams for Interference
"The term “interference” has been used to describe any setting in which one subject’s exposure may affect another subject’s outcome. We use causal diagrams to distinguish among three causal mechanisms that give rise to interference. The first causal mechanism by which interference can operate is a direct causal effect of one individual’s treatment on another individual’s outcome; we call this direct interference. Interference by contagion is present when one individual’s outcome may affect the outcomes of other individuals with whom he comes into contact. Then giving treatment to the first individual could have an indirect effect on others through the treated individual’s outcome. The third pathway by which interference may operate is allocational interference. Treatment in this case allocates individuals to groups; through interactions within a group, individuals may affect one another’s outcomes in any number of ways. In many settings, more than one type of interference will be present simultaneously. The causal effects of interest differ according to which types of interference are present, as do the conditions under which causal effects are identifiable. Using causal diagrams for interference, we describe these differences, give criteria for the identification of important causal effects, and discuss applications to infectious diseases."
to:NB  social_influence  contagion  graphical_models  causal_inference  statistics  ogburn.elizabeth
5 days ago
Spirtes , Zhang : A Uniformly Consistent Estimator of Causal Effects under the $k$-Triangle-Faithfulness Assumption
"Spirtes, Glymour and Scheines [Causation, Prediction, and Search (1993) Springer] described a pointwise consistent estimator of the Markov equivalence class of any causal structure that can be represented by a directed acyclic graph for any parametric family with a uniformly consistent test of conditional independence, under the Causal Markov and Causal Faithfulness assumptions. Robins et al. [Biometrika 90 (2003) 491–515], however, proved that there are no uniformly consistent estimators of Markov equivalence classes of causal structures under those assumptions. Subsequently, Kalisch and Bühlmann [J. Mach. Learn. Res. 8 (2007) 613–636] described a uniformly consistent estimator of the Markov equivalence class of a linear Gaussian causal structure under the Causal Markov and Strong Causal Faithfulness assumptions. However, the Strong Faithfulness assumption may be false with high probability in many domains. We describe a uniformly consistent estimator of both the Markov equivalence class of a linear Gaussian causal structure and the identifiable structural coefficients in the Markov equivalence class under the Causal Markov assumption and the considerably weaker k-Triangle-Faithfulness assumption."
5 days ago
Agent-Based Models in Empirical Social Research
"Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research."
to:NB  agent-based_models  modeling
5 days ago
Zhang , Kolaczyk , Spencer : Estimating network degree distributions under sampling: An inverse problem, with applications to monitoring social media networks
"Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently the case, for example, in the monitoring and study of massive, online social networks. We study the problem of how to estimate the degree distribution—an object of fundamental interest—of a true underlying network from its sampled network. In particular, we show that this problem can be formulated as an inverse problem. Playing a key role in this formulation is a matrix relating the expectation of our sampled degree distribution to the true underlying degree distribution. Under many network sampling designs, this matrix can be defined entirely in terms of the design and is found to be ill-conditioned. As a result, our inverse problem frequently is ill-posed. Accordingly, we offer a constrained, penalized weighted least-squares approach to solving this problem. A Monte Carlo variant of Stein’s unbiased risk estimation (SURE) is used to select the penalization parameter. We explore the behavior of our resulting estimator of network degree distribution in simulation, using a variety of combinations of network models and sampling regimes. In addition, we demonstrate the ability of our method to accurately reconstruct the degree distributions of various sub-communities within online social networks corresponding to Friendster, Orkut and LiveJournal. Overall, our results show that the true degree distributions from both homogeneous and inhomogeneous networks can be recovered with substantially greater accuracy than reflected in the empirical degree distribution resulting from the original sampling."
to:NB  network_data_analysis  network_sampling  statistics
5 days ago
Ober, J.: The Rise and Fall of Classical Greece (eBook and Hardcover).
"Lord Byron described Greece as great, fallen, and immortal, a characterization more apt than he knew. Through most of its long history, Greece was poor. But in the classical era, Greece was densely populated and highly urbanized. Many surprisingly healthy Greeks lived in remarkably big houses and worked for high wages at specialized occupations. Middle-class spending drove sustained economic growth and classical wealth produced a stunning cultural efflorescence lasting hundreds of years.
