The New School
  • New York City, New York, United States
Recent publications
The watershed in modern Chinese politics known as the May Fourth Movement (1919) offers insights into how a single protest event can quickly diffuse to other regions, draw in new participants and produce legacies in contentious politics. This article examines the May Fourth protests from the perspective of “eventful sociology” – an approach that examines how protests, repression and other contingent events link together to bring about landmark political episodes. It traces the sequence of protest and repression events in Beijing and draws on an original database of protest and repression events in Shanghai to emphasize the haphazard sequencing of actions and information flows that led the Chinese government to reverse its stance and concede to protestors’ demands. An eventful account illustrates how past protest sequences can produce a long-term impact on subsequent protest events. It also calls for greater awareness of “single sparks” that initiate protest sequences and unexpected political outcomes.
Eigenvalues of input-output matrices have significant implications for the structures of equilibrium prices and quantities. According to the Bródy Conjecture (BC), all subdominant eigenvalues of matrix would approach zero as matrix size approached infinity. Thus, any given initial quantity or price vector would converge to the corresponding equilibrium one in a single step. This paper adds significant empirical evidence to this theoretical discussion. We create a database of 307 different sizes matrices ranging over 30 years. Contrary to BC, we find that: the coefficient of variation and the subdominant eigenvalue moduli rise with matrix size; there’s a universal rank-size curve of eigenvalue moduli, but it is smooth and convex rather than L-shaped; the distribution of eigenvalue moduli is best fit by a Weibull probability distribution; the Weibull quantile function in turn yields a power law for eigenvalue moduli which is a better fit than a previously proposed exponential function.
Patterns of memory sharing begin early in one’s life, informing relationships, one’s history, and one’s sense of cultural belonging. Memory sharing among families has been the focus of research investigating the relationship between mental health and intergenerational memory. A burgeoning body of research is showing that intergenerational knowledge of one’s family history is associated with positive mental health and wellbeing. However, research on the specific mechanisms and potential applications of such findings are just beginning to emerge. In particular, studies examining intergenerational storytelling point to the importance of culture and gender as critical factors underlying how stories are told and the extent to which these stories are associated with wellbeing. Such findings hold important promise for the pentation and treatment of mental health issues. As research in this area continues to evolve, the identification and characterization of factors and mechanisms underlying intergenerational family stories and wellbeing may help to guide the integration of family stories into mental health interventions.
The use of exploratory network analysis has increased in psychopathology research over the past decade. A benefit of exploratory network analysis is the wealth of information it can provide; however, a single analysis may generate more inferences than what can be discussed in one manuscript (e.g., centrality indices of each node). This necessitates that authors choose which results to discuss in further detail and which to omit. Without a guide for this process, the likelihood of a biased interpretation is high. We propose that the integration of theory throughout the research process makes the interpretation of exploratory networks more manageable for the researcher and more likely to result in an interpretation that advances science. The goals of this paper are to differentiate between exploratory and confirmatory network analyses, discuss the utility of exploratory work, and provide a practical framework that uses theory as a guide to interpret exploratory network analyses.
Throughout the COVID-19 pandemic, studies have demonstrated increases in boredom and its negative impact on mental health. This cross-sectional study examines state and trait boredom at four different points of the pandemic using an online sample of participants from the United States (n = 783). The results showed significant increases in boredom proneness, state boredom, substance use, loneliness, and distress. Boredom was associated with increases in each of these variables and a greater likelihood of testing positive for COVID-19. Moreover, the increases in distress, loneliness, and substance use became non-significant when controlling for boredom. Boredom proneness remained associated with all adverse outcomes when accounting for state boredom. In contrast, the relationships between state boredom and most adverse outcomes lost significance when controlling for boredom proneness, and state boredom was positively associated with increased hope for the future. Overall, the results suggest that high boredom proneness is an important vulnerability factor for poor psychological health and risky behaviors during the pandemic. However, high levels of recent state boredom, independent of boredom proneness, do not predict similarly negative outcomes. State boredom may indicate the extent to which one remains hopeful that circumstances will improve without resorting to risky, potentially maladaptive coping strategies.
