13120
Connecting in College: How Friendship Networks Matter for Academic and Social Success, McCabe
"We all know that good study habits, supportive parents, and engaged instructors are all keys to getting good grades in college. But as Janice M. McCabe shows in this illuminating study, there is one crucial factor determining a student’s academic success that most of us tend to overlook: who they hang out with. Surveying a range of different kinds of college friendships, Connecting in College details the fascinatingly complex ways students’ social and academic lives intertwine and how students attempt to balance the two in their pursuit of straight As, good times, or both.
"As McCabe and the students she talks to show, the friendships we forge in college are deeply meaningful, more meaningful than we often give them credit for. They can also vary widely. Some students have only one tight-knit group, others move between several, and still others seem to meet someone new every day. Some students separate their social and academic lives, while others rely on friendships to help them do better in their coursework. McCabe explores how these dynamics lead to different outcomes and how they both influence and are influenced by larger factors such as social and racial inequality. She then looks toward the future and how college friendships affect early adulthood, ultimately drawing her findings into a set of concrete solutions to improve student experiences and better guarantee success in college and beyond."
to:NB  books:noted  academia  education  social_networks  re:homophily_and_confounding 
3 hours ago
Medieval Islamic Maps: An Exploration, Pinto
"Hundreds of exceptional cartographic images are scattered throughout medieval and early modern Arabic, Persian, and Turkish manuscript collections. The plethora of copies created around the Islamic world over the course of eight centuries testifies to the enduring importance of these medieval visions for the Muslim cartographic imagination. With Medieval Islamic Maps, historian Karen C. Pinto brings us the first in-depth exploration of medieval Islamic cartography from the mid-tenth to the nineteenth century.
"Pinto focuses on the distinct tradition of maps known collectively as the Book of Roads and Kingdoms (Kitab al-Masalik wa al-Mamalik, or KMMS), examining them from three distinct angles—iconography, context, and patronage. She untangles the history of the KMMS maps, traces their inception and evolution, and analyzes them to reveal the identities of their creators, painters, and patrons, as well as the vivid realities of the social and physical world they depicted.  In doing so, Pinto develops innovative techniques for approaching the visual record of Islamic history, explores how medieval Muslims perceived themselves and their world, and brings Middle Eastern maps into the forefront of the study of the history of cartography. "
to:NB  medieval_eurasian_history  islamic_civilization  history_of_science  maps  books:noted 
3 hours ago
Dictionary of Indo-European Concepts and Society, Benveniste, Palmer, Agamben
"Since its publication in 1969, Émile Benveniste’s Vocabulaire—here in a new translation as the Dictionary of Indo-European Concepts and Society—has been the classic reference for tracing the institutional and conceptual genealogy of the sociocultural worlds of gifts, contracts, sacrifice, hospitality, authority, freedom, ancient economy, and kinship. A comprehensive and comparative history of words with analyses of their underlying neglected genealogies and structures of signification—and this via a masterful journey through Germanic, Romance, Indo-Iranian, Latin, and Greek languages—Benveniste’s dictionary is a must-read for anthropologists, linguists, literary theorists, classicists, and philosophers alike."
to:NB  books:noted  ancient_history  anthropology  indo-europeans  linguistics 
4 hours ago
The Invention of Culture, Wagner, Ingold
"In anthropology, a field that is known for its critical edge and intellectual agility, few books manage to maintain both historical value and contemporary relevance. Roy Wagner's The Invention of Culture, originally published in 1975, is one.
"Wagner breaks new ground by arguing that culture arises from the dialectic between the individual and the social world. Rooting his analysis in the relationships between invention and convention, innovation and control, and meaning and context, he builds a theory that insists on the importance of creativity, placing people-as-inventors at the heart of the process that creates culture. In an elegant twist, he shows that this very process ultimately produces the discipline of anthropology itself.
"Tim Ingold’s foreword to the new edition captures the exhilaration of Wagner’s book while showing how the reader can journey through it and arrive safely—though transformed—on the other side."
to:NB  books:noted  anthropology  cultural_evolution 
4 hours ago
Evolution Made to Order: Plant Breeding and Technological Innovation in Twentieth-Century America, Curry
"In the mid-twentieth century, American plant breeders, frustrated by their dependence on natural variation in creating new crops and flowers, eagerly sought technologies that could extend human control over nature. Their search led them to celebrate a series of strange tools: an x-ray beam directed at dormant seeds, a drop of chromosome-altering colchicine on a flower bud, and a piece of radioactive cobalt in a field of growing crops. According to scientific and popular reports of the time, these mutation-inducing methods would generate variation on demand, in turn allowing breeders to genetically engineer crops and flowers to order. Creating a new crop or flower would soon be as straightforward as innovating any other modern industrial product.
"In Evolution Made to Order, Helen Anne Curry traces the history of America’s pursuit of tools that could speed up evolution. It is an immersive journey through the scientific and social worlds of midcentury genetics and plant breeding and a compelling exploration of American cultures of innovation. As Curry reveals, the creation of genetic technologies was deeply entangled with other areas of technological innovation—from electromechanical to chemical to nuclear. An important study of biological research and innovation in America, Evolution Made to Order provides vital historical context for current worldwide ethical and policy debates over genetic engineering."
to:NB  books:noted  history_of_science  history_of_technology  biology  genetics 
4 hours ago
The Diversity Bargain: And Other Dilemmas of Race, Admissions, and Meritocracy at Elite Universities, Warikoo
"We’ve heard plenty from politicians and experts on affirmative action and higher education, about how universities should intervene—if at all—to ensure a diverse but deserving student population. But what about those for whom these issues matter the most? In this book, Natasha K. Warikoo deeply explores how students themselves think about merit and race at a uniquely pivotal moment: after they have just won the most competitive game of their lives and gained admittance to one of the world’s top universities.
"What Warikoo uncovers—talking with both white students and students of color at Harvard, Brown, and Oxford—is absolutely illuminating; and some of it is positively shocking. As she shows, many elite white students understand the value of diversity abstractly, but they ignore the real problems that racial inequality causes and that diversity programs are meant to solve. They stand in fear of being labeled a racist, but they are quick to call foul should a diversity program appear at all to hamper their own chances for advancement. The most troubling result of this ambivalence is what she calls the “diversity bargain,” in which white students reluctantly agree with affirmative action as long as it benefits them by providing a diverse learning environment—racial diversity, in this way, is a commodity, a selling point on a brochure. And as Warikoo shows, universities play a big part in creating these situations. The way they talk about race on campus and the kinds of diversity programs they offer have a huge impact on student attitudes, shaping them either toward ambivalence or, in better cases, toward more productive and considerate understandings of racial difference.
"Ultimately, this book demonstrates just how slippery the notions of race, merit, and privilege can be. In doing so, it asks important questions not just about college admissions but what the elite students who have succeeded at it—who will be the world’s future leaders—will do with the social inequalities of the wider world."
to:NB  books:noted  diversity  affirmative_action  racism  academia 
4 hours ago
Data-Centric Biology: A Philosophical Study, Leonelli
"In recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves?
" Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices."
to:NB  books:noted  history_of_science  philosophy_of_science  bioinformatics  biology 
4 hours ago
Conquest and Community: The Afterlife of Warrior Saint Ghazi Miyan, Amin
"Few topics in South Asian history are as contentious as that of the Turkic conquest of the Indian subcontinent that began in the twelfth century and led to a long period of Muslim rule. How is a historian supposed to write honestly about the bloody history of the conquest without falling into communitarian traps?