"Why did Greece reach such heights in the classical period—and why only then? And how, after “the Greek miracle” had endured for centuries, did the Macedonians defeat the Greeks, seemingly bringing an end to their glory? Drawing on a massive body of newly available data and employing novel approaches to evidence, Josiah Ober offers a major new history of classical Greece and an unprecedented account of its rise and fall.
"Ober argues that Greece’s rise was no miracle but rather the result of political breakthroughs and economic development. The extraordinary emergence of citizen-centered city-states transformed Greece into a society that defeated the mighty Persian Empire. Yet Philip and Alexander of Macedon were able to beat the Greeks in the Battle of Chaeronea in 338 BCE, a victory made possible by the Macedonians’ appropriation of Greek innovations. After Alexander’s death, battle-hardened warlords fought ruthlessly over the remnants of his empire. But Greek cities remained populous and wealthy, their economy and culture surviving to be passed on to the Romans—and to us."
books:noted  ancient_history  institutions  economic_history  ober.josiah
6 days ago
Brad DeLong on John Quiggin's _The Political is Personal_
"I have often wondered and never manage to get completely straight in my mind how economics lost its utilitarian roots--how it went from saying "this is a good policy because it advances the greater good of the greater number" to "competitive free-market allocations are good because they are Pareto-optimal, and we do not prefer any particular Pareto-optimal allocation because that would be a question not of science but of values and politics, and non-Pareto-optimal allocations are bad." It has puzzled me particularly because the claim that we cannot say X is better than Y because they are not Pareto-ranked is not, in general, raised when the policy at issue issue is a GDP-increasing and either distributionally-neutral or inequality-increasing policy like tariff reductions or cuts in capital taxation..."

--- I am puzzled that Brad is puzzled. If economists did _not_ ignore their own principles about social welfare when giving policy advice like this, they'd be as respected and supported as sociologists. But perhaps he's taking this for granted, and wants to know the mechanism by which individual economists are kept in line, in which case I admit there is something to be explained, and would wave my hands at their centralized and hierarchical job market (Han, 2003), and their deeply-internalized and cultivated obsession with a one-dimensional prestige ladder (EconJobRumors, ad nauseam).
6 days ago
"P values, hypothesis testing, and model selection: it’s deja vu all over again"
"Those of us who went through graduate school in the 1970s, 1980s, and 1990s remember attempting to coax another 0.001 out of SAS’s P 1⁄4 0.051 output (maybe if I just rounded to two decimal places . . .), raising a toast to P 1⁄4 0.0499 (and the invention of floating point processors), or desperately searching the back pages of Sokal and Rohlf for a different test that would cross the finish line and satisfy our dissertation committee. The P 1⁄4 0.05 ‘‘red line in the sand’’ partly motivated the ecological Bayesian wars of the late 1990s and the model-selection detente of the early 2000s. The introduction of Markov chain Monte Carlo (MCMC) integration to statistical modeling and inference led many of us to hope that we could capture, or at least model, ecological elephants."

--- Via Tim Danford on Twitter (https://twitter.com/arthegall/status/595891426329808896), whose comment "It's hard to imagine a more succinct explanation of why hypothesis testing is mathematically plausible but a social disaster" goes further than I would, but, still
to:NB  to:blog  hypothesis_testing  model_selection  ecology  statistics
7 days ago
Building Blocs: How Parties Organize Society | Edited by Cedric de Leon, Manali Desai, and Cihan Tuğal
"Do political parties merely represent divisions in society? Until now, scholars and other observers have generally agreed that they do. But Building Blocs argues the reverse: that some political parties in fact shape divisions as they struggle to remake the social order. Drawing on the contributors' expertise in Indonesia, India, the United States, Canada, Egypt, and Turkey, this volume demonstrates further that the success and failure of parties to politicize social differences has dramatic consequences for democratic change, economic development, and other large-scale transformations.
