#quantitative methodologist

[dataanxiety]

via FOCUS: Complexity and the failure of quantitative social science 

Is this just so much woo? The following is supposedly the wrong paradigm: 

the history of statistics in the social sciences is one of great achievement but also error; and the basis for both is the belief that disorganized complexity constitutes the major challenge to social scientific inquiry.

Disorganized complexity 

It seems more than adequately daunting, no? If the results make sense and the analysis is tractable, the conventional quantitative program in the social sciences is approached as follows: 

social reality is a form of disorganized complexity, which is best handled using the tools of statistics; 

the goal is to explain majority, aggregate behavior in terms of probability theory and the macroscopic laws of averages; 

to do so, one seeks to develop simple, variable-based linear models, in which variables are treated as ‘rigorously real’ measures of social reality; 

model-in-hand, the goal is to identify, measure, describe and (hopefully) control or manage how certain independent variables impact one or more dependent variables of concern; 

and, if done right, these models lead to reasonably linear explanations of why things happen the way they do; 

which, in turn, leads to relatively straightforward policy recommendations for what to do about them.

Organized complexity less tractable than disorganized complexity?

But no! Social reality is a form of organized complexity which is much more difficult!  In order to do social science one needs to study and discuss (through college coursework): 

philosophy and sociology of science, post-positivism and pragmatism, feminism and feminist methodology, pragmatism and anti-positivism, critical realism and neo-pragmatism, ecofeminism and systems theory, social constructionism and social constructivism, 2nd order cybernetics and post-structuralism, qualitative method and historiography, ethnography and deconstructionism, actor-network theory and postmodernism.

To grapple with the complicated modern world of complex organized complexity, scholars must contend with a “data-saturated world of social problems far beyond the pale of conventional quantitative social science”. 

A revolution in computational methods

Over the past 30 years, this revolution in method contains some of the most highly innovative tools and techniques ever created, from geospatial modeling and complex network analysis to dynamical systems theory and nonlinear statistical mechanics to multi-agent modeling and artificial neural nets to cellular automata and data mining to data visualization and case-based modeling.

Hmm, okay, I guess. 

the common view amongst complexity scholars is that social reality and the data used to examine it are best understood, methodologically speaking, in organized complex systems terms.  In other words, social reality and data are best seen as self-organizing, emergent, nonlinear, evolving, dynamic, network-based, interdependent, qualitative and non-reductive.

So how do social scientists learn how to do this?  Recall that the message is “statistics isn’t enough”. The recommendation: 

it is not so much that the social sciences would need to be proficient in calculus, computational analysis, and nonlinear statistical mechanics!  Hardly. Instead, an open learning environment would need to be created, where students could be introduced to new and innovative notions of complexity, critical thinking, data visualization and modeling, as well as the challenges of mixed-methods, interdisciplinary teamwork, global complexity, and big data!

I think that is what people who do PhD level work in sociology do now. Interdisciplinary team work and critical thinking is nothing new. 

Finally, we get to what sounds like one of those impossible, ridiculous job descriptions, where the candidate should know everything: 

...while the overwhelming majority of physicists, mathematicians and computational scientists are incredible technicians and methodologists, most are not very good social scientists.  In turn, the overwhelming majority of social scientists are not very good technicians or methodologists.  And, both sides are at fault for not extending their reach, and both are foolish for not doing so.

LOL

Find me a physicist or mathematician who is also a good social scientist!  There are a few, e.g. Andrew Gelman, PhD in statistics from Harvard, and Columbia University professor of sociology. And even he doesn’t have great intuition or common sense despite being ahead of the rest, and technically excellent, or so political scientists say. Academia isn’t going to turn out thousands or even hundreds of Andrew Gelmans regardless of curriculum changes. 

Nice, colorful chart, but my verdict is woo. I would be delighted to be corrected though.

[attorneyandlawyer]

HOW TO CHOOSE THE RIGHT RESEARCH MEASUREMENT INSTRUMENT

HOW TO CHOOSE THE RIGHT RESEARCH MEASUREMENT INSTRUMENT

Measurement instrument refers to various methods through which a researcher obtains data from respondents for his research work. The term data refers to all forms of information that researchers obtain from the participant of the study. Adedokun (2003:57) asserts that data refers “to any fact, observation or facts relating to the subject of…

[wordstitta]

Pingree quant center

She is a member of the House Appropriations Committee and has worked with her colleagues on fully funding the Forest Service budget and the EDA. Pingree has worked work with the rest of Maine’s Congressional Delegation to bring an Economic Development Assessment Team (EDAT) to Maine to study ways to revitalize the state's forest products economy and bring federal resources to implement the team’s recommendations. The emergence of this new innovation based industry cluster will result in positive economic impacts to both local and regional economies, particularly in Maine’s rural communities.” The Center will team up with industrial partners, trade organizations, construction firms, architects, and other stakeholders in the region to revitalize and diversify Maine’s forest-based economy by bringing innovative mass timber manufacturing to the State of Maine. According to the EDA, “This EDA investment funds the creation of the Maine Mass Timber Commercialization Center, based at the University of Maine. The Economic Development Administration i6 grant is for $454,532. Mass timber products, such as cross-laminated timber, have the increased strength needed to build taller, multi-story buildings than with conventional lumber. Pingree Center Bruges driving directions. I’m excited to see what developments come out of the Maine Mass Timber Commercialization Center and have been proud to work with Maine’s Congressional Delegation to help bring federal resources to help write the next chapter of Maine’s forest products industry.” “With our natural resources and hard-working labor force, Maine is in a great position to capitalize on that potential. a broad understanding of the way quantitative reasoning informs and. The University of Maine has done fantastic work in this regard, notably in mass timber products that can compete with concrete and steel in building practices,” said Congresswoman Pingree. Exciting opportunity in South Hamilton, MA for Pingree School as a Math Teacher. “The first step to revitalizing Maine’s critical forest products industry-and bringing back the jobs it has supported for generations-is finding and commercializing new innovations for those products. Whether the focus is on brainstorming, structuring an essay, incorporating evidence, or processing feedback on essays and research papers, conferences further enable students to reflect on the writing process and learn strategies to become more critical readers and analytical writers.Congresswoman Chellie Pingree (D-ME) today welcomed news of a major federal grant from the Economic Development Administration to create the Maine Mass Timber Commercialization Center at the University of Maine. Through 1-on-1 or small group conferences, student writers learn to talk through their ideas in order to clearly communicate with their readers. Students who frequent the Writing Center learn to become advocates for their self-expression as they embrace revision and ultimately find personal success. Whether students seek an opportunity to merely discuss how they might approach an assignment, to make final revisions, or for help with their college application essays, they find that as they become more involved with their writing, they become better critical readers, thinkers, and writers who can clearly articulate their ideas. As a highly collaborative applied quantitative research methodologist, I have focused my scholarship, teaching and leadership roles on. Students come to the Writing Center to talk about writing assignments and essays throughout their four years at Pingree. Click Here for Appointments and Citations