"Conquest and Community is Shahid Amin's answer. Covering more than eight hundred years of history, the book centers on the enduringly popular saint Ghazi Miyan, a youthful soldier of Islam whose shrines are found all over India. Amin details the warrior saint’s legendary exploits, then tracks the many ways he has been commemorated in the centuries since. The intriguing stories, ballads, and proverbs that grew up around Ghazi Miyan were, Amin shows, a way of domesticating the conquest—recognizing past conflicts and differences but nevertheless bringing diverse groups together into a community of devotees. What seems at first glance to be the story of one mythical figure becomes an allegory for the history of Hindu-Muslim relations over an astonishingly long period of time, and a timely contribution to current political and historical debates."
to:NB  books:noted  history  history_of_religion  epidemiology_of_representations  india  islam 
11 hours ago
Bleak Liberalism, Anderson
"Why is liberalism so often dismissed by thinkers from both the left and the right? To those calling for wholesale transformation or claiming a monopoly on “realistic” conceptions of humanity, liberalism’s assured progressivism can seem hard to swallow. Bleak Liberalism makes the case for a renewed understanding of the liberal tradition, showing that it is much more attuned to the complexity of political life than conventional accounts have acknowledged.
"Amanda Anderson examines canonical works of high realism, political novels from England and the United States, and modernist works to argue that liberalism has engaged sober and even stark views of historical development, political dynamics, and human and social psychology. From Charles Dickens’s Bleak House and Hard Times to E. M. Forster’s Howards End to Doris Lessing’s The Golden Notebook, this literature demonstrates that liberalism has inventive ways of balancing sociological critique and moral aspiration. A deft blend of intellectual history and literary analysis, Bleak Liberalism reveals a richer understanding of one of the most important political ideologies of the modern era."
to:NB  books:noted  liberalism  defenses_of_liberalism  political_philosophy  literary_criticism 
11 hours ago
How to Make a Meaningful Comparison of Models: The Church–Turing Thesis Over the Reals | SpringerLink
"It is commonly believed that there is no equivalent of the Church–Turing thesis for computation over the reals. In particular, computational models on this domain do not exhibit the convergence of formalisms that supports this thesis in the case of integer computation. In the light of recent philosophical developments on the different meanings of the Church–Turing thesis, and recent technical results on analog computation, I will show that this current belief confounds two distinct issues, namely the extension of the notion of effective computation to the reals on the one hand, and the simulation of analog computers by Turing machines on the other hand. I will argue that it is possible in both cases to defend an equivalent of the Church–Turing thesis over the reals. Along the way, we will learn some methodological caveats on the comparison of different computational models, and how to make it meaningful."
to:NB  theoretical_computer_science  computation 
11 hours ago
What American Government Does
"It has become all too easy to disparage the role of the US government today. Many Americans are influenced by a simplistic anti-government ideology that is itself driven by a desire to roll back the more democratically responsive aspects of public policy. But government has improved the lives of Americans in numerous ways, from providing income, food, education, housing, and healthcare support, to ensuring cleaner air, water, and food, to providing a vast infrastructure upon which economic growth depends.
"In What American Government Does, Stan Luger and Brian Waddell offer a practical understanding of the scope and function of American governance. They present a historical overview of the development of US governance that is rooted in the theoretical work of Charles Tilly, Karl Polanyi, and Michael Mann. Touching on everything from taxes, welfare, and national and domestic security to the government’s regulatory, developmental, and global responsibilities, each chapter covers a main function of American government and explains how it emerged and then evolved over time. Luger and Waddell are careful to both identify the controversies related to what government does and those areas of government that should elicit concern and vigilance. Analyzing the functions of the US government in terms of both a tug-of-war and a collaboration between state and societal forces, they provide a reading of American political development that dispels the myth of a weak, minimal, non-interventionist state."
to:NB  books:noted  us_politics  american_history 
11 hours ago
What they don’t teach you at STEM school | Meaningness
Interesting, but a comprehensive (and valid!) refutation of nihilism as an intermediate step does bring to mind "I think you should be a bit more specific here in step 2". (Also: ethnomethodology as the key to everything, _really_? Even if you accept its findings on their own terms [and Gellner had a great essay back in the day on why you shouldn't], it's just question-begging about how people have the capacity for those sorts of social interactions, so we're off to the races again. But I'd probably enjoy having these arguments with the author.)
rationality  limits_of_rationality  systems  philosophy  epistemology  via:vaguery  have_read  cognition 
14 hours ago
The Good Life in the Scientific Revolution: Descartes, Pascal, Leibniz, and the Cultivation of Virtue, Jones
"Amid the unrest, dislocation, and uncertainty of seventeenth-century Europe, readers seeking consolation and assurance turned to philosophical and scientific books that offered ways of conquering fears and training the mind—guidance for living a good life.
"The Good Life in the Scientific Revolution presents a triptych showing how three key early modern scientists, René Descartes, Blaise Pascal, and Gottfried Leibniz, envisioned their new work as useful for cultivating virtue and for pursuing a good life. Their scientific and philosophical innovations stemmed in part from their understanding of mathematics and science as cognitive and spiritual exercises that could create a truer mental and spiritual nobility.  In portraying the rich contexts surrounding Descartes’ geometry, Pascal’s arithmetical triangle, and Leibniz’s calculus, Matthew L. Jones argues that this drive for moral therapeutics guided important developments of early modern philosophy and the Scientific Revolution."

--- No Bacon? No Spinoza?
to:NB  books:noted  scientific_revolution  moral_philosophy  history_of_science  history_of_morals  descartes.rene  pascal.blaise  leibniz.g.w. 
15 hours ago
Reckoning with Matter: Calculating Machines, Innovation, and Thinking about Thinking from Pascal to Babbage, Jones
"From Blaise Pascal in the 1600s to Charles Babbage in the first half of the nineteenth century, inventors struggled to create the first calculating machines. All failed—but that does not mean we cannot learn from the trail of ideas, correspondence, machines, and arguments they left behind.
"In Reckoning with Matter, Matthew L. Jones draws on the remarkably extensive and well-preserved records of the quest to explore the concrete processes involved in imagining, elaborating, testing, and building calculating machines. He explores the writings of philosophers, engineers, and craftspeople, showing how they thought about technical novelty, their distinctive areas of expertise, and ways they could coordinate their efforts. In doing so, Jones argues that the conceptions of creativity and making they exhibited are often more incisive—and more honest—than those that dominate our current legal, political, and aesthetic culture."
to:NB  books:noted  history_of_technology  history_of_ideas  pre-cognitivism  computers  innovation  pascal.blaise  leibniz.g.w.  babbage.charles 
15 hours ago
The Phoenix: An Unnatural Biography of a Mythical Beast, Nigg
"Arising triumphantly from the ashes of its predecessor, the phoenix has been an enduring symbol of resilience and renewal for thousands of years. But how did this mythical bird become so famous that it has played a part in cultures around the world and throughout human history? How much of its story do we actually know? Here to offer a comprehensive biography and engaging (un)natural history of the phoenix is Joseph Nigg, esteemed expert on mythical creatures—from griffins and dragons to sea monsters.
"Beginning in ancient Egypt and traveling around the globe and through the centuries, Nigg’s vast and sweeping narrative takes readers on a brilliant tour of the cross-cultural lore of this famous, yet little-known, immortal bird. Seeking both the similarities and the differences in the phoenix’s many myths and representations, Nigg describes its countless permutations over millennia, including legends of the Chinese “phoenix,” which was considered one of the sacred creatures that presided over China’s destiny; classical Greece and Rome, where it can be found in the writings of Herodotus and Ovid; nascent and medieval Christianity, in which it came to embody the resurrection; and in Europe during the Renaissance, when it was a popular emblem of royals. Nigg examines the various phoenix traditions, the beliefs and tales associated with them, their symbolic and metaphoric use, the skepticism and speculation they’ve raised, and their appearance in religion, bestiaries, and even contemporary popular culture, in which the ageless bird of renewal is employed as a mascot and logo, including for our own University of Chicago.
"Never bested by hardship or defeated by death, the phoenix is the ultimate icon of hope and rebirth. And in The Phoenix: An Unnatural Biography of a Mythical Beast, it finally has its due—a complete chronicle worthy of such a fantastic and phantasmal creature. This entertaining and informative look at the life and transformation of the phoenix will be the authoritative source for anyone fascinated by folklore and mythology, re-igniting our curiosity about one of myth’s greatest beasts."
to:NB  books:noted  mythology 
15 hours ago
Partisans and Partners: The Politics of the Post-Keynesian Society, Pacewicz
"There’s no question that Americans are bitterly divided by politics. But in Partisans and Partners, Josh Pacewicz finds that our traditional understanding of red/blue, right/left, urban/rural division is too simplistic.