"This politicization of divisions, or "political articulation," is neither the product of a single charismatic leader nor the machinations of state power, but is instead a constant call and response between parties and would-be constituents. When articulation becomes inconsistent, as it has in Indonesia, partisan calls grow faint and the resulting vacuum creates the possibility for other forms of political expression. However, when political parties exercise their power of interpellation efficiently, they are able to silence certain interests such as those of secular constituents in Turkey. Building Blocs exposes political parties as the most influential agencies that structure social cleavages and invites further critical investigation of the related consequences."
to:NB  books:noted  democracy  political_science  political_parties
7 days ago
How a well-adapted immune system is organized
"The repertoire of lymphocyte receptors in the adaptive immune system protects organisms from diverse pathogens. A well-adapted repertoire should be tuned to the pathogenic environment to reduce the cost of infections. We develop a general framework for predicting the optimal repertoire that minimizes the cost of infections contracted from a given distribution of pathogens. The theory predicts that the immune system will have more receptors for rare antigens than expected from the frequency of encounters; individuals exposed to the same infections will have sparse repertoires that are largely different, but nevertheless exploit cross-reactivity to provide the same coverage of antigens; and the optimal repertoires can be reached via the dynamics of competitive binding of antigens by receptors and selective amplification of stimulated receptors. Our results follow from a tension between the statistics of pathogen detection, which favor a broader receptor distribution, and the effects of cross-reactivity, which tend to concentrate the optimal repertoire onto a few highly abundant clones. Our predictions can be tested in high-throughput surveys of receptor and pathogen diversity."
8 days ago
Extremism In Thought Experiment Is A Vice, Actually | Thing of Things
"I think a lot of torture vs. dust specks arguers aren’t really interested in the paradoxes of utility aggregation. They’re interested in signaling that they are hard-headed people who bite bullets and come to counterintuitive ethical conclusions. And, you know, if you want to optimize your thought experiments for signaling hard-headed contrarianism, that’s your business. But you really shouldn’t pretend that it’s just a product of the tragic constraints of moral philosophy and there’s nothing you can do about it."

--- Somebody, surely, has written a good study of the rhetoric of tough-mindedness; where is it?
8 days ago
Worthwhile Canadian Initiative: When I really learned the David Ricardo idea
This is amusing, but I cannot help but observe that Rowe acted like a central planner who'd read his Kantorovich, and did not, e.g., create a market in which the department auctioned off the right to teach specific course.
10 days ago
This Watery Graveyard Is the Resting Place for 161 Sunken Spaceships
Of course our spacecraft die by leaving debris trails hundreds of miles long through the ocean. Of course we drop them on R'lyeh.
space  via:?
11 days ago
Individuality May Be a Genetic Trait, Study Suggests | Quanta Magazine
It seems fitting that (lo these many years ago) both (i) "Under precisely controlled conditions, the organism does what it damn well pleases", and (ii) to call (i) "The first Harvard law of animal behavior".
12 days ago
GNU Pricing
"As part of this deal, we will begin to add per-use fees to many of the popular GNU software we maintain, such as "ls", "dd", "cat", "grep", and many more. You can check out our pricing update and documentation on Github. Supported tools now include a "--pricing" flag so you can keep track of how much you owe us. For example, you can type "gcc --pricing" to get the amount you owe from compiling all those continuous integration deployments."
funny:geeky  funny:pointed  programming  the_wired_ideology  satire  via:?
13 days ago
Biased and Inefficient - What’s the right proof of the Continuous Mapping Theorem?
"A lot of the time I’m happy to treat advanced probability theory as a black box and just use it to call in air strikes on obstacles in the proof."