[desirablebabyy]

The absence of QA(Quality Assurance) in server Hardening. - 4 pages research pap

The absence of QA(Quality Assurance) in server Hardening. – 4 pages research pap

The absence of QA(Quality Assurance) in server Hardening. – 4 pages research paper and slides 10 Abstract introduction Problem Statement Purpose statement Background of the problem Significance (value of the research) Choice of methodologist Qualitive research Quantitative research   Conclusion Recommendation must follow -APA format -citations -references

[charliebroger-blog]

Social Science Methodology: A Unified Framework (Strategies for Social Inquiry)

John Gerring

John Gerring's exceptional textbook has been thoroughly revised in this second edition. It offers a one-volume introduction to social science methodology relevant to the disciplines of anthropology, economics, history, political science, psychology and sociology. This new edition has been extensively developed with the introduction of new material and a thorough treatment of essential elements such as conceptualization, measurement, causality and research design. It is written for students, long-time practitioners and methodologists and covers both qualitative and quantitative methods. It synthesizes the vast and diverse field of methodology in a way that is clear, concise and comprehensive. While offering a handy overview of the subject, the book is also an argument about how we should conceptualize methodological problems. Thinking about methodology through this lens provides a new framework for understanding work in the social sciences.

[jeki2011-blog]

Literary Economy: On “The Routledge Companion to Literature and Economics”

John Macintosh

I

THE INTRODUCTION TO The Routledge Companion to Literature and Economics, edited by Matt Seybold and Michelle Chihara, aims “to examine the complex and counterintuitive relationship between the two disciplines which gave this companion its title.” What follows is a compelling interdisciplinary history that begins with the literary inclinations of political economists Adam Smith, John Stuart Mill, Karl Marx, and John Maynard Keynes. Although these political economists were steeped in literature and culture, Seybold and Chihara identify two turns that sent political economy on a different path. The marginal revolution of the late 19th century brought a new theory of value: subjective value and marginal utility were in; the labor theory of value was out. More definitively, in the 20th century, the Keynesian synthesis supposedly brought neoclassical microeconomics into accord with Keynes’s macroeconomic theory. Economists “increasingly severed themselves from their disciplinary roots in philosophy, rhetoric, and politics, seeking to style themselves as scientists inspired by mathematics, physics, and engineering.” By shedding this political economic skin, the emerging discipline of economics sought to leave behind the vagaries of people and politics for the clean rationalities of math and models.

In Foundations of Economic Analysis (1947), the influential US economist Paul Samuelson solidified mathematics as the economic lingua franca. By the third edition of his textbook, Economics (1955), Samuelson consolidated the neoclassical synthesis and argued that it was “accepted in its broad outlines by all but about 5 per cent of extreme left wing and right wing writers.” Economic historian Philip Mirowski argues this consensus was won through the concerted “exile of history and philosophy from any place within the contemporary economic orthodoxy.” Mirowski writes:

After a brief flirtation in the 1960s and ’70s, the grandees of the [economic] profession took it upon themselves to express their disdain and scorn for the types of self-reflection practiced by “methodologists” and historians of economics, and to go out of their way to prevent those so inclined from occupying any tenured foothold in reputable economics departments. It was perhaps no coincidence that history and philosophy were the areas where one found greatest concentrations of skeptics concerning the shape and substance of the postwar American economic orthodoxy.

Top economics departments and journals policed a methodological orthodoxy. Economic history courses dwindled. Historical and philosophical debate were supplanted by quantitative analysis. The Nobel Memorial Prize in Economic Sciences, a mock Nobel established by Sweden’s central bank in 1968, helped to popularize modern economics as a scientific discourse. (Ragnar Frisch and Jan Tinbergen, two founders of econometrics, were the first laureates in 1969; Samuelson had to wait until the next year.) Mainstream economists may not self-identify as neoclassical today, but mathematical modeling retains a stranglehold on the discipline. Although traditions of heterodox economics exist, they have often been marginalized, and much debate and dissent has come from outside the discipline itself.

Where was the discipline of literary studies during this mathematical turn in economics? A through-line of Marxist literary criticism notwithstanding, Seybold and Chihara note that by the mid-20th century, “English and Economics departments each indulged their own brand of navel-gazing formalism, their repudiation of each other was characterized by apathy, not animosity.” New Criticism eschewed historical context for the unified whole of the text. The rise of structuralism and post-structuralism — the linguistic turn in literature departments from the late 1960s through the 1990s — also tended to emphasize form, semiotics, and the play of the signifier rather than political, historical, or social contexts. However, by the 1980s, New Historicism, Cultural Materialism, Ethnic Studies, Post-Colonialism, Queer Studies, and other fields sought to reestablish those contexts. While economics settled into methodological consensus and orthodoxy, literature departments began to pursue new methodologies and neglected areas of study.

Literary critics in this period also joined historians and philosophers in engaging with economics. In their preceding Routledge volume, The New Economic Criticism: Studies at the Intersection of Literature and Economics (1999), Mark Osteen and Martha Woodmansee identified a “first wave of economic criticism, which appeared during the late 1970s and the early 1980s.” The New Economic Criticism, “a second, seemingly tidal wave of scholarship investigating the relations among literature, culture and economics,” emerged in the 1980s and ’90s from the popularity of New Historicism (their own term sought to capitalize on its momentum), the make-it-new imperative of scholarly publication, and the reemergence of cultural studies. According to Seybold and Chihara, New Economic Criticism “was not a wholesale rejection of Marxist Literary Criticism,” but “New Economic Critics did tend to treat Marx as part of a historical continuum of economic thought, not an invalidation of it.” Some of these critics drew on the work of the founder of rhetorical economics — and later Chicago school civil libertarian — Deirdre McCloskey, who emphasized the rhetorical underpinnings of economics to temper the discipline’s truth claims. Some critics also followed her suggestion that literary economic criticism was stunted because its “knowledge of economics begins and ends with Karl Marx.” It is a pithy statement, if not exactly true. Marx himself was nothing if not a close reader of political economy, and for more recent critics, to understand Marx means to understand the body of thought that made up the object of his critique. In his chapter “Keynes and Keynesianism,” Seybold notes that “[o]nly a small fraction of professional economists read Keynes’s General Theory, or any canonical works in the history of economic thought, for that matter.” Put differently, the study of economic history in mainstream economics departments does not end with Marx — or Keynes or Mill or Smith — but rather before it begins.