"Wheels-down in Iowa—that most important of primary states—Pacewicz looks to two cities, one traditionally Democratic, the other traditionally Republican, and finds that younger voters are rejecting older-timers’ strict political affiliations. A paradox is emerging—as the dividing lines between America’s political parties have sharpened, Americans are at the same time growing distrustful of traditional party politics in favor of becoming apolitical or embracing outside-the-beltway candidates. Pacewicz sees this change coming not from politicians and voters, but from the fundamental reorganization of the community institutions in which political parties have traditionally been rooted. Weaving together major themes in American political history—including globalization, the decline of organized labor, loss of locally owned industries, uneven economic development, and the emergence of grassroots populist movements—Partisans and Partners is a timely and comprehensive analysis of American politics as it happens on the ground."

--- I can't tell from this whether the author mightn't wish for an opportunity to revise and extend their remarks...
to:NB  books:noted  us_politics  ethnography  our_decrepit_institutions  whats_gone_wrong_with_america 
15 hours ago
Mathematical Structures in Languages, Keenan, Moss
"Mathematical Structures in Languages introduces a number of mathematical concepts that are of interest to the working linguist. The areas covered include basic set theory and logic, formal languages and automata, trees, partial orders, lattices, Boolean structure,  generalized quantifier theory, and linguistic invariants, the last drawing on Edward L. Keenan and Edward Stabler’s Bare Grammar: A Study of Language Invariants, also published by CSLI Publications. Ideal for advanced undergraduate and graduate students of linguistics, this book contains numerous exercises and will be a valuable resource for courses on mathematical topics in linguistics. The product of many years of teaching, Mathematic Structures in Languages is very much a book to be read and learned from."
to:NB  books:noted  mathematics  logic  linguistics 
15 hours ago
Reconstructing Karl Polanyi, Dale
"Karl Polanyi was one of the most influential political economists of the twentieth-century and is widely regarded as the most gifted of social democrat theorists. In Reconstructing Karl Polanyi, Gareth Dale draws upon primary sources archived in the countries that Polanyi called home—Hungary, Austria, Britain, the United States, and Canada—to provide a sweeping survey of his contribution to the social sciences.
"Polanyi’s intellectual and political outlook can best be summarized through paradoxical formulations such as ‘romantic modernist’, ‘liberal socialist’, and ‘cosmopolitan patriot.’ In exploring these paradoxes, Dale excavates and reconstructs Polanyi’s views on a range of topics that have been neglected in the critical literature, including Keynesian economic policy, the evolution and dynamics of Stalin’s Russia, regional integration, and McCarthyism. He reinterprets Polanyi’s philosophy of history, his theory of democracy, and his economic historiography of Ancient Greece and Mesopotamia, and guides readers through Polyani's critical dialogue with Marxism.  
"While the central threads and motifs of this study are intellectual-historiographical in nature, Dale also critically analyzes the views of Polanyi and his followers on issues of pressing present-day relevance, notably the clash between democracy and capitalism, and the nature and trajectory of European unification."
to:NB  books:noted  lives_of_the_scholars  economics  economic_history  polyani.karl  progressive_forces 
15 hours ago
Energy Humanities
"Energy humanities is a field of scholarship that, like medical and digital humanities before it, aims to overcome traditional boundaries between the disciplines and between academic and applied research. Responding to growing public concern about anthropogenic climate change and the unsustainability of the fuels we use to power our modern society, energy humanists highlight the essential contribution that humanistic insights and methods can make to areas of analysis once thought best left to the natural sciences.
"In this groundbreaking anthology, Imre Szeman and Dominic Boyer have brought together a carefully curated selection of the best and most influential work in energy humanities. In just the past decade, the humanities have witnessed a remarkable efflorescence of research that is beginning to receive recognition by scientists, government officials, and industry. Arguing that today’s energy and environmental dilemmas are fundamentally problems of ethics, habits, imagination, values, institutions, belief, and power—all traditional areas of expertise of the humanities and humanistic social sciences—the essays featured here demonstrate the scale and complexity of the issues the world faces. They also offer compelling possibilities for finding our way beyond our current energy dependencies toward a sustainable future.
"Staying true to the diverse work that makes up this emergent field, selections range from anthropology and geography to philosophy, history, and cultural studies to recent energy-focused interventions in art and literature. Energy Humanities will appeal to scholars and students across the disciplines, especially those concerned with environmental issues and social justice, as well as anyone concerned with our shared planet and the challenges of political, social, and environmental change."
to:NB  books:noted  literary_criticism  cultural_criticism  climate_change  to_be_shot_after_a_fair_trial 
16 hours ago
Seizing Power: The Strategic Logic of Military Coups
"While coups drive a majority of regime changes and are responsible for the overthrow of many democratic governments, there has been very little empirical work on the subject. Seizing Power develops a new theory of coup dynamics and outcomes, drawing on 300 hours of interviews with coup participants and an original dataset of 471 coup attempts worldwide from 1950 to 2000. Naunihal Singh delivers a concise and empirical evaluation, arguing that understanding the dynamics of military factions is essential to predicting the success or failure of coups.
"Singh draws on an aspect of game theory known as a coordination game to explain coup dynamics. He finds a strong correlation between successful coups and the ability of military actors to project control and the inevitability of success. Examining Ghana’s multiple coups and the 1991 coup attempt in the USSR, Singh shows how military actors project an image of impending victory that is often more powerful than the reality on the ground.
"In addition, Singh also identifies three distinct types of coup dynamics, each with a different probability of success, based on where within the organization each coup originated: coups from top military officers, coups from the middle ranks, and mutinous coups from low-level soldiers."

--- Wonder how much this advances over the old Luttwak book...
to:NB  books:noted  political_science  coup_d'etat  game_theory 
16 hours ago
Universities and Their Cities: Urban Higher Education in America
"Today, a majority of American college students attend school in cities. But throughout the nineteenth and much of the twentieth century, urban colleges and universities faced deep hostility from writers, intellectuals, government officials, and educators who were concerned about the impact of cities, immigrants, and commuter students on college education. In Universities and Their Cities, Steven J. Diner explores the roots of American colleges’ traditional rural bias. Why were so many people, including professors, uncomfortable with nonresident students? How were the missions and activities of urban universities influenced by their cities? And how, improbably, did much-maligned urban universities go on to profoundly shape contemporary higher education across the nation?
"Surveying American higher education from the early nineteenth century to the present, Diner examines the various ways in which universities responded to the challenges offered by cities. In the years before World War II, municipal institutions struggled to "build character" in working class and immigrant students. In the postwar era, universities in cities grappled with massive expansion in enrollment, issues of racial equity, the problems of "disadvantaged" students, and the role of higher education in addressing the "urban crisis." Over the course of the twentieth century, urban higher education institutions greatly increased the use of the city for teaching, scholarly research on urban issues, and inculcating civic responsibility in students. In the final decades of the century, and moving into the twenty-first century, university location in urban areas became increasingly popular with both city-dwelling students and prospective resident students, altering the long tradition of anti-urbanism in American higher education.
"Drawing on the archives and publications of higher education organizations and foundations, Universities and Their Cities argues that city universities brought about today’s commitment to universal college access by reaching out to marginalized populations. Diner shows how these institutions pioneered the development of professional schools and PhD programs. Finally, he considers how leaders of urban higher education continuously debated the definition and role of an urban university. Ultimately, this book is a considered and long overdue look at the symbiotic impact of these two great American institutions: the city and the university."
to:NB  books:noted  education  academia  cities  american_history 
16 hours ago
Reading Galileo: Scribal Technologies and _Two New Sciences_
"In 1638, Galileo was over seventy years old, blind, and confined to house arrest outside of Florence. With the help of friends and family, he managed to complete and smuggle to the Netherlands a manuscript that became his final published work, Two New Sciences. Treating diverse subjects that became the foundations of mechanical engineering and physics, this book is often depicted as the definitive expression of Galileo’s purportedly modern scientific agenda. In Reading Galileo, Renée Raphael offers a new interpretation of Two New Sciences which argues instead that the work embodied no such coherent canonical vision. Raphael alleges that it was written—and originally read—as the eclectic product of the types of discursive textual analysis and meandering descriptive practices Galileo professed to reject in favor of more qualitative scholarship.