- Need to think of where to quote this in _Almost None_...
probability  funny:geeky  re:almost_none  lumley.thomas
13 days ago
Biased and Inefficient - Superefficiency
I wonder if this related to the results about how superefficiency is only possible on a computable set of parameter values?
statistics  estimation
13 days ago
Drought, agricultural adaptation, and sociopolitical collapse in the Maya Lowlands
"Paleoclimate records indicate a series of severe droughts was associated with societal collapse of the Classic Maya during the Terminal Classic period (∼800–950 C.E.). Evidence for drought largely derives from the drier, less populated northern Maya Lowlands but does not explain more pronounced and earlier societal disruption in the relatively humid southern Maya Lowlands. Here we apply hydrogen and carbon isotope compositions of plant wax lipids in two lake sediment cores to assess changes in water availability and land use in both the northern and southern Maya lowlands. We show that relatively more intense drying occurred in the southern lowlands than in the northern lowlands during the Terminal Classic period, consistent with earlier and more persistent societal decline in the south. Our results also indicate a period of substantial drying in the southern Maya Lowlands from ∼200 C.E. to 500 C.E., during the Terminal Preclassic and Early Classic periods. Plant wax carbon isotope records indicate a decline in C4 plants in both lake catchments during the Early Classic period, interpreted to reflect a shift from extensive agriculture to intensive, water-conservative maize cultivation that was motivated by a drying climate. Our results imply that agricultural adaptations developed in response to earlier droughts were initially successful, but failed under the more severe droughts of the Terminal Classic period."
to:NB  maya_civilization  archaeology  climate_change
15 days ago
The amplification of risk in experimental diffusion chains
"Understanding how people form and revise their perception of risk is central to designing efficient risk communication methods, eliciting risk awareness, and avoiding unnecessary anxiety among the public. However, public responses to hazardous events such as climate change, contagious outbreaks, and terrorist threats are complex and difficult-to-anticipate phenomena. Although many psychological factors influencing risk perception have been identified in the past, it remains unclear how perceptions of risk change when propagated from one person to another and what impact the repeated social transmission of perceived risk has at the population scale. Here, we study the social dynamics of risk perception by analyzing how messages detailing the benefits and harms of a controversial antibacterial agent undergo change when passed from one person to the next in 10-subject experimental diffusion chains. Our analyses show that when messages are propagated through the diffusion chains, they tend to become shorter, gradually inaccurate, and increasingly dissimilar between chains. In contrast, the perception of risk is propagated with higher fidelity due to participants manipulating messages to fit their preconceptions, thereby influencing the judgments of subsequent participants. Computer simulations implementing this simple influence mechanism show that small judgment biases tend to become more extreme, even when the injected message contradicts preconceived risk judgments. Our results provide quantitative insights into the social amplification of risk perception, and can help policy makers better anticipate and manage the public response to emerging threats."
15 days ago
Causal effects of the early caregiving environment on development of stress response systems in children
"Disruptions in stress response system functioning are thought to be a central mechanism by which exposure to adverse early-life environments influences human development. Although early-life adversity results in hyperreactivity of the sympathetic nervous system (SNS) and hypothalamic–pituitary–adrenal (HPA) axis in rodents, evidence from human studies is inconsistent. We present results from the Bucharest Early Intervention Project examining whether randomized placement into a family caregiving environment alters development of the autonomic nervous system and HPA axis in children exposed to early-life deprivation associated with institutional rearing. Electrocardiogram, impedance cardiograph, and neuroendocrine data were collected during laboratory-based challenge tasks from children (mean age = 12.9 y) raised in deprived institutional settings in Romania randomized to a high-quality foster care intervention (n = 48) or to remain in care as usual (n = 43) and a sample of typically developing Romanian children (n = 47). Children who remained in institutional care exhibited significantly blunted SNS and HPA axis responses to psychosocial stress compared with children randomized to foster care, whose stress responses approximated those of typically developing children. Intervention effects were evident for cortisol and parasympathetic nervous system reactivity only among children placed in foster care before age 24 and 18 months, respectively, providing experimental evidence of a sensitive period in humans during which the environment is particularly likely to alter stress response system development. We provide evidence for a causal link between the early caregiving environment and stress response system reactivity in humans with effects that differ markedly from those observed in rodent models."
