Search

"Breaks in the Air: The Birth of Rap Radio in New York City" by John Klaess is a significant contribution to the history of New York hip-hop culture. The book explores the early days of rap radio in New York, when stations like WBLS played a crucial role in shaping the sound and culture of hip-hop. Klaess uses interviews and cassette recordings to provide insights into the inseparable relationship between rap, radio, and diverse listening communities. The book also examines the impact of deregulation on the commercial radio industry and the role of radio in advancing Black social progress. Overall, "Breaks in the Air" offers a valuable perspective on the history of rap radio in New York City. [Extracted from the article]

"Black Women and the Changing Television Landscape" by Lisa M. Anderson is a book that examines the portrayal of Black women on television throughout history. Anderson, an associate professor of women and gender studies, builds on her previous work to explore the complex and evolving representations of Black women in media. Using a semiotic approach and drawing on the work of Black feminist scholars, Anderson analyzes specific television shows and personalities from the 1950s to the present. The book goes beyond simplistic judgments and aims to understand the historical and cultural contexts in which these representations exist, as well as the agency of Black women in shaping them. It is a valuable resource for scholars in cultural, media, and television studies. [Extracted from the article]

The grid plays a prominent role in architecture, aiding in space organization and influencing all aspects of planning, ranging from urban design to intricate building details. This paper posits that the grid receives heightened emphasis in Brutalism, particularly in constructivist Brutalism, where materials and construction are intentionally exposed. A question arises regarding the grid's characteristics—despite its subtle appearance, the grid can sometimes be deceptive, ambiguous, and manipulative. The paper analyzes the merits and drawbacks of employing the grid in architecture, shedding light on its contributions to both structural and perceptual comprehensibility, as well as its role in increasing usefulness. To illustrate the application and perception of the grid, the paper examines two primary planning levels: urban planning and building design. The case studies focus on examples from New York City housing developments, specifically those constructed between the 1950s and the 1970s, and projects by architect I. M. Pei, which offer valuable insights into practical implementation. The paper concludes that while the grid can establish order, it may also engender an "uncanny" feeling. [ABSTRACT FROM AUTHOR]

Background: In the U.S. there are significant racial and gender disparities in the uptake of pre-exposure prophylaxis (PrEP). Black Americans represented 14% of PrEP users in 2022, but accounted for 42% of new HIV diagnoses in 2021 and in the South, Black people represented 48% of new HIV diagnoses in 2021 but only 21% of PrEP users in 2022. Women who use drugs may be even less likely than women who do not use drugs have initiated PrEP. Moreover, women involved in community supervision programs (CSP) are less likely to initiate or use PrEP, More PrEP interventions that focus on Black women with recent history of drug use in CSPs are needed to reduce inequities in PrEP uptake. Methods: We conducted a secondary analysis from a randomized clinical trial with a sub-sample (n = 336) of the total (N = 352) participants from the parent study (E-WORTH), who tested HIV negative at baseline were considered PrEP-eligible. Black women were recruited from CSPs in New York City (NYC), with recent substance use. Participants were randomized to either E-WORTH (n = 172) an HIV testing plus, receive a 5-session, culturally-tailored, group-based HIV prevention intervention, versus an HIV testing control group (n = 180). The 5 sessions included an introduction to PrEP and access. This paper reports outcomes on improved awareness of PrEP, willingness to use PrEP, and PrEP uptake over the 12-month follow-up period. HIV outcomes are reported in a previous paper. Results: Compared to control participants, participants in this study assigned to E-WORTH had significantly greater odds of being aware of PrEP as a biomedical HIV prevention strategy (OR = 3.25, 95% CI = 1.64–6.46, p = 0.001), and indicated a greater willingness to use PrEP as an HIV prevention method (b = 0.19, 95% CI = 0.06–0.32, p = 0.004) over the entire 12-month follow-up period. Conclusions: These findings underscore the effectiveness of a culturally-tailored intervention for Black women in CSP settings in increasing awareness, and intention to initiate PrEP. Low uptake of PrEP in both arms highlight the need for providing more robust PrEP-on-demand strategies that are integrated into other services such as substance abuse treatment. Trial Registration: ClinicalTrials.gov Identifier: NCT02391233. [ABSTRACT FROM AUTHOR]

Copyright of Urban Studies (Sage Publications, Ltd.) is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Given that Ecuadorians are one of the largest groups of Hispanics living in New York, they have become a tight community that they now call little Ecuador. Although Ecuadorians living in the diaspora in NYC come from different parts of the country (mostly from the Andean region), they share the same cultural practices they performed in Ecuador that give them the sense of being in their country without bearing the instability and turmoil their country experiences. This shows how the group has fostered a sense of a multifaceted, multidimensional simultaneity between the host country and the motherland. The goal of this paper is to analyze the strategies Ecuadorian migrants use to validate their language and cultural practices to negotiate their identity as a group. Data for this paper come from ethnographic observations, semi-spontaneous conversations, oral interviews with members of the group, along with pictures taken while walking the community and participating in some of their events. Our study reveals that participants hold varying perceptions regarding their linguistic and cultural practices. However, it is noteworthy that they recognize these practices as a manifestation of Ecuadorianness, signifying a sense of solidarity among community members. [ABSTRACT FROM AUTHOR]

In the dynamic realm of big data processing, conquering the challenges imposed by highdimensional datasets is imperative. This paper introduces a groundbreaking advancement in dimensionality reduction, employing Variational Auto-Encoder (VAE) within the Spark distributed framework. The deliberate selection of the "TLC" dataset, representative of New York City taxi trips with inherent high dimensionality, highlights the practicality of our approach. Our research showcases the virtuoso performance of VAE, achieving an impressive 95.12% reduction ratio and 89.26% accuracy. This highlights VAE's ability to elegantly distill essential information while discarding superfluous dimensions, achieving a harmonious balance between reduction and accuracy. Furthermore, building on the demonstrated superiority of Spark over Hadoop in prior successes, our adoption of VAE aligns with the overarching goal of enhancing big data processing. Spark's consistent advantage as a distributed framework reaffirms its reliability in handling diverse machine learning algorithms. This paper not only contributes to the advancement of machine learning in big data processing but also underscores the adaptability, versatility, and consistent performance of our approach across various methodologies and frameworks. The success of VAE in reducing dimensionality, coupled with Spark's inherent advantages, positions this research as a valuable contribution to the exploration of advanced techniques in distributed big data processing. [ABSTRACT FROM AUTHOR]

In the mid-twentieth century, growing North American textile and ready-to