"Focusing on annotations period readers left in the margins of extant copies and on the notes and teaching materials of seventeenth-century university professors whose lessons were influenced by Galileo’s text, Raphael explores the ways in which a range of early-modern readers, from ordinary natural philosophers to well-known savants, responded to Galileo. She highlights the contrast between the practices of Galileo’s actual readers, who followed more traditional, "bookish" scholarly methods, and their image, constructed by Galileo and later historians, as "modern" mathematical experimenters.
"Two New Sciences has not previously been the subject of such rigorous attention and analysis. Reading Galileo considerably changes our understanding of Galileo’s important work while offering a well-executed case study in the reception of an early-modern scientific classic. This important text will be of interest to a wide range of historians—of science, of scholarly practices and the book, and of early-modern intellectual and cultural history."

--- This hardly seems like a contradiction. Surely it's _possible_ both that Galileo intended his book in a "modern" way, and that many people read it in a much older fashion?
to:NB  books:noted  history_of_science  early_modern_european_history  reception_history  galileo  scientific_revolution  the_printing_press_as_an_agent_of_change 
16 hours ago
The myth of the Rust Belt revolt.
"Compared with 2012, three times as many voters in the Rust Belt who made under $100,000 voted for third parties. Twice as many voted for alternative or write-in candidates. Similarly, compared with 2012, some 500,000 more voters chose to sit out this presidential election. If there was a Rust Belt revolt this year, it was the voters’ flight from both parties.
"In short, the story of a white working-class revolt in the Rust Belt just doesn't hold up, according to the numbers. In the Rust Belt, Democrats lost 1.35 million voters. Trump picked up less than half, at 590,000. The rest stayed home or voted for someone other than the major party candidates.
"This data suggests that if the Democratic Party wants to win the Rust Belt, it should not go chasing after the white working-class men who voted for Trump. The party should spend its energy figuring out why Democrats lost millions of voters to some other candidate or to abstention. Exit polls do not collect information about why voters stay home. Perhaps it’s time someone asked them."
us_politics  track_down_references 
yesterday
Book - Colin Crouch - The Knowledge Corrupters: Hidden Consequences of the Financial Takeover of Public Life
"In principle the advanced, market-driven world in which we now live is fuelled by knowledge, information and transparency, but in practice the processes that produce this world systematically corrupt and denigrate knowledge: this is the powerful and provocative argument advanced by Colin Crouch in his latest exploration of societies on the road to post-democracy."
Crouch shows that executives in profit-maximizing corporations have incentives to ignore or distort knowledge, especially firms in the information business of the mass media themselves, as financial knowledge increasingly trumps the other kinds of knowledge that business needs. Firms also seek to take control of public knowledge and use it for their own ends, often at the cost of other stakeholders in society. Meanwhile the transfer of similar practices to professional public services undermines professional skills and ethics - especially when these services are out-sourced to the private sector. Attempts to extricate ourselves from these problems involve reshaping the complex and often conflicting relationships among citizens, professionals, managers and financiers.
to:NB  books:noted  deceiving_us_has_become_an_industrial_process  natural_history_of_truthiness  crouch.colin  social_life_of_the_mind  via:henry_farrell 
yesterday
The Rule of Logistics: Walmart and the Architecture of Fulfillment — University of Minnesota Press
"How the world’s largest retailer is redefining architecture by organizing flows of merchandise and information across space and time
"Jesse LeCavalier analyzes Walmart’s stores, distribution centers, databases, and inventory practices to make sense of its spatial and architectural ramifications. A major new contribution to architectural history and theory, The Rule of Logistics helps us understand how retailing today is changing our bodies, brains, buildings, and cities."
to:NB  books:noted  logistics  architecture  business  cultural_criticism  economics  design  via:? 
yesterday
NetSim
"One of the key challenges in today’s social networks research is to understand the link between dynamic micro-models that describe behavior of individuals and macro-outcomes that describe social networks as a whole. NetSim is a flexible R package that allows to simulate and combine a variety of micro-models to research their impact on the macro-features of social networks."
via:?  social_networks  network_data_analysis  statistics  to_teach:baby-nets 
yesterday
[1611.05923] "Influence Sketching": Finding Influential Samples In Large-Scale Regressions
"There is an especially strong need in modern large-scale data analysis to prioritize samples for manual inspection. For example, the inspection could target important mislabeled samples or key vulnerabilities exploitable by an adversarial attack. In order to solve the "needle in the haystack" problem of which samples to inspect, we develop a new scalable version of Cook's distance, a classical statistical technique for identifying samples which unusually strongly impact the fit of a regression model (and its downstream predictions). In order to scale this technique up to very large and high-dimensional datasets, we introduce a new algorithm which we call "influence sketching." Influence sketching embeds random projections within the influence computation; in particular, the influence score is calculated using the randomly projected pseudo-dataset from the post-convergence General Linear Model (GLM). We validate that influence sketching can reliably and successfully discover influential samples by applying the technique to a malware detection dataset of over 2 million executable files, each represented with almost 100,000 features. For example, we find that randomly deleting approximately 10% of training samples reduces predictive accuracy only slightly from 99.47% to 99.45%, whereas deleting the same number of samples with high influence sketch scores reduces predictive accuracy all the way down to 90.24%. Moreover, we find that influential samples are especially likely to be mislabeled. In the case study, we manually inspect the most influential samples, and find that influence sketching pointed us to new, previously unidentified pieces of malware."
to:NB  regression  linear_regression  computational_statistics  random_projections  via:vaguery 
yesterday
Chicago Police Try to Predict Who May Shoot or Be Shot - The New York Times
They're referencing good sociology, but the use of a closed, secret program is indefensible.
have_read  data_mining  social_networks  chicago  crime  police  surveillance 
yesterday
[1611.06928] Memory Lens: How Much Memory Does an Agent Use?
"We propose a new method to study the internal memory used by reinforcement learning policies. We estimate the amount of relevant past information by estimating mutual information between behavior histories and the current action of an agent. We perform this estimation in the passive setting, that is, we do not intervene but merely observe the natural behavior of the agent. Moreover, we provide a theoretical justification for our approach by showing that it yields an implementation-independent lower bound on the minimal memory capacity of any agent that implement the observed policy. We demonstrate our approach by estimating the use of memory of DQN policies on concatenated Atari frames, demonstrating sharply different use of memory across 49 games. The study of memory as information that flows from the past to the current action opens avenues to understand and improve successful reinforcement learning algorithms."

--- *pettily* Ahem, Shalizi and Crutchfield (2001), and Shalizi (2001, ch. 7) [to be fair, cited, but the things which supposedly distinguish their approach are in fact explicitly handled]. */pettily*
to:NB  to_read  information_theory  learning_in_games  predictive_states 
yesterday
Democratic politics have to be “identity politics.”
"Certainly, Democrats should champion the interests of working people. They should struggle to expand the social safety net and defend the labor movement against conservative attempts to destroy it. They should work to preserve the gains of the Affordable Care Act, even for those Trump supporters who just voted to gut their own health care. But there can be no going back on defending the tenuous gains of women and people of color, or foregrounding their demands for full equality. They are the base of the party, the people who gave Hillary Clinton a popular vote majority but will now be ruled by a hostile minority.