to:NB  stress  psychology  neuroscience  endocrinology
15 days ago
AEAweb: JEP (29,2) p. 213 - Bitcoin: Economics, Technology, and Governance
"Bitcoin is an online communication protocol that facilitates the use of a virtual currency, including electronic payments. Bitcoin's rules were designed by engineers with no apparent influence from lawyers or regulators. Bitcoin is built on a transaction log that is distributed across a network of participating computers. It includes mechanisms to reward honest participation, to bootstrap acceptance by early adopters, and to guard against concentrations of power. Bitcoin's design allows for irreversible transactions, a prescribed path of money creation over time, and a public transaction history. Anyone can create a Bitcoin account, without charge and without any centralized vetting procedure—or even a requirement to provide a real name. Collectively, these rules yield a system that is understood to be more flexible, more private, and less amenable to regulatory oversight than other forms of payment—though as we discuss, all these benefits face important limits. Bitcoin is of interest to economists as a virtual currency with potential to disrupt existing payment systems and perhaps even monetary systems. This article presents the platform's design principles and properties for a nontechnical audience; reviews its past, present, and future uses; and points out risks and regulatory issues as Bitcoin interacts with the conventional financial system and the real economy."

---- Nothing new, but perhaps useful to have in one academically-citable place.
16 days ago
The 1% and the Rest of Us: A Political Economy of Dominant Ownership, Di Muzio
"In The 1% and the Rest of Us, Tim Di Muzio offers the first empirical and theoretical study of the culture, politics, built environments, and social behavior of this extremely wealthy minority. In doing so, he examines the fallout of this socio-economic order and its devastating consequences for the other ninety-nine percent of the population."

--- The cover image is a subtle commentary on sexism _I'm sure_.
to:NB  books:noted  inequality  political_economy  popular_social_science
18 days ago
Anatomy of Melancholy: The Best of A Softer World by Joey Comeau and Emily Horne — Kickstarter
Minus: _A Softer World_ is ending. This is very sad.
Plus: You can (in effect) pre-order their best-of collection.
a_softer_world
18 days ago
Vulnerability and power on networks
"Inspired by socio-political scenarios, like dictatorships, in which a minority of people exercise control over a majority of weakly interconnected individuals, we propose vulnerability and power measures defined on groups of actors of networks. We establish an unexpected connection between network vulnerability and graph regularizability. We use the Shapley value of coalition games to introduce fresh notions of vulnerability and power at node level defined in terms of the corresponding measures at group level. We investigate the computational complexity of computing the defined measures, both at group and node levels, and provide effective methods to quantify them. Finally we test vulnerability and power on both artificial and real networks."
to:NB  networks  power  re:do-institutions-evolve
18 days ago
In Which I Critique Your Story (That I Haven’t Read) « terribleminds: chuck wendig
"A story should look more like:
"1. HEY LOOK A PROBLEM
"2. I’M GONNA JUST GO AHEAD AND FIX THAT PROBLEM AND –
"3. OH GOD I MADE IT WORSE
"4. OH FUCK SOMEBODY ELSE IS MAKING IT WORSE TOO
"5. WAIT I THINK I GOT THIS –
"6A. SHIT SHIT SHIT
"6B. FUCK FUCK FUCK
"7. IT’S NOT JUST WORSE NOW BUT DIFFERENT
"8. EVERYTHING IS COMPLICATED
"9. ALL IS LOST
"10. WAIT, IS THAT A LIGHT AT THE END OF THE TUNNEL?
"11. IT IS BUT IT’S A VELOCIRAPTOR WITH A FLASHLIGHT IN ITS MOUTH
"12. WAIT AN IDEA
"13. I HAVE BEATEN THE VELOCIRAPTOR AND NOW I HAVE A FLASHLIGHT AND MY PROBLEMS ARE SOLVED IN PART BUT NOT TOO NEATLY BECAUSE TIDY, PAT ENDINGS MAKE STORY JESUS ANGRY, SO ANGRY THAT STORY JESUS GIVES EVERYONE MOUTH HERPES"

--- Well, that's not the _only_ way a story should look, but, yes.