II.

Speaking of beginnings, it seems clear why a new new economic criticism might emerge now — whether one prefers the financial crisis of 2007 and 2008 or the almost 50 years of economic stagnation that economic historian Robert Brenner has termed “the long downturn.” One certainly need not be an academic to know that the economic weighs heavily on contemporary life. But why does “contemporary econo-literary criticism” respond so widely and so thoroughly in this period? Seybold and Chihara note that

a sizable community of scholars trained in literary and cultural studies have chosen to spend the last decade (or longer) fastidiously reading political economy, economic history, business journalism, Wall St. memoirs, microeconomics textbooks, and many other tediously “unliterary” genres which make up what Leigh Claire La Berge calls “financial print culture.”

Whatever the individual reasons for their engagement, the scholars in Literature and Economics “approach economic texts and contexts with rigorous attention to the disciplinary vocabulary, methodological assumptions, and intellectual history of economics.”

Literature and Economics is expansive. It ranges temporally from premodern economics (Andrew Galloway) to the rise of finance and behavioral economics (Richard Godden and Chihara, respectively). The essays included read literature with and against paper money (Mary McAleer Balkun), energy (Imre Szeman), real estate (Alison Shonkwiler), speculation (Peter Knight), inflation (Joseph Jonghyun Jeon), social want (Howard Horwitz), and black markets (Sharada Balachandran Orihuela). Some contributors use economic concepts as lenses to read literary texts or demonstrate how literary texts illustrate or complicate economic thought. Others read economic discourse using literary tropes and devices or demonstrate how those tropes and devices function in ways analogous to economic phenomena. Each chapter is informative and brief — most are 10 pages or less — and students of literary-economic history will find more avenues to explore in each chapter’s notes and references.

Seybold and Chihara group 38 chapters into four sections. The essays that comprise the first, Critical Traditions, set the stakes for the literary study of economics and the political and economic study of literature (including a stand-out essay by Christopher Chen and Timothy Kreiner on the politics of form and poetics of identity). The Histories section periodizes from medieval ethics to NAFTA novels. Each chapter of Principles (by far the longest section) tackles an economic trope, concept, or school, from Eleanor Courtemanche’s methodical history of “classical economics” to Annie McClanahan’s characteristically incisive reading of “[s]ecular stagnation and the discourse of reproductive limit.” The collection ends with a short section on contemporary culture, which further expands the literary (represented here by Laura Finch on global finance and scale in the novel) to include multimedia mergers (Michael Szalay), the musical Hamilton (Jennifer J. Baker), the podcast (Chihara), and serial television (David Buxton).

Seybold and Chihara’s introduction draws in part on Elizabeth Hewitt, who has argued the disciplines of literature and economics tend “to alternate between devotion and repudiation” in their relation to one another. This dynamic obtains within literary studies itself. Seybold and Chihara note that Marxist literary criticism repudiates orthodox economics, while New Economic Criticism has displayed more scholarly devotion. Given the financial crisis and recession, one might expect contemporary literary economic criticism to opt for the former. However, according to the editors, this is not the case, or at least not quite. Instead, Seybold and Chihara argue (in a move both dialectical and reparative) that “the nature of this era’s repudiation is […] distinct, as it is not so much an alternative to devotion as the synthesis of shared roots.” The editors continue:

Contemporary econo-literary criticism is, paradoxically, energetically engaged with the history of economic thought and methods of economic analysis and openly hostile toward economics’ prevailing disciplinary hegemony and its perceived program of institutional and cultural imperialism.

Seybold and Chihara then set out to show “how and (why) contemporary econo-literary criticism breaks the cycle by absorbing its extremes.” This critical recovery of shared disciplinary roots — provocatively, in language not unlike Samuelson’s description of the Keynesian synthesis — characterizes their account of econo-literary criticism today.

III.

The genesis of The Routledge Companion to Literature and Economics was a 2015 American Comparative Literature Association panel, “Literary Finance: Why Now?,” convened by Seybold and Chihara. Drawing on La Berge, Seybold and Chihara describe how finance came to stand in for the economic writ large in popular discourse (see, for instance, the ubiquitous stock ticker on cable news, the hourly NASDAQ and the Dow updates on public radio, and pundits — and presidents — who erroneously use financial markets as indicators of the health of the economy). No doubt financialization generally and the financial crisis more pointedly provided exigence for cultural analysis of the economic. Due to popular fascination and finance’s increased share of the economy, the study of finance and financialization became a key node of contemporary literary and cultural economic analysis, as evidenced by the rise of interdisciplinary Critical Finance Studies working groups, conferences, and journals.

Yet despite its origins in literary finance, Seybold and Chihara are wary of limiting the economic to finance in the collection, and for good reason. As stock prices soar, a result of low interest rates, corporate tax cuts, and stock buy-backs, wages continue to languish. The economy has recovered, and the labor market is tighter than it has been in nearly 50 years, we are told, even as the jobs created since the financial crisis have been almost exclusively in low-wage, low-productivity service work. A fault line that characterizes contemporary criticism of finance emerges here: namely, the financial sector’s relationship to production or the “real” economy. Alissa G. Karl’s chapter on neoliberalism, for instance, deftly explains the varied histories and referents of this by now-vexed term. However, casual claims that “[f]inance and production became increasingly divorced from one another through a number of means,” or that finance has led to the creation of markets that are “divorced from actual labor or material goods” give pause. Indeed, they are sharply undercut in chapters by, among others, McClanahan, Szalay, and Christian P. Haines, the last of whom cautions against critique that “call[s] financialization into question only by repeating a fiction that finance tells about itself, namely, that finance capital belongs to another ontological level, that it is free of mere existence, untethered from the concrete labour that reproduces capitalism.” Also nodding to La Berge, Haines argues that discourses of complexity and abstraction

conceal the mutual imbrication of fictitious capital (i.e., capital that derives profits in a manner not immediately tied to commodity production) and productive capital (i.e., capital invested in the production of commodities), reinforcing belief in the transcendence of finance over the social domain of labour.