"Trump may very well oversee the end of abortion as a constitutional right in America. He wants to register members of a religious minority. His vice president is vehemently opposed to laws protecting gay people from discrimination. Lilla’s prose is vague, so I’m not sure what he considers to be the “proper sense of scale” in responding to these threats. I am sure liberals should not respond to them quietly. Trump’s nominee for attorney general is a racist opponent of the Voting Rights Act and must be stopped whether or not a campaign against him appeals to white Americans. The focus of left-of-center politics in the dark years to come must be on protecting the groups of people who are targets precisely because of their identities. To sideline their interests is to accede to a backlash that has just begun and will only get worse. If Democrats standing up for diversity makes Trump voters feel disrespected, the best response is a slogan popular among enemies of political correctness at Trump rallies: Fuck your feelings."
us_politics  have_read  goldberg.michelle 
2 days ago
Cowie, J.: The Great Exception: The New Deal and the Limits of American Politics. (eBook, Paperback and Hardcover)
"Where does the New Deal fit in the big picture of American history? What does it mean for us today? What happened to the economic equality it once engendered? In The Great Exception, Jefferson Cowie provides new answers to these important questions. In the period between the Great Depression and the 1970s, he argues, the United States government achieved a unique level of equality, using its considerable resources on behalf of working Americans in ways that it had not before and has not since. If there is to be a comparable battle for collective economic rights today, Cowie argues, it needs to build on an understanding of the unique political foundation for the New Deal. Anyone who wants to come to terms with the politics of inequality in the United States will need to read The Great Exception."
in_NB  books:noted  american_history  the_new_deal  class_struggles_in_america 
2 days ago
[1311.4555] Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife
"We study the variability of predictions made by bagged learners and random forests, and show how to estimate standard errors for these methods. Our work builds on variance estimates for bagging proposed by Efron (1992, 2012) that are based on the jackknife and the infinitesimal jackknife (IJ). In practice, bagged predictors are computed using a finite number B of bootstrap replicates, and working with a large B can be computationally expensive. Direct applications of jackknife and IJ estimators to bagging require B on the order of n^{1.5} bootstrap replicates to converge, where n is the size of the training set. We propose improved versions that only require B on the order of n replicates. Moreover, we show that the IJ estimator requires 1.7 times less bootstrap replicates than the jackknife to achieve a given accuracy. Finally, we study the sampling distributions of the jackknife and IJ variance estimates themselves. We illustrate our findings with multiple experiments and simulation studies."
to:NB  bootstrap  confidence_sets  ensemble_methods  random_forests  decision_trees  statistics  nonparametrics  efron.bradley  hastie.trevor 
2 days ago
[1311.5768] An RKHS Approach to Estimation with Sparsity Constraints
"The investigation of the effects of sparsity or sparsity constraints in signal processing problems has received considerable attention recently. Sparsity constraints refer to the a priori information that the object or signal of interest can be represented by using only few elements of a predefined dictionary. Within this thesis, sparsity refers to the fact that a vector to be estimated has only few nonzero entries. One specific field concerned with sparsity constraints has become popular under the name Compressed Sensing (CS). Within CS, the sparsity is exploited in order to perform (nearly) lossless compression. Moreover, this compression is carried out jointly or simultaneously with the process of sensing a physical quantity. In contrast to CS, one can alternatively use sparsity to enhance signal processing methods. Obviously, sparsity constraints can only improve the obtainable estimation performance since the constraints can be interpreted as an additional prior information about the unknown parameter vector which is to be estimated. Our main focus will be on this aspect of sparsity, i.e., we analyze how much we can gain in estimation performance due to the sparsity constraints."
to:NB  sparsity  compressed_sensing  hilbert_space  estimation  statistics 
2 days ago
[1611.06168] On $p$-values
"Models are consistently treated as approximations and all procedures are consistent with this. They do not treat the model as being true. In this context p-values are one measure of approximation, a small p-value indicating a poor approximation. Approximation regions are defined and distinguished from confidence regions."
to:NB  statistics  misspecification  approximation  p-values  hypothesis_testing  via:vaguery 
2 days ago
HUD Games - MTV
"Trump's lurching transition to the presidency has run roughshod over so many norms it’s easy to get drawn into describing the whole fantastic, mesmerizing spectacle rather than each somewhat ordinary catastrophe."
us_politics  our_decrepit_institutions  mortgage_crisis 
5 days ago
After Piketty — Heather Boushey, J. Bradford DeLong, Marshall Steinbaum | Harvard University Press
"Thomas Piketty’s Capital in the Twenty-First Century is the most widely discussed work of economics in recent history, selling millions of copies in dozens of languages. But are its analyses of inequality and economic growth on target? Where should researchers go from here in exploring the ideas Piketty pushed to the forefront of global conversation? A cast of economists and other social scientists tackle these questions in dialogue with Piketty, in what is sure to be a much-debated book in its own right.
"After Piketty opens with a discussion by Arthur Goldhammer, the book’s translator, of the reasons for Capital’s phenomenal success, followed by the published reviews of Nobel laureates Paul Krugman and Robert Solow. The rest of the book is devoted to newly commissioned essays that interrogate Piketty’s arguments. Suresh Naidu and other contributors ask whether Piketty said enough about power, slavery, and the complex nature of capital. Laura Tyson and Michael Spence consider the impact of technology on inequality. Heather Boushey, Branko Milanovic, and others consider topics ranging from gender to trends in the global South. Emmanuel Saez lays out an agenda for future research on inequality, while a variety of essayists examine the book’s implications for the social sciences more broadly. Piketty replies to these questions in a substantial concluding chapter."
to:NB  books:noted  coveted  economics  inequality  political_economy  economic_history  delong.brad  naidu.suresh  piketty.thomas 
5 days ago
you have to do this work – Fredrik deBoer
"The conventional wisdom within progressive media is that this is a phony controversy: trigger warnings are optional for professors, not mandatory, and they’re just warnings, so they can’t censor anything. I have heard this line more times than I can count. The fact that it isn’t true seems unimportant to the people who push it. In fact the initial wave of debate about trigger warnings flared up precisely because there were people calling for them to be mandatory and because there were arguments that classroom material that carried trigger warnings should be optional. Here is a UCSB student government resolution calling for exactly that. They are not alone in that call. “No one says students should be able to use trigger warnings to opt out of course materials” is simply untrue. It is a dodge, a very common one in this discussion. It is a means for sympathetic voices in the media to avoid precisely the difficult intellectual and political questions at hand. That this insistence that “no one is calling for” what some people in my world are explicitly calling for comes packaged with smug eye-rolling only makes it more aggravating."
academia  academic_freedom  education  progressive_forces  deboer.frederik  have_read 
5 days ago
[1311.6392] A Comprehensive Approach to Universal Piecewise Nonlinear Regression Based on Trees
"In this paper, we investigate adaptive nonlinear regression and introduce tree based piecewise linear regression algorithms that are highly efficient and provide significantly improved performance with guaranteed upper bounds in an individual sequence manner. We use a tree notion in order to partition the space of regressors in a nested structure. The introduced algorithms adapt not only their regression functions but also the complete tree structure while achieving the performance of the "best" linear mixture of a doubly exponential number of partitions, with a computational complexity only polynomial in the number of nodes of the tree. While constructing these algorithms, we also avoid using any artificial "weighting" of models (with highly data dependent parameters) and, instead, directly minimize the final regression error, which is the ultimate performance goal. The introduced methods are generic such that they can readily incorporate different tree construction methods such as random trees in their framework and can use different regressor or partitioning functions as demonstrated in the paper."
to:NB  regression  decision_trees  nonparametrics  statistics  ensemble_methods  to_be_shot_after_a_fair_trial 
5 days ago
[1311.6359] Score-based Causal Learning in Additive Noise Models
"Given data sampled from a number of variables, one is often interested in the underlying causal relationships in the form of a directed acyclic graph. In the general case, without interventions on some of the variables it is only possible to identify the graph up to its Markov equivalence class. However, in some situations one can find the true causal graph just from observational data, for example in structural equation models with additive noise and nonlinear edge functions. Most current methods for achieving this rely on nonparametric independence tests. One of the problems there is that the null hypothesis is independence, which is what one would like to get evidence for. We take a different approach in our work by using a penalized likelihood as a score for model selection. This is practically feasible in many settings and has the advantage of yielding a natural ranking of the candidate models. When making smoothness assumptions on the probability density space, we prove consistency of the penalized maximum likelihood estimator. We also present empirical results for simulated scenarios and real two-dimensional data sets (cause-effect pairs) where we obtain similar results as other state-of-the-art methods."