19 days ago
The Social Production of Indifference: Exploring the Symbolic Roots of Western Bureaucracy, Herzfeld
"Herzfeld argues that "modern" bureaucratically regulated societies are no more "rational" or less "symbolic" than the societies traditionally studied by anthropologists. He suggests that we cannot understand national bureaucracies divorced from local-level ideas about chance, personal character, social relationships and responsibility."
in_NB  books:noted  bureaucracy  anthropology
20 days ago
Veg-O-Matic Egonomics - NYTimes.com
"All successful researchers have gigantic egos. If they didn’t — if they did not have, at the core of their being, a frightening level of intellectual arrogance — they would never have had the temerity to decide that they had insights denied to all the extremely clever scholars who preceded them. And it takes even more egotism to persist in the face of all the people who will, in fact, tell you that your insight is trivial, it’s wrong, and they said it in 1962.
"So we’re all monsters, however nice we may seem in person. But there’s still the matter of self-awareness and self-control — the ability to set limits, to avoid the temptation to spend your life claiming that the insights you had decades ago were the final word on the subject, maybe even the final word on all subjects."

--- The rest of the post is worthwhile, but of more transient interest than those paragraphs.
moral_psychology  science_as_a_social_process  intellectuals  krugman.paul
20 days ago
Lag threads organize the brain’s intrinsic activity
"It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term “lag threads,” are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals."
to:NB  neuroscience  fmri  functional_connectivity  spatio-temporal_statistics
24 days ago
Experimental Studies of Cumulative Culture in Modern Humans: What Are the Requirements of the Ratchet? - Springer
"The success of Homo sapiens as a species may be explained, at least in part, by their learning abilities. The archaeological record suggests that the material culture of humans during the Palaeolithic was fluid and diverse. Social learning abilities may therefore have allowed Homo sapiens to adapt rapidly to novel or changeable environmental conditions. A capacity for cumulative cultural evolution is certainly apparent in all contemporary human societies, whereas it appears either absent or extremely rare in other extant species. Here I review laboratory studies of cumulative culture in modern adult humans, designed to shed light on the social information required for this type of learning to occur. Although it has been suggested that cumulative culture may depend on a capacity for imitation, we found that imitation (at least in the narrow sense of action copying) was not necessary for human participants to exhibit ratchet-like effects of improvement over learner generations. We discuss the need for high fidelity reproduction in cumulative culture (independent of action copying)."
to:NB  cultural_evolution  experimental_psychology  experimental_sociology  cultural_transmission  social_life_of_the_mind  re:do-institutions-evolve  epidemiology_of_representations
25 days ago
Inferring Learning Strategies from Cultural Frequency Data - Springer
"Social learning has been identified as one of the fundamentals of culture and therefore the understanding of why and how individuals use social information presents one of the big questions in cultural evolution. To date much of the theoretical work on social learning has been done in isolation of data. Evolutionary models often provide important insight into which social learning strategies are expected to have evolved but cannot tell us which strategies human populations actually use. In this chapter we explore how much information about the underlying learning strategies can be extracted by analysing the temporal occurrence or usage patterns of different cultural variants in a population. We review the previous methodology that has attempted to infer the underlying social learning processes from such data, showing that they may apply statistical methods with insufficient power to draw reliable inferences. We then introduce a generative inference framework that allows robust inferences on the social learning processes that underlie cultural frequency data. Using developments in population genetics—in the form of generative simulation modelling and approximate Bayesian computation—as our model, we demonstrate the strength of this method with an example based on simulated data."
to:NB  social_learning  cultural_evolution  statistics  phylogenetics  approximate_bayesian_computation  to_read  re:do-institutions-evolve
25 days ago
How wedding dresses got so expensive and roast chickens got so cheap - Vox
Referring to "making up a story" as "economic naturalism" is either horridly sarcastic or deeply oblivious, and Frank does not appear to be sarcastic at all. What's conspicuously missing from this is _any pretense of gathering empirical evidence_ to _check the proposed explanation_. God knows there are problems with the myth of "scientific method" that gets taught in junior high, but here at least it would be an improvement. As it is, there's no more value to his, or his students', stories about costs than there would've been to a psychoanalyst's stories.

N.B., despite my criticism on this point, Frank has done much excellent work, and he's actually much better about trying to make contact with reality than many of his colleagues. The issue is that _even_ Frank is awful about this.