The response of governments to the COVID-19 outbreak was foremost oriented to two objectives: saving lives and limiting economic losses. However, the effectiveness and success factors of interventions were unknown ex-ante. This study aims to shed light on the drivers of countries’ performances during the first year of the COVID-19 pandemic. We measure performances by excess mortality and GDP growth adjusted for additional fiscal stimulus. We conduct an empirical analysis in two stages: first, using hierarchical clustering, we partition countries based on their similarity in health and economic outcomes. Second, we identify the key drivers of outcomes in each country cluster by regression analysis, which include linear, least absolute shrinkage and selection operator (LASSO), and logit models. We argue that differences in countries’ performances can be traced back both to policy responses to COVID-19 and structural conditions, the latter being immutable over the pandemic. Three relevant structural conditions emerge from the results: trade reliance on services, corruption, and the size of the vulnerable population (elderly, low-income, smoking, or cardiovascular-failing). Policies such as large-scale open public testing and additional fiscal stimulus in non-health could help reduce excess mortality, which might lead to lower economic losses.
Although pregnancy and the first year of life are sensitive windows for child development, we know very little about the lived experiences of mothers living in poverty or near poverty during the perinatal period; specifically, how they perceive and use public resources to support themselves and their newborn. In this qualitative study, we explore how predominantly Black and Latinx mothers with infants living in or near poverty and engaged in public assistance manage to meet their family’s needs with available resources from safety net programs and social supports. We conducted 20 qualitative interviews with mothers living in (85%) or near poverty in New York City (NYC). All participants (mean age = 24) had an 11-month-old infant at the time of the interview. Using thematic analysis, we identified five main themes reflecting how mothers experience and navigate living with very low incomes while engaging in public assistance programs: (1) experiencing cascading effects of hardships during pregnancy, (2) relying on food assistance and informal supports amid scarcity, (3) waiting for limited affordable housing: ‘life on hold’, (4) finding pathways towards stability after the baby’s birth, (5) making it work: efforts to look forward. Results describe how the current focus on “work first” of existing federal and state policies adds a layer of stress and burden on the lives of single mothers experiencing low incomes and entangled hardships during pregnancy and after birth. We document how mothers experience coverage gaps and implementation challenges navigating the patchwork of public assistance programs, yet how the support of flexible caseworkers accessing, using, and coordinating assistance has the potential to help mothers plan for longer-term goals.
Background While message-based therapy has been shown to be effective in treating a range of mood disorders, it is critical to ensure that providers are meeting a consistently high standard of care over this medium. One recently developed measure of messaging quality–The Facilitative Interpersonal Skills Task for Text (FIS-T)–provides estimates of therapists’ demonstrated ability to convey psychotherapy's common factors (e.g., hopefulness, warmth, persuasiveness) over text. However, the FIS-T's scoring procedure relies on trained human coders to manually code responses, thereby rendering the FIS-T an unscalable quality control tool for large messaging therapy platforms. Objective In the present study, researchers developed two algorithms to automatically score therapist performance on the FIS-T task. Methods The FIS-T was administered to 978 messaging therapists, whose responses were then manually scored by a trained team of raters. Two machine learning algorithms were then trained on task-taker messages and coder scores: a support vector regressor (SVR) and a transformer-based neural network (DistilBERT). Results The DistilBERT model had superior performance on the prediction task while providing a distribution of ratings that was more closely aligned with those of human raters, versus SVR. Specifically, the DistilBERT model was able to explain 58.8% of the variance ( R 2 = 0.588) in human-derived ratings and realized a prediction mean absolute error of 0.134 on a 1–5 scale. Conclusions Algorithms can be effectively used to ensure that digital providers meet a consistently high standard of interactions in the course of messaging therapy. Natural language processing can be applied to develop new quality assurance systems in message-based digital psychotherapy.