to:NB  causal_inference  causal_discovery  additive_models  statistics  buhlmann.peter 
5 days ago
[1311.6425] Robust Multimodal Graph Matching: Sparse Coding Meets Graph Matching
"Graph matching is a challenging problem with very important applications in a wide range of fields, from image and video analysis to biological and biomedical problems. We propose a robust graph matching algorithm inspired in sparsity-related techniques. We cast the problem, resembling group or collaborative sparsity formulations, as a non-smooth convex optimization problem that can be efficiently solved using augmented Lagrangian techniques. The method can deal with weighted or unweighted graphs, as well as multimodal data, where different graphs represent different types of data. The proposed approach is also naturally integrated with collaborative graph inference techniques, solving general network inference problems where the observed variables, possibly coming from different modalities, are not in correspondence. The algorithm is tested and compared with state-of-the-art graph matching techniques in both synthetic and real graphs. We also present results on multimodal graphs and applications to collaborative inference of brain connectivity from alignment-free functional magnetic resonance imaging (fMRI) data. The code is publicly available."
to:NB  to_read  network_comparison  graph_theory  network_data_analysis  statistics  information_theory  re:network_differences 
5 days ago
[1311.5954] Robust Vertex Classification
"For random graphs distributed according to stochastic blockmodels, a special case of latent position graphs, adjacency spectral embedding followed by appropriate vertex classification is asymptotically Bayes optimal; but this approach requires knowledge of and critically depends on the model dimension. In this paper, we propose a sparse representation vertex classifier which does not require information about the model dimension. This classifier represents a test vertex as a sparse combination of the vertices in the training set and uses the recovered coefficients to classify the test vertex. We prove consistency of our proposed classifier for stochastic blockmodels, and demonstrate that the sparse representation classifier can predict vertex labels with higher accuracy than adjacency spectral embedding approaches via both simulation studies and real data experiments. Our results demonstrate the robustness and effectiveness of our proposed vertex classifier when the model dimension is unknown."
to:NB  spectral_clustering  stochastic_block_models  network_data_analysis  community_discovery  classifiers  statistics 
5 days ago
Chaurasia , Harel : Model selection rates of information based criteria
"Model selection criteria proposed over the years have become common procedures in applied research. This article examines the true model selection rates of any model selection criteria; with true model meaning the data generating model. The rate at which model selection criteria select the true model is important because the decision of model selection criteria affects both interpretation and prediction.
"This article provides a general functional form for the mean function of the true model selection rates process, for any model selection criteria. Until now, no other article has provided a general form for the mean function of true model selection rate processes. As an illustration of the general form, this article provides the mean function for the true model selection rates of two commonly used model selection criteria, Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC). The simulations reveal deeper insight into properties of consistency and efficiency of AIC and BIC. Furthermore, the methodology proposed here for tracking the mean function of model selection procedures, which is based on accuracy of selection, lends itself for determining sufficient sample size in linear models for reliable inference in model selection."
to:NB  model_selection  statistics  information_criteria 
5 days ago
[1311.6756] Stochastic Mechanistic Interaction
"We propose a fully probabilistic formulation of the notion of mechanistic interaction (interaction in some fundamental mechanistic sense) between the effects of putative (possibly continuous) causal factors A and B on a binary outcome variable Y indicating 'survival' vs 'failure'. We define mechanistic interaction in terms of departure from a generalized 'noisy OR' model, under which the multiplicative causal effect of A (resp., B) on the probability of failure cannot be enhanced by manipulating B (resp., A). We present conditions under which mechanistic interaction in the above sense can be assessed via simple tests on excess risk or superadditivity, in a possibly retrospective regime of observation. These conditions are defined in terms of generalized conditional independence relationships (generalised because they may involve non-stochastic 'regime indicators') that can often be checked on a graphical representation of the problem. Inference about mechanistic interaction between direct, or path-specific, causal effects can be accommodated in the proposed framework. The method is illustrated with the aid of a study in experimental psychology."
to:NB  causal_inference  graphical_models  statistics  dawid.a._philip 
5 days ago
[1311.6765] Hypothesis testing by convex optimization
"We discuss a general approach to handling "multiple hypotheses" testing in the case when a particular hypothesis states that the vector of parameters identifying the distribution of observations belongs to a convex compact set associated with the hypothesis. With our approach, this problem reduces to testing the hypotheses pairwise. Our central result is a test for a pair of hypotheses of the outlined type which, under appropriate assumptions, is provably nearly optimal. The test is yielded by a solution to a convex programming problem, so that our construction admits computationally efficient implementation. We further demonstrate that our assumptions are satisfied in several important and interesting applications. Finally, we show how our approach can be applied to a rather general detection problem encompassing several classical statistical settings such as detection of abrupt signal changes, cusp detection and multi-sensor detection."
to:NB  statistics  hypothesis_testing  convexity 
5 days ago
[1210.6516] The RKHS Approach to Minimum Variance Estimation Revisited: Variance Bounds, Sufficient Statistics, and Exponential Families
"The mathematical theory of reproducing kernel Hilbert spaces (RKHS) provides powerful tools for minimum variance estimation (MVE) problems. Here, we extend the classical RKHS based analysis of MVE in several directions. We develop a geometric formulation of five known lower bounds on the estimator variance (Barankin bound, Cramer-Rao bound, constrained Cramer-Rao bound, Bhattacharyya bound, and Hammersley-Chapman-Robbins bound) in terms of orthogonal projections onto a subspace of the RKHS associated with a given MVE problem. We show that, under mild conditions, the Barankin bound (the tightest possible lower bound on the estimator variance) is a lower semicontinuous function of the parameter vector. We also show that the RKHS associated with an MVE problem remains unchanged if the observation is replaced by a sufficient statistic. Finally, for MVE problems conforming to an exponential family of distributions, we derive novel closed-form lower bound on the estimator variance and show that a reduction of the parameter set leaves the minimum achievable variance unchanged."
to:NB  hilbert_space  cramer-rao  estimation  statistics  sufficiency  exponential_families 
5 days ago
[1212.6788] Local and global asymptotic inference in smoothing spline models
"This article studies local and global inference for smoothing spline estimation in a unified asymptotic framework. We first introduce a new technical tool called functional Bahadur representation, which significantly generalizes the traditional Bahadur representation in parametric models, that is, Bahadur [Ann. Inst. Statist. Math. 37 (1966) 577-580]. Equipped with this tool, we develop four interconnected procedures for inference: (i) pointwise confidence interval; (ii) local likelihood ratio testing; (iii) simultaneous confidence band; (iv) global likelihood ratio testing. In particular, our confidence intervals are proved to be asymptotically valid at any point in the support, and they are shorter on average than the Bayesian confidence intervals proposed by Wahba [J. R. Stat. Soc. Ser. B Stat. Methodol. 45 (1983) 133-150] and Nychka [J. Amer. Statist. Assoc. 83 (1988) 1134-1143]. We also discuss a version of the Wilks phenomenon arising from local/global likelihood ratio testing. It is also worth noting that our simultaneous confidence bands are the first ones applicable to general quasi-likelihood models. Furthermore, issues relating to optimality and efficiency are carefully addressed. As a by-product, we discover a surprising relationship between periodic and nonperiodic smoothing splines in terms of inference."