No matter the geographical or temporal remove at which it seems to operate, finance remains tethered to production through claims on future value. Now that finance is firmly established in literary studies, I suspect we will see more criticism that grapples with the continued imbrication of different sectors of the capitalist world system (as evidenced in Alden Sajor Marte-Wood’s chapter on “Consumption,” which offers a strong critique of literary studies that occlude production, distribution, and circulation).

While critiques of contemporary finance are well represented in the collection, the editors’ “use of economics gestures toward economic histories that predate the metonymy of finance.” This capaciousness is an asset and is reflected in collection’s broad temporal and conceptual range. This scope supplements more period specific collections, including contributor Shonkwiler and La Berge’s Reading Capitalist Realism (2014) and Mitchum Huehls and Rachel Greenwald Smith’s Neoliberalism and Contemporary Literary Culture (2017), both of which cluster around a particular intersection of contemporary literature and economics. Although it also trends toward 20th and 21st centuries and the Anglo-US contexts, Literature and Economics brings together scholars from across literary and economic history and its longer durée opens up comparative readings and implied conversations by critics who do not often appear together in print. One wonders if these conversations might be opened up to economists, too. (The New Economic Criticism was also primarily made up of literary critics, but did feature a handful of economists, evidence of a parallel track of contemporaneous heterodox criticism.) However, literary allusions in Thomas Piketty’s surprise best seller Capital in the Twenty-First Century (2013) aside, orthodox economists do not seem interested in these conversations. If midcentury economists were merely disinterested in the humanities, the apathy of contemporary economists verges on antipathy.

IV.

It should not be controversial to note how mainstream economics undervalues social and cultural life, which produces and reinforces a tendency in US society more broadly. As Seybold and Chihara note, “Economists are routinely called upon to rationalize limitations of access to education, healthcare, and legal protection which disproportionately disadvantage minorities and enable harmful upward redistributions of wealth.” The policy prescriptions economists justify, lead, in no small part, to attacks on humanities specifically. The cynical economic imperatives behind the underfunding or outright elimination of humanities departments (most recently a reorganization — read cuts — at the University of Tulsa), the casualization and two-tiered system of academic labor, and the shortsighted attempt to defund Stanford University Press are obvious. However, I may be on less friendly ground in suggesting a tendency in the literary and cultural criticism of economics to overvalue our own contributions, at least in political terms.

Let me be absolutely clear: I am not chastising scholars in the humanities working at the intersection of culture and economics (of which I am one), or the methodologically sharp, interpretively fine-grained, and historically grounded analyses evidenced here. The rigor of collection’s interdisciplinary work is no small accomplishment, and as Seybold and Chihara note, “Interdisciplinary critiques of economics can and should be used to strengthen the society built around them.” Econo-literary criticism is one of the most exciting fields in literary studies, and its value, as this collection demonstrates, ought to transcend the discipline. This is important work, full stop. Yet I am suggesting, and I suspect that some, if not many, contributors to the present volume agree, that when we remind economists of their own historical, philosophical, and rhetorical traditions, or demystify the abstractions of global finance, or insist on the lived realities of our economic system occluded by the scientistic dreams of neoclassical economics, we tend to only do those things: remind economists of their roots or demystify finance or insist economists acknowledge that mathematical maps do not correspond to the actual economic territory.

Here it might be illustrative to move from beginnings to ends, from histories to futures. Seybold and Chihara’s introduction concludes not with Marx (pace McCloskey), but with a typically literary (and typically droll) Keynes: “The reason ‘good economists are scarce,’ Keynes posited, was that while neither the art nor the science of economics ‘require a highly specialized intellectual technique,’ the mind which possesses both ‘appears to be a very rare one.’” Keynes thus suggests another sort of synthesis: good economists — and, one imagines, good econo-literary critics — exist at the intersection of art and science. But the problem of the economic is not a merely a matter of finding equilibrium between rhetoric and models, history and mathematics, or moral philosophy and physics. Seybold and Chihara anticipate this:

We do not imagine that literature can or should represent an entirely autonomous field from power or from the capitalist social relations under which is produced. We do believe in the importance of literary knowledge in the face of the political and social matrix that creates us and that today threatens to destroy us.

This moves us into the realm of politics.

V.

The struggle over economic justice requires political contestation, not solely better ideas or histories. The greatest coup of modern economics was neither the marginal revolution, nor the neoclassical synthesis. Rather it was smuggling in an exploitative ideological project behind a technocratic front. Those who hold politico-economic power have no interest in ceding it, which is in no small part why the conversation this collection encapsulates seems one-sided. Mainstream economics has long demonstrated it cares little about being just, about being fair, about being equitable, about being egalitarian. In the lead up to and fall out from the financial crisis, it has demonstrated that it cares little about being consistent, let alone correct. It cares less about freedom, a concept it consistently evokes, than its relationship to power and its ability to reproduce that relationship. This is why “[t]he richest 1 percent alone absorbed nearly 60 percent of the total increase of US national income” since 1980, according to Piketty. No amount of historical, philosophical, or rhetorical arguments, no demystification, no study or synthesis will change this simple fact. If mainstream economics has reproduced its relation to power by making arguments that appeal to the interests of the powerful, the realm of argumentation seems limited. Making the economy more just is not, unfortunately, a matter of making just arguments to powerful people. It’s about making them do it, which amounts to taking their power away.

Many scholars in the humanities rightfully scoff at the economistic rationality of “the marketplace of ideas,” in which good thinking, well argued, must eventually win out, when it is uncritically proffered by university administrators confronted by encroaching hate speech and incitement on college campuses. The metaphor fails because it relies on bad economic thinking: free markets, equal access, and equilibrium. Like mainstream economic models, the marketplace of ideas refuses to see power — by design. Yet there is a similar market basis for the technocratic arguments offered by progressive critics — literary and otherwise — of the excesses of capitalism over the last 45 years. Calling economics to its shared roots in political economy and its relation to humanistic study is, to my mind, insufficient. Without the power of collective action, better interpretations alone will not change our politico-economic world. And, to paraphrase one of Seybold and Chihara’s literary-minded political economists, the point is, emphatically, to change it.

It is also by design that Christopher Newfield’s contribution “What is literary knowledge of the economy?” directly follows the editors’ thought-provoking introduction. Newfield’s chapter situates “literary knowledge of the economy at the center of an answer to neoliberal economization.” While the claim is optimistic, Newfield suggests how literary knowledge of the economy might turn to praxis. If literature “posit[s] that economy determines subjectivity only across a gap of incommensurability,” then “[t]his apparent paradox has the effect of constituting psychic possibilities and seeing the psyche (and its cultural effects) as incommensurable with these apparently determinate forces.” As examples of this paradox, Newfield references Judith Butler’s work on the political possibilities opened up by power’s inability to reproduce itself perfectly, as well as the “moments of revolutionary possibility that Benjamin called jetztzeit, when the flow of history is interrupted.” Both are examples of an incommensurability between economic, which is to say historical, determination, and a political subjectivity that exceeds the current economic order that conditions it.

Of course, in The 18th Brumaire, Marx also had an account of determination, subjectivity, and political praxis. He argues, in a familiar line, that “[m]en [sic] make their own history, but they do not make it as they please; they do not make it under self-selected circumstances, but under circumstances existing already, given and transmitted from the past.” As scholars, students, and readers of literature and economics, it is our job to understand and explain and contest this shared history — the synthesis that Seybold and Chihara suggest in their definition of the new new economic criticism — and that there is no more capacious introduction to this history than The Routledge Companion to Literature and Economics. But, to modify Marx once more, we also must not allow history to smother our own content. When it comes to the political contestation of economics, we cannot take our poetry from the past but only from the future. No economic arrangement lasts forever, but what follows is not inevitable. Literary knowledge of the economy may allow us to see the possibilities opened up by this incommensurability, but possibilities need to be seized, not solely historicized.

John Macintosh is a lecturer in English at the University of Maryland, College Park. He is currently at work on a book project on labor, precarity, and contemporary fiction.

https://lareviewofbooks.org/article/literary-economy-on-the-routledge-companion-to-literature-and-economics/

[benrleeusa]

"Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment"

The title of this post is the title of this article recently published by the journal Criminal Justice and Behavior and authored by Laurel Eckhouse, Kristian Lum, Cynthia Conti-Cook and Julie Ciccolini.  Here is the article's abstract:

Scholars in several fields, including quantitative methodologists, legal scholars, and theoretically oriented criminologists, have launched robust debates about the fairness of quantitative risk assessment. As the Supreme Court considers addressing constitutional questions on the issue, we propose a framework for understanding the relationships among these debates: layers of bias.

In the top layer, we identify challenges to fairness within the risk-assessment models themselves.  We explain types of statistical fairness and the tradeoffs between them.  The second layer covers biases embedded in data.  Using data from a racially biased criminal justice system can lead to unmeasurable biases in both risk scores and outcome measures. The final layer engages conceptual problems with risk models: Is it fair to make criminal justice decisions about individuals based on groups?  We show that each layer depends on the layers below it: Without assurances about the foundational layers, the fairness of the top layers is irrelevant.

[punsnpuns-blog]

Reading Response Blog 7

In many ways, as I read through Jones, Torres, and Arminio’s (2014) concluding chapter, I felt a sense of kindred spirit. As they point out in their framework of lessons learned: reflexivity is a key component of qualitative methodologies (and, for my money, research designs in general). What struck me for the first time as I read through their chapter, though, was the idea of research community resistance. In many ways, quantitative/positivistic studies have a storied history that have contributed to the nominalistic efforts of science from the Enlightenment to present; as a result, a hierarchy of methodology has emerged in which it may be easier in many instances to convince others of the significance of a study or findings when quantitative methodology frames your study. In thinking about the practical effects here, I start to think about how such a preferential treatment has a corollary, reversed effect on something like, say, the IRB process. Will it be more difficult to convince non-experts of the benefit of certain kinds of methods? 

More importantly, even, is the question of choosing a chair and methodologist to support a dissertation; the alignment of their views of research and approaches and mine, that has to be a primary consideration. Subsequent to that consideration is likely the fine-tuned attention to how I might communicate with my committee about any conceptual, methodological, epistemological difference. My chief take-away, then, from their chapter here is that I would do well to keep this idea of alignment at the forefront of my choices and ensure that I’m able to make choices that are satisfactory to my own predilections and world view without violating entrenched norms. Navigating those two ideas is an unimaginable task insofar as how little I know about what that geography will look like until I’m moving through it. 

[thegodwithinblog]

The Unbreakable!

"The Unbreakable!" ...because if you do this you will never have a peaceful mind but an agitated one which always tries to please everyone you meet...

“Truth and Honesty is the oldest and most powerful of all of the human values.”  ~ Gary King; American political scientist and quantitative methodologist.

“Truth allows you to live with integrity.  Everything you do and say shows the world who you really are.  Let it be the Truth.”  ~ Oprah Winfrey.

People tend to follow their egos and always seek the approval and attention from others, they…

[t-baba]

Transcript: Ask the UXperts: Taking Your Research to the Next Level — Panel Discussion

Yesterday our Slack channel lit up with the combined knowledge of three members of our very own community.

Dr Jade Jones, Dr Marion Boberg and Stephanie Pratt were brave enough to work with me to trial a new idea that I had for our Ask the UXperts sessions.

The panel format proved to be a huge success. It allowed us to cover a broad range of topics and meant that we were able to get through more questions in the hour than is possible with a single guest.

The broad topic was UX research and we covered everything from selecting the most effective techniques to the emerging role of AI in user research. It’s fair to say that we all learned something!

If you didn’t make the session today because you didn’t know about it, make sure you join our community to get updates of upcoming sessions.

If you’re interested in seeing what we discussed, or you want to revisit your own questions, here is a full transcript of the chat.

Transcript

hawk

2017-07-05 18:02

Thanks everyone for joining us today. An especially big thanks to our panelists, @docboom @marionb and @stephaniempratt

hawk

2017-07-05 18:02

All of whom I cold emailed and lured into this session :wink:

flaxenink

2017-07-05 18:02

:+1:

hawk

2017-07-05 18:02

A quick intro of each:

Jade Jenkins is an experimental psychologist. After spending a decade researching various phenomena within social cognition (perception and memory) and occupational health psychology (including the interplay of technology, stress, and health), she earned her PhD in social and industrial-organizational psychology from Northern Illinois University.

Jade currently works in assessment within the Texas A&M University system, where her role consists of equal parts change agent, data and statistics octopus, and development consultant. She has expertise in numerous UX research methodologies, ranging from focus groups and experience sampling to biometric measurement (e.g., heart rate variability; HRV) and surveys.

She is a member of the Dallas-Fort Worth branch of UXPA, and welcomes kindred expressions of UX research methodology geekery on Twitter @jadejenkinsUX.

hawk

2017-07-05 18:03

Marion Boberg is a UX researcher born in Normandy France. She moved to Finland in 2003. Marion holds a PhD in Psychology from both French University of Caen and Finnish University of Eastern Finland.

Marion has 10+ years of experience in UX research, from Nokia Research Centre, Tampere University of Applied Sciences and Qvantel. Her UX experience is related mainly to IT products, mobile apps and telephony, her passion is about People and Innovation.

Author and Co-author of several HCI scientific publications and 10 + pending patents (5 granted) related to mobile UI and services for Nokia Technology.

hawk

2017-07-05 18:03

Stephanie M. Pratt is the Lead User Experience Researcher at a startup called LiveSafe. At LiveSafe, she primarily focuses on problem space research and understanding the users.

Prior to LiveSafe, she has worked in a variety of industries including another startup called mHelpDesk, GEICO, and a government contractor, Aptima. In those roles, she has done many levels of fidelities of usability testing and interviews. She has her Master’s degree in Human Factors / Applied Cognition from George Mason University.

Additionally, Stephanie is actively involved in the Washington, DC UX community.

hawk

2017-07-05 18:03

@docboom Can you give us some insight into the areas of research that you are particularly interested or passionate about at the moment?

docboom

2017-07-05 18:04

Absolutely, and thanks for having me here, @hawk!

docboom

2017-07-05 18:06

In a nutshell, you could say that I am a UX methodologist. I have many years of experience in quantitative, qualitative, and mixed-methods approaches to doing research. I am passionate about the UX research process itself, and am particularly passionate about new and emerging methodologies in UX research, especially heart rate variability; HRV.

docboom

2017-07-05 18:07

So in general, I’m here for anyone who has questions about UX research as a process. :slightly_smiling_face: I’m looking forward to the discussion!

hawk

2017-07-05 18:07

Perfect! @marionb – what are you areas of expertise?

marionb

2017-07-05 18:08

Hi, and thanks for inviting me :slightly_smiling_face:

marionb

2017-07-05 18:08

My expertise would be on designing for Playful Experiences (PLEX)

marionb

2017-07-05 18:09

or researching in that field, among many other subject –

hawk

2017-07-05 18:10

Fantastic. Sounds cool! And @stephaniempratt – what about you?

stephaniempratt

2017-07-05 18:10

Hi everyone! Excited to be here!

stephaniempratt

2017-07-05 18:11

My expertise falls under the qualitative side, with my psych background. From qualitative usability testing to interviews.

stephaniempratt

2017-07-05 18:11

I have conducted some “listening sessions” recently, which were really enjoyable, and led to building behavioral audience segments instead of personas, so happy to discuss that. As well as life as a researcher at a startup

stephaniempratt

2017-07-05 18:11

Looking forward to the discussion!

hawk

2017-07-05 18:12

Such a great range of skills. Thanks again for your time.

hawk

2017-07-05 18:12

ok – who has a question to kick things off?

isha

2017-07-05 18:13

I’m curious to hear more from @stephaniempratt about behavioral audience groups vs personas. Seems like a lot of orgss are turnign away from personas. Can you speak to this a little bit.

steveportigal

2017-07-05 18:13

@marionb What is going on in organizations these days that is either helping or hindering the impact of user research?

hawk

2017-07-05 18:14

(if others have questions, ask away. I’ll queue them while Stephanie answers)

melanie

2017-07-05 18:14

What is your favorite framework for measuring user sentiment for a product feature?

stephaniempratt

2017-07-05 18:14

@isha – Sure thing! I mislabeled initially, behavioral audience segments is what I meant to call them. Pulled from Indy Young. :slightly_smiling_face:

bgas

2017-07-05 18:14

How would you suggest a small company with a limited budget can apply user research into the UX process when currently it is extremely limited?

melanie

2017-07-05 18:14

Do you see a role emerging for AI in user research?

stephaniempratt

2017-07-05 18:14

When dealing with various contexts that change, people will behave differently

stephaniempratt

2017-07-05 18:15

For example, I do work in the safety space, so in one instance a person may feel threatened, and in another context, may feel empathetic toward someone else in trouble

shillman

2017-07-05 18:15

How do you deal with businesses that want you to use techniques that you’re less convinced of the effectiveness? I’m thinking things like A/B testing (in most smaller companies) and focus groups.

flaxenink

2017-07-05 18:15

more talk about emerging methodologies in UX research, especially heart rate variability; HRV. @docboom Where do you see that going and how does that go with UX?

stephaniempratt

2017-07-05 18:16

So people don’t fall into a category all the time, they move, and it is outside gender/age/demographics, so by focusing on behaviors I think it helps build empathy and remove biases because anyone could experience that situation and behave that way.

stephaniempratt

2017-07-05 18:16

Sorry, editing my typos as I go :wink:

stephaniempratt

2017-07-05 18:16

Let me know if you would like more resources/explanation!

marionb

2017-07-05 18:17

@steveportigal From my personal point of view – the fact that business pace does not match research pace – often you need to downgrade the level of research or focus only on very specific issues at the time.

stephaniempratt

2017-07-05 18:18

@bgas asked “How would you suggest a small company with a limited budget can apply user research into the UX process when currently it is extremely limited?”

stephaniempratt

2017-07-05 18:19

In my experience it has been starting with little wins

stephaniempratt

2017-07-05 18:19

Maybe first taking some initial prototypes to a coffee shop and buying a few people a coffee for helping you out with feedback.

docboom

2017-07-05 18:21

@bgas I think it would be helpful to determine what your higher-level priorities are (both in importance and in terms of reach/impact on your org’s other goals) and then determine what conservative efforts could help you get the biggest bang for your buck.

stephaniempratt

2017-07-05 18:21

Or maybe an entry into a gift card raffle for filling out a survey

stephaniempratt

2017-07-05 18:21

Or even reaching out to current customers who are invested in the product

stephaniempratt

2017-07-05 18:21

a lot of time a thank you will suffice for them

stephaniempratt

2017-07-05 18:21

And just being listened to

leigh715

2017-07-05 18:21

What are some new methodologies you’re starting to see more of?

docboom

2017-07-05 18:22

yes! like @stephaniempratt suggested, you may be surprised by just how many survey respondents you can get with little money. especially if MTurk crowds interest you.

docboom

2017-07-05 18:23

@flaxenink Users are often unaware of the mental effort they are expending to complete a task because they are too focused on trying to perform well.

docboom

2017-07-05 18:23

HRV is a way to measure this process as users exert mental effort in real time (instead of having us researchers merely assume what’s happened after users have finished).

flaxenink

2017-07-05 18:23

@docboom: How can you track it? the HRV?

marionb

2017-07-05 18:24

@bgas try to involve small amount of user at the time from arly stage – the great opportunity of a small company is that you can also more esaly reach all the stakeholders and focus on what you all think is key to be tested.

docboom

2017-07-05 18:25

@flaxenink There are many physio ways to do it; I’ve often used a pulse wave sensor (usually an ear clip users can wear while completing a study). HRV is measured in milliseconds.

docboom

2017-07-05 18:25

High HRV = high effort, low HRV = low effort.

docboom

2017-07-05 18:25

HRV is of interest to human-computer interaction folks due to the assumption that well-designed products should be relatively easy to use (and, thus, users should demonstrate low HRV while using a product, all things considered).

docboom

2017-07-05 18:26

When coupled with other tools (e.g., video monitoring footage), HRV can help objectively identify weak points of the HCI.

stephaniempratt

2017-07-05 18:27

@shillman regarding your question ” How do you deal with businesses that want you to use techniques that you’re less convinced of the effectiveness? I’m thinking things like A/B testing (in most smaller companies) and focus groups.” I try to focus on what the stakeholders want to know

flaxenink

2017-07-05 18:27

@docboom: is the equipment expensive? While you are doing the testing?

stephaniempratt

2017-07-05 18:27

So for example, I will start building a research plan by having a meeting with them to get all their questions out there on a specific topic

stephaniempratt

2017-07-05 18:27

Then based on what they want to know, I will recommend/tell them the methodology I will pursue and explain to them why

stephaniempratt

2017-07-05 18:28

If they pushback on the methodology and prefer a different one, I will try to give them pros and cons of them and how they will or will not answer the questions

docboom

2017-07-05 18:28

@flaxenink Depending on the package, I think the equipment can either be on par with or much cheaper than eye tracking equipment and software.

stephaniempratt

2017-07-05 18:29

A good example might be if they ask “why are people abandoning the page?” and suggest a focus group, I will tell them why a usability test is more appropriate and provide more info on what a focus group could provide (e.g., concept feedback or marketing opinions)

shillman

2017-07-05 18:29

@stephaniempratt Aaah, this makes sense, yes.

stephaniempratt

2017-07-05 18:29

Sometimes it’s a game of politics though, and balancing that with what you want to research :wink:

shillman

2017-07-05 18:30

*nodnod*

flaxenink

2017-07-05 18:30

@docboom: Ah I see, will the HRV can be use in big companies or smaller ones do you think it will benefit from?

docboom

2017-07-05 18:32

@flaxenink Certainly the larger companies will likely have other equipment (e.g., video recording software or eye tracking) that are great compliments to HRV, thus enhancing its value.

docboom

2017-07-05 18:33

However, small companies struggling to pinpoint the exact moments where users are encountering design errors and other issues could benefit.

stephaniempratt

2017-07-05 18:34

@melanie: “Do you see a role emerging for AI in user research?” – What I have seen is a lot more research on AI experiences. At conferences I have attended there has been a lot of presentations on how to research using Amazon Echos/Google Homes, or chatbot prototypes. I have not seen AI as a support for user research as of yet, but maybe someone else has. :wink:

marionb

2017-07-05 18:34

@leigh715 about new methodologies, i see that there is more and more bridge, or collaborations between UX and CX, and I would say using user research to flesh out customer journey maps

flaxenink

2017-07-05 18:34

@docboom: if it was a smaller company how could they leverage the HRV? Do you have advise on that and what can they over come to get over the pinpoints of the exact moments?

shillman

2017-07-05 18:34

@melanie When you say AI, do you mean machine learning? Robotics? Something else?

melanie

2017-07-05 18:35

Yes, machine learning. For example, using data to improve your behavioral segments, something like that.

docboom

2017-07-05 18:35

@leigh715 Certainly eye tracking has exploded in recent years, though many still have misconceptions about what data is valuable, what it means, etc.

shillman

2017-07-05 18:36

@melanie I would not tend to expect the use of machine learning to do UX research, since it really just means using algorithms to deal with huge amounts of data. Usually to categorize it somehow or another.

hawk

2017-07-05 18:36

If you’ve just joined us and you have a research related question for our panel – jump in and ask at any time. I’ll queue them if nec.

stephaniempratt

2017-07-05 18:37

@melanie – you also asked, “What is your favorite framework for measuring user sentiment for a product feature?” – What are you trying to solve here? Are you trying to learn satisfaction of a new feature? Or something about a current feature? Please offer a little more context so we can better answer this question :slightly_smiling_face:

docboom

2017-07-05 18:37

@flaxenink I think I would start with a discussion of what the company’s biggest usability issues are, what’s been done in the past to address it, and how HRV fills that gap.

docboom

2017-07-05 18:38

So I’d think about what persistent, nagging issues you’ve had and, where possible, align that with a cost-benefit analysis

melanie

2017-07-05 18:38

Sure! Proposed features (not currently existing features). A way to measure the expected satisfaction or delight of the user. ie, will the user like it? and using that to decide whether to build the feature

docboom

2017-07-05 18:39

At minimum, HRV + video recordings is a good starting point and doesn’t have to be terribly expensive.

marionb

2017-07-05 18:39

@melanie I recently read this article on UX analytic – I see AI a way to guide us where to focus – but you still need to investigate the Why

marionb

2017-07-05 18:39

http://ift.tt/2tScPmB

melanie

2017-07-05 18:39

@marionb thanks!!

stephaniempratt

2017-07-05 18:39

@leigh715 I’d also add on to take a look at Indi Young’s Practical Empathy, and learning about listening sessions. I have found them to be extremely enlightening to have a deep conversation with someone about how they think, feel, and react in context with your research question.

hawk

2017-07-05 18:42

we have ~15 mins left in the session and we’re at the end of our queue of questions. Now is your chance to jump in with more!

stephaniempratt

2017-07-05 18:43

@melanie Ah, so you’re interested in understanding if they user will be interested in a proposed idea, so conceptual work. Well first, I’d make sure that the idea is based on solving a problem that has been identified from research. That will help back your reasoning for going forward with the feature.

stephaniempratt

2017-07-05 18:43

I actually read a great article on how to do design studios with constraints from user research this morning http://ift.tt/1Oq3OSX

isha

2017-07-05 18:43

@stephaniempratt wanted to follow up on my first question. Can you speak a little more about how you document audience behavior segments (I might be butchering the term, sorry)?

melanie

2017-07-05 18:43

@stephaniempratt thanks!

flaxenink

2017-07-05 18:44

@docboom @marionb @stephaniempratt: What source or tip you can not live with out in the UX industry?

stephaniempratt

2017-07-05 18:45

Then from there, getting the concept in front of some people – building rapport with them so that they are comfortable being disapproving (examples: telling them you are not involved at all with the design, asking some warm up questions, etc.)

stephaniempratt

2017-07-05 18:46

Then getting the concept in front of them and maybe asking them what they think it does, what they think it is for, how useful or not useful they think it is (via likert scale), or anything else that relates to the questions/context at hand.

bgas

2017-07-05 18:46

When the product you are working on is designed for a very niche group of users, would UX research from people outside of the intended group (who do not understand the processes) still be beneficial?

stephaniempratt

2017-07-05 18:46

Kind of like a “sniff test” to see if it’s worth putting more effort to consider usability testing

stephaniempratt

2017-07-05 18:47

@isha Yes! Here is a wonderful resource from Indi Young : http://ift.tt/1Xs1i2t

docboom

2017-07-05 18:48

@flaxenink Jeff Sauro and his team of UX researchers (MeasuringU) frequently produce excellent content on research as a process, so I often find myself tuning in to their latest posts.

marionb

2017-07-05 18:48

I’m a Fan of http://ift.tt/1oK12Mq and UX Mastery of course :wink:

marionb

2017-07-05 18:48

and I have some methodology books I fav

stephaniempratt

2017-07-05 18:49

I use both of those resources and these: http://ift.tt/ZmsnGH , http://ift.tt/1YC0LjI

isha

2017-07-05 18:50

when it comes to information design (dashboard, graphs etc.), do you have have any suggestions on resources (besides the ones posted above for other UX oriented information)?

docboom

2017-07-05 18:50

Ah yes, Nielson Norman was on the tip of my tongue! :slightly_smiling_face:

docboom

2017-07-05 18:50

*Nielsen

marionb

2017-07-05 18:50

Yes the new edition

marionb

2017-07-05 18:51

of Norman classic is also great!

docboom

2017-07-05 18:52

Oh! And for anyone who gets queasy around statistics, I have found that Andy Field’s books (or his website, Statistics Hell) are often received well by newcomers.

stephaniempratt

2017-07-05 18:53

@bgas “When the product you are working on is designed for a very niche group of users, would UX research from people outside of the intended group (who do not understand the processes) still be beneficial?” Getting it in front of other people may help identify big usability problems from human perception (e.g., contrast of colors, ability to navigate/find a button, etc.) but when it comes to getting through a process that is skilled, it is highly recommended to get niche users if you can.

viratahuja

2017-07-05 18:53

#ask-the-uxperts any advice any books

marionb

2017-07-05 18:53

@isha it’s a tool and online ressource: http://ift.tt/Hbatki they tackle if i remember right some dashboards and other visual graphical data

stephaniempratt

2017-07-05 18:54

I used to work at a company that created software for field service professionals, so those were the people I would recruit would be service pros, but it was always hard to get the really low tech people to participate

stephaniempratt

2017-07-05 18:54

In the end, you have to make do with what you can get, so if getting it in front of a few people who aren’t that niche to get a gut check on higher level usability is all you can do, I’d say that’s better than no testing. :slightly_smiling_face:

flaxenink

2017-07-05 18:54

@docboom: Anymore tips about being queasy around statistics!

bgas

2017-07-05 18:55

@stephaniempratt Great response. Thank you.

stephaniempratt

2017-07-05 18:55

@flaxenink – the cartoon guide to statistics was good for me in grad school :slightly_smiling_face:

docboom

2017-07-05 18:55

@viratahuja If you’re only going to get one book on research as a process, I recommend Baxter, Courage, & Caine’s “Understanding Your Users”.

stephaniempratt

2017-07-05 18:56

You’re welcome!

viratahuja

2017-07-05 18:56

@docboom thanks

hawk

2017-07-05 18:57

We have just a few minutes left. Does anyone have anything pressing that hasn’t been answered?

hawk

2017-07-05 18:57

If you have follow up questions, all three panelists are active members of our community forums at http://ift.tt/1qs7rt7

marionb

2017-07-05 18:57

I would say for the single book : http://ift.tt/2uQgRJE

docboom

2017-07-05 18:58

@flaxenink Fail early and often. :slightly_smiling_face: Keep all old datasets for practice, and search for a stats expert/geek who doesn’t speak to you like a robot. :wink:

marionb

2017-07-05 18:59

I agree – I’d like to have a professional statitiscian just to guide me – but never found that (only at Uni)

marionb

2017-07-05 19:00

As a final word despite the budget or the schedule – keep going and do what you think is best – practice everyday and that’s how you’ll gain the expertise – and also interview as many people as you feel is necessary –

hawk

2017-07-05 19:00

And that’s a wrap! Thanks SO much to @docboom @marionb and @stephaniempratt for their time and advice today

hawk

2017-07-05 19:00

It was a fantastic session.

hawk

2017-07-05 19:00

I hope you all learned lots!

flaxenink

2017-07-05 19:01

Yes yes (clapping hands standing on a rainbow)!

The post Transcript: Ask the UXperts: Taking Your Research to the Next Level — Panel Discussion appeared first on UX Mastery.

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