In recent decades, many tech spaces have emerged worldwide to promote innovation. Based on ethnographic research, this article examines one of such initiatives in Brazil—a public laboratory of digital fabrication located in a low‐income neighborhood in the periphery of São Paulo. While scholars have exposed the neoliberal aspects of fablabs, this article aims to de‐center hegemonic understandings of innovation by attending to its situated practices. Analyzing the techno‐optimist aspirations and institutional legacies behind this laboratory, I explain how the US‐based fablab model was reconfigured in light of community concerns and previous Latin American experiments of digital inclusion. Against a monolithic image of tech collectives, I show how lab workers cultivated a diverse range of audiences and creative practices, specifically those of working‐class women. The article concludes with a call for more anthropological attention to overlooked tech practices as a means to imagine fairer and more solidary forms of innovation. En décadas recientes, muchos centros de tecnología han emergido globalmente con el propósito de promover innovaciones. Basado en investigación etnográfica, este artículo examina una de esas iniciativas en Brasil: un laboratorio público de fabricación digital localizado en una comunidad de la zona sur de San Pablo. Dado que los aspectos neoliberales de los fablabs ya fueron expuestos por investigadores, este artículo pretende descentrar entendimientos hegemónicos de la innovación a través del estudio de sus prácticas situadas. Analizando las aspiraciones tecno‐optimistas y los legados institucionales detrás de este laboratorio, se explica cómo un modelo estadounidense de fablab fue reconfigurado a la luz de las preocupaciones de la comunidad y experimentos latinoamericanos anteriores de inclusión digital. Complejizando imágenes monolíticas de colectivos tecnológicos, se muestra cómo los trabajadores de laboratorio cultivaron una gama diversificada de públicos y prácticas creativas, específicamente de mujeres de la clase trabajadora. El artículo concluye con un llamamiento a una mayor atención antropológica a prácticas tecnológicas desatendidas como medio de imaginar formas más justas y solidarias de innovación. [informática, desarrollo, inclusión digital, innovación, tecnología] Em décadas recentes, muitos centros de tecnologia têm emergido globalmente com o propósito de promover inovação. Baseado em pesquisa etnográfica, este artigo examina uma dessas iniciativas no Brasil: um laboratório público de fabricação digital localizado numa comunidade da zona sul de São Paulo. Dado que os aspectos neoliberais dos fablabs já foram expostos, este artigo pretende descentrar entendimentos hegemônicos de inovação através do estudo das suas práticas situadas. Analisando as aspirações tecno‐otimistas e os legados institucionais por detrás deste laboratório, explica‐se como o modelo Estadunidense de fablab foi reconfigurado à luz de preocupações da comunidade e experimentos Latino‐americanos de inclusão digital anteriores. Complexificando imagens monolíticas de coletivos tecnológicos, mostra‐se como os trabalhadores do laboratório cultivaram uma gama diversificada de públicos e práticas criativas, especificamente de mulheres de classe trabalhadora. O artigo conclui com um apelo por maior atenção antropológica a práticas tecnológicas negligenciadas como meio de imaginar formas mais justas e solidárias de inovação. [computação, desenvolvimento, inclusão digital, inovação, tecnologia]
From the onset, it was clear that the impact of the global economic and social crisis caused by the COVID-19 pandemic was unlikely to affect all children equally. Thus, it was necessary to ascertain the impact of COVID-19 on child poverty as the events unfolded. Many of the indirect effects of the pandemic – disruptions to health services, delayed vaccination programmes, widespread school closures, and increases in food insecurity – have significant impacts on the realisation of children’s rights and, consequently, were expected to increase material deprivations across different dimensions. The question was by how much? In this article we explain the modelling and methodological approach to project or nowcast the answer to that question. The method is dynamic as it was revised as additional information emerged during 2020 and 2021.
The adoption of a vegan diet might have public, health, and environmental benefits; however, still little is known about veganism as the majority of studies on dietary lifestyles have focused on vegetarianism. Hence, in order to address this gap, the present study adopted a sequential and mixed (qualitative; quantitative) research approach based on laddering interviews (n = 20) and a survey (n = 400) to validate the motives for adopting a vegan diet. The results identified seven motives: economic, ethical, health-related, hedonic, animal empathy, respect for animal rights, and personal accountability. Three motives in particular – (i.e., animal empathy, accountability, and animal rights) appear to be the key determinants of consumer’s self-identification as vegan-oriented individuals. The study found five attributes (price, nutritious, freshness; tasty, eco/animal friendly ingredients) of vegan products associated with the afore-mentioned motives. Food marketers and policy makers could highlight such attributes to encourage the adoption of a vegan diet.
The COVID‐19 pandemic has exacerbated preexisting mental health disparities. In India, marginalization based on caste membership, gender, and rural residence are critical determinants of inequity across the lifespan. Guided by the theoretical frameworks of minority stress and intersectionality, this study examined caste‐based disparities in fear of coronavirus (FOC), mental health symptoms, and perceived loneliness amongst rural women in north India during the COVID‐19 pandemic. Participants (N = 316) completed self‐report measures and were classified into three groups based on their responses: General caste (GC, n = 124), other backward castes (OBC, n = 122), and scheduled caste or tribe (SC/ST, n = 71). Using a three‐way ANOVA and Tukey t‐tests, women in SC/ST and OBC groups reported greater FOC (OBC d = .37; SC/ST d = .40) and greater mental health symptoms (OBC d = .58; SC/ST d = .43) relative to the GC group. OBC, but not SC/ST, group also reported higher perceived loneliness (d = .32). The results were consistent after adjusting for demographic variables such as wealth and highlight caste as an important social determinant for well‐being during the COVID‐19 pandemic amongst rural Indian women.