to:NB  nonparametrics  splines  regression  confidence_sets  statistics 
5 days ago
Stationary-Sparse Causality Network Learning
"Recently, researchers have proposed penalized maximum likelihood to identify network topology underlying a dynamical system modeled by multivariate time series. The time series of interest are assumed to be stationary, but this restriction is never taken into consideration by existing estimation methods. Moreover, practical problems of interest may have ultra-high dimensionality and obvious node collinearity. In addition, none of the available algorithms provides a probabilistic measure of the uncertainty for the obtained network topology which is informative in reliable network identification. The main purpose of this paper is to tackle these challenging issues. We propose the S2 learning framework, which stands for stationary- sparse network learning. We propose a novel algorithm referred to as the Berhu iterative sparsity pursuit with stationarity (BISPS), where the Berhu regularization can improve the Lasso in detection and estimation. The algorithm is extremely easy to implement, efficient in computation and has a theoretical guarantee to converge to a global optimum. We also incorporate a screening technique into BISPS to tackle ultra- high dimensional problems and enhance computational efficiency. Furthermore, a stationary bootstrap technique is applied to provide connection occurring frequency for reliable topology learning. Experiments show that our method can achieve stationary and sparse causality network learning and is scalable for high-dimensional problems."
to:NB  time_series  graphical_models  statistics  books:noted  high-dimensional_statistics  causal_discovery  to_be_shot_after_a_fair_trial 
5 days ago
[1311.5066] Some context-specific graphical models for discrete longitudinal data
"Ron et al (1998) introduced a rich family of models for discrete longitudinal data, called acyclic probabilistic finite automata. These may be described as context-specific graphical models, since they are represented as directed multigraphs that embody context-specific conditional independence relations. Here we develop the methodology from a statistical modelling perspective. We show how likelihood ratio tests may be constructed using standard contingency table methods, and indicate how these may be used in model selection. We also show that the models generalize certain subclasses of conventional undirected and directed graphical models."
to:NB  graphical_models  time_series  model_selection  statistics 
5 days ago
[1311.2079] Nonparametric Multi-group Membership Model for Dynamic Networks
"Relational data-like graphs, networks, and matrices-is often dynamic, where the relational structure evolves over time. A fundamental problem in the analysis of time-varying network data is to extract a summary of the common structure and the dynamics of the underlying relations between the entities. Here we build on the intuition that changes in the network structure are driven by the dynamics at the level of groups of nodes. We propose a nonparametric multi-group membership model for dynamic networks. Our model contains three main components: We model the birth and death of individual groups with respect to the dynamics of the network structure via a distance dependent Indian Buffet Process. We capture the evolution of individual node group memberships via a Factorial Hidden Markov model. And, we explain the dynamics of the network structure by explicitly modeling the connectivity structure of groups. We demonstrate our model's capability of identifying the dynamics of latent groups in a number of different types of network data. Experimental results show that our model provides improved predictive performance over existing dynamic network models on future network forecasting and missing link prediction."
to:NB  network_data_analysis  community_discovery  statistics  time_series  leskovec.jure 
5 days ago
[1311.3257] Compressive Nonparametric Graphical Model Selection For Time Series
"We propose a method for inferring the conditional indepen- dence graph (CIG) of a high-dimensional discrete-time Gaus- sian vector random process from finite-length observations. Our approach does not rely on a parametric model (such as, e.g., an autoregressive model) for the vector random process; rather, it only assumes certain spectral smoothness proper- ties. The proposed inference scheme is compressive in that it works for sample sizes that are (much) smaller than the number of scalar process components. We provide analytical conditions for our method to correctly identify the CIG with high probability."
to:NB  graphical_models  time_series  causal_discovery  statistics 
5 days ago
Janzing , Balduzzi , Grosse-Wentrup , Schölkopf : Quantifying causal influences
"Many methods for causal inference generate directed acyclic graphs (DAGs) that formalize causal relations between n variables. Given the joint distribution on all these variables, the DAG contains all information about how intervening on one variable changes the distribution of the other n−1 variables. However, quantifying the causal influence of one variable on another one remains a nontrivial question.
"Here we propose a set of natural, intuitive postulates that a measure of causal strength should satisfy. We then introduce a communication scenario, where edges in a DAG play the role of channels that can be locally corrupted by interventions. Causal strength is then the relative entropy distance between the old and the new distribution.
"Many other measures of causal strength have been proposed, including average causal effect, transfer entropy, directed information, and information flow. We explain how they fail to satisfy the postulates on simple DAGs of ≤3 nodes. Finally, we investigate the behavior of our measure on time-series, supporting our claims with experiments on simulated data."
to:NB  graphical_models  time_series  causality  statistics  information_theory  to_read  re:ADAfaEPoV  to_teach:undergrad-ADA 
5 days ago
[1311.4500] Time series prediction via aggregation : an oracle bound including numerical cost
"We address the problem of forecasting a time series meeting the Causal Bernoulli Shift model, using a parametric set of predictors. The aggregation technique provides a predictor with well established and quite satisfying theoretical properties expressed by an oracle inequality for the prediction risk. The numerical computation of the aggregated predictor usually relies on a Markov chain Monte Carlo method whose convergence should be evaluated. In particular, it is crucial to bound the number of simulations needed to achieve a numerical precision of the same order as the prediction risk. In this direction we present a fairly general result which can be seen as an oracle inequality including the numerical cost of the predictor computation. The numerical cost appears by letting the oracle inequality depend on the number of simulations required in the Monte Carlo approximation. Some numerical experiments are then carried out to support our findings."
to:NB  prediction  time_series  statistics  computational_statistics  monte_carlo  ensemble_methods 
5 days ago
[1211.1547] A note on p-values interpreted as plausibilities
"P-values are a mainstay in statistics but are often misinterpreted. We propose a new interpretation of p-value as a meaningful plausibility, where this is to be interpreted formally within the inferential model framework. We show that, for most practical hypothesis testing problems, there exists an inferential model such that the corresponding plausibility function, evaluated at the null hypothesis, is exactly the p-value. The advantages of this representation are that the notion of plausibility is consistent with the way practitioners use and interpret p-values, and the plausibility calculation avoids the troublesome conditioning on the truthfulness of the null. This connection with plausibilities also reveals a shortcoming of standard p-values in problems with non-trivial parameter constraints."
to:NB  p-values  hypothesis_testing  statistics  to_be_shot_after_a_fair_trial 
5 days ago
Phys. Rev. E 88, 052810 (2013) - Network reliability: The effect of local network structure on diffusive processes
"This paper reintroduces the network reliability polynomial, introduced by Moore and Shannon [Moore and Shannon, J. Franklin Inst. 262, 191 (1956)], for studying the effect of network structure on the spread of diseases. We exhibit a representation of the polynomial that is well suited for estimation by distributed simulation. We describe a collection of graphs derived from Erdős-Rényi and scale-free-like random graphs in which we have manipulated assortativity-by-degree and the number of triangles. We evaluate the network reliability for all of these graphs under a reliability rule that is related to the expected size of a connected component. Through these extensive simulations, we show that for positively or neutrally assortative graphs, swapping edges to increase the number of triangles does not increase the network reliability. Also, positively assortative graphs are more reliable than neutral or disassortative graphs with the same number of edges. Moreover, we show the combined effect of both assortativity-by-degree and the presence of triangles on the critical point and the size of the smallest subgraph that is reliable."
to:NB  networks  graphical_models  epidemic_models 
5 days ago
Sequential Learning, Predictability, and Optimal Portfolio Returns - JOHANNES - 2014 - The Journal of Finance - Wiley Online Library
"This paper finds statistically and economically significant out-of-sample portfolio benefits for an investor who uses models of return predictability when forming optimal portfolios. Investors must account for estimation risk, and incorporate an ensemble of important features, including time-varying volatility, and time-varying expected returns driven by payout yield measures that include share repurchase and issuance. Prior research documents a lack of benefits to return predictability, and our results suggest that this is largely due to omitting time-varying volatility and estimation risk. We also document the sequential process of investors learning about parameters, state variables, and models as new data arrive."
to:NB  finance  prediction  time_series  online_learning 
5 days ago
[1308.4123] A Likelihood Ratio Approach for Probabilistic Inequalities
"We propose a new approach for deriving probabilistic inequalities based on bounding likelihood ratios. We demonstrate that this approach is more general and powerful than the classical method frequently used for deriving concentration inequalities such as Chernoff bounds. We discover that the proposed approach is inherently related to statistical concepts such as monotone likelihood ratio, maximum likelihood, and the method of moments for parameter estimation. A connection between the proposed approach and the large deviation theory is also established. We show that, without using moment generating functions, tightest possible concentration inequalities may be readily derived by the proposed approach. We have derived new concentration inequalities using the proposed approach, which cannot be obtained by the classical approach based on moment generating functions."
to:NB  deviation_inequalities  probability  large_deviations  to_be_shot_after_a_fair_trial  information_theory 
5 days ago
[1307.5396] Star graphs induce tetrad correlations: for Gaussian as well as for binary variables
"Tetrad correlations were obtained historically for Gaussian distributions when tasks are designed to measure an ability or attitude so that a single unobserved variable may generate the observed, linearly increasing dependences among the tasks. We connect such generating processes to a particular type of directed graph, the star graph, and to the notion of traceable regressions. Tetrad correlation conditions for the existence of a single latent variable are derived. These are needed for positive dependences not only in joint Gaussian but also in joint binary distributions. Three applications with binary items are given."
to:NB  graphical_models  statistics  re:g_paper  factor_analysis  warmuth.nanny  to_read 
5 days ago
[1311.5828] The Splice Bootstrap
"This paper proposes a new bootstrap method to compute predictive intervals for nonlinear autoregressive time series model forecast. This method we call the splice boobstrap as it involves splicing the last p values of a given series to a suitably simulated series. This ensures that each simulated series will have the same set of p time series values in common, a necessary requirement for computing conditional predictive intervals. Using simulation studies we show the methods gives 90% intervals intervals that are similar to those expected from theory for simple linear and SETAR model driven by normal and non-normal noise. Furthermore, we apply the method to some economic data and demonstrate the intervals compare favourably with cross-validation based intervals."
to:NB  bootstrap  time_series  statistics  prediction  to_teach:undergrad-ADA  re:ADAfaEPoV  to_read 
5 days ago
America: This Is Your Future
Shorter: bruces's "Old people in cities, afraid of the sky" needs to add "and their neighbors".
demography  futurology  us_politics  goldstein.dana  have_read 
5 days ago
The irrational hungry judge effect revisited: Simulations reveal that the magnitude of the effect is overestimated
"Danziger, Levav and Avnaim-Pesso (2011) analyzed legal rulings of Israeli parole boards concerning the effect of serial order in which cases are presented within ruling sessions. They found that the probability of a favorable decision drops from about 65% to almost 0% from the first ruling to the last ruling within each session and that the rate of favorable rulings returns to 65% in a session following a food break. The authors argue that these findings provide support for extraneous factors influencing judicial decisions and cautiously speculate that the effect might be driven by mental depletion. A simulation shows that the observed influence of order can be alternatively explained by a statistical artifact resulting from favorable rulings taking longer than unfavorable ones. An effect of similar magnitude would be produced by a (hypothetical) rational judge who plans ahead minimally and ends a session instead of starting cases that he or she assumes will take longer directly before the break. One methodological detail further increased the magnitude of the artifact and generates it even without assuming any foresight concerning the upcoming case. Implications for this article are discussed and the increased application of simulations to identify nonobvious rational explanations is recommended."

--- The proposed mechanism should be easy enough to check, no?
to:NB  to_read  debunking  decision-making  psychology 
6 days ago
Multifractal network generator
"We introduce a new approach to constructing networks with realistic features. Our method, in spite of its conceptual simplicity (it has only two parameters) is capable of generating a wide variety of network types with prescribed statistical properties, e.g., with degree or clustering coefficient distributions of various, very different forms. In turn, these graphs can be used to test hypotheses or as models of actual data. The method is based on a mapping between suitably chosen singular measures defined on the unit square and sparse infinite networks. Such a mapping has the great potential of allowing for graph theoretical results for a variety of network topologies. The main idea of our approach is to go to the infinite limit of the singular measure and the size of the corresponding graph simultaneously. A very unique feature of this construction is that with the increasing system size the generated graphs become topologically more structured. We present analytic expressions derived from the parameters of the—to be iterated—initial generating measure for such major characteristics of graphs as their degree, clustering coefficient, and assortativity coefficient distributions. The optimal parameters of the generating measure are determined from a simple simulated annealing process. Thus, the present work provides a tool for researchers from a variety of fields (such as biology, computer science, biology, or complex systems) enabling them to create a versatile model of their network data."
to:NB  networks  network_data_analysis  graph_limits 
7 days ago
Public Knowledge
"This paper argues that the public can do more than legitimate government; it can provide public knowledge for sound public policy. Critics of democracy worry that the public has too little objectivity and impartiality to know what is best. These critics have a point: taken one by one, people have little knowledge of the whole. For this reason, citizens need to escape the cloisters of kith and kin and enter a world of unlike others. They need to be open to other perspectives and concerns. They need to deliberate with others in public. In other words, an inchoate plurality of people needs to become public in order to develop a more comprehensive picture of the whole and to define ‘where the shoe pinches’. Democracy requires that the multitude deliberate publicly in order to create public knowledge by which sound public policy can be formed."
to:NB  to_read  democracy  social_life_of_the_mind  collective_cognition  re:democratic_cognition  mcafee.noelle 
7 days ago
Links Between Multiplicity Automata, Observable Operator Models and Predictive State Representations -- a Unified Learning Framework
"Stochastic multiplicity automata (SMA) are weighted finite automata that generalize probabilistic automata. They have been used in the context of probabilistic grammatical inference. Observable operator models (OOMs) are a generalization of hidden Markov models, which in turn are models for discrete-valued stochastic processes and are used ubiquitously in the context of speech recognition and bio-sequence modeling. Predictive state representations (PSRs) extend OOMs to stochastic input-output systems and are employed in the context of agent modeling and planning.
"We present SMA, OOMs, and PSRs under the common framework of sequential systems, which are an algebraic characterization of multiplicity automata, and examine the precise relationships between them. Furthermore, we establish a unified approach to learning such models from data. Many of the learning algorithms that have been proposed can be understood as variations of this basic learning scheme, and several turn out to be closely related to each other, or even equivalent."
to:NB  re:AoS_project  stochastic_processes  statistics  prediction  state-space_models  automata_theory 
7 days ago
Detecting Causality in Complex Ecosystems | Science
"Identifying causal networks is important for effective policy and management recommendations on climate, epidemiology, financial regulation, and much else. We introduce a method, based on nonlinear state space reconstruction, that can distinguish causality from correlation. It extends to nonseparable weakly connected dynamic systems (cases not covered by the current Granger causality paradigm). The approach is illustrated both by simple models (where, in contrast to the real world, we know the underlying equations/relations and so can check the validity of our method) and by application to real ecological systems, including the controversial sardine-anchovy-temperature problem."
to:NB  statistics  ecology  causal_inference  to_be_shot_after_a_fair_trial  time_series  state_reconstruction 
7 days ago
How social and genetic factors predict friendship networks
"Recent research suggests that the genotype of one individual in a friendship pair is predictive of the genotype of his/her friend. These results provide tentative support for the genetic homophily perspective, which has important implications for social and genetic epidemiology because it substantiates a particular form of gene–environment correlation. This process may also have important implications for social scientists who study the social factors related to health and health-related behaviors. We extend this work by considering the ways in which school context shapes genetically similar friendships. Using the network, school, and genetic information from the National Longitudinal Study of Adolescent Health, we show that genetic homophily for the TaqI A polymorphism within the DRD2 gene is stronger in schools with greater levels of inequality. Our results suggest that individuals with similar genotypes may not actively select into friendships; rather, they may be placed into these contexts by institutional mechanisms outside of their control. Our work highlights the fundamental role played by broad social structures in the extent to which genetic factors explain complex behaviors, such as friendships."
to:NB  social_networks  human_genetics  sociology  homophily 
7 days ago
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