Background The aim of this study was to evaluate an interaction-based prenatal parenting intervention program aimed at promoting parental sensitivity and involvement in expectant fathers using ultrasound images: Prenatal Video-Feedback Intervention to Promote Positive Parenting (VIPP-PRE). Methods In this randomized controlled trial, 73 first-time, healthy expectant fathers were enrolled. Participants were randomly assigned to the VIPP-PRE intervention ( n = 39) or a dummy intervention ( n = 34). Parental sensitivity was coded from video-recorded 10-min interactions with an infant simulator at a prenatal pretest and with fathers’ own infant at a postnatal posttest. Prenatal and postnatal involvement was assessed via an application on participants’ smartphones. Results Fathers receiving VIPP-PRE demonstrated increased sensitivity across the perinatal period, relative to fathers receiving a dummy intervention. Fathers’ involvement with the infant increased significantly from the prenatal to postnatal period, regardless of the intervention. Conclusions Prenatal video-feedback using ultrasound imaging of the unborn child has the potential to promote the quality of parenting in an important, but understudied, population and period: men in the transition to fatherhood. Future research should examine the long-term effectiveness of VIPP-PRE and its effectiveness in increasing parenting quality in at-risk families. Impact This study identifies a brief and focused prenatal intervention using assisted interactions between the father and his baby by means of ultrasound imaging as a promising strategy to improve sensitive fathering in the early postnatal phase. Our study shows that pregnancy provides a window of opportunity for promoting prenatal involvement and bonding in expectant fathers, with potential long-term benefits for the future father–child relationship. Ultrasound measures are currently used to monitor fetal growth and development, but our results suggest that they may also create an opportunity for stimulating father–infant interaction to promote postnatal caregiving quality.
The principle of maximum entropy, developed more than six decades ago, provides a systematic approach to modeling inference, and data analysis grounded in the principles of information theory, Bayesian probability and constrained optimization. Since its formulation, criticisms about the consistency of that method and the role of constraints have been raised. Among these, the chief criticism is that maximum entropy does not satisfy the principle of causation, or similarly, that maximum entropy updating is inconsistent due to an inadequate representation of causal information. We show that these criticisms rest on misunderstanding and misapplication of the way constraints have to be specified within the maximum entropy method. Correction of these problems eliminates the seeming paradoxes and inconsistencies critics claim to have detected. We demonstrate that properly formulated maximum entropy models satisfy the principle of causation.
Wind energy is one of the most used clean energy sources in renewable energy, and its renewable and sustainable nature is one of the reasons why it is used for power generation. In the current environment where all countries in the world are facing energy problems, research on wind power generation systems is also increasing. This article aims to study the problem of modeling and controlling wind speed in the wind power generation system of renewable energy power generation. To this end, this article proposes a modeling method for wind power generation systems, which can be used to study the momentum problems in wind power generation and the mechanical torque of the generator. And at the end of the article, related experiments and analysis are designed to explore and compare its operating cost, speed, and wind wheel speed. The experimental results in this paper show that through effective modeling and control of its wind speed, the economic risks in the actual wind power generation system can be controlled, with a maximum reduction of 24%, and the actual operating cost is also reduced by 8.66%, so wind power has high practical value.
The Diversity, Equity, & Inclusion (DEI) industry has grown throughout the public and private sectors, using ideas drawn from critical race theory yet applied in a manner that undercuts social justice goals. Research findings suggest that current approaches to DEI training do not meaningfully improve diversity and prejudice in institutions, and may worsen prejudice leading to racial backlash negatively impacting marginalized groups. The proposed chapter will critique DEI training framing racism primarily as a conflict of “White versus non-White,” which triggers avoidance among people of color and White people that deepens racial inequality. The chapter will review the findings of the Race-Class Narrative Project (Lopez, 2019) as a lens to rethink DEI training. The Race-Class Message, by framing racism as a weapon of class warfare exploited by the wealthy, increases the investment of Whites in Antiracism, paradoxically making them receptive to exploring traditional DEI topics such as White privilege. Preliminary recommendations will be elaborated showing how this approach radically restructures not only DEI training in the helping professions, but their broader curriculum as well.
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4,158 members
Arien Mack
  • Department of Psychology (Social Research)
Timon McPhearson
  • Urban Systems Lab
Jeremy Ginges
  • Department of Psychology (Social Research)
Brian P Mcgrath
  • Department of Architecture
Michael F Schober
  • Department of Psychology (Social Research)
New York City, New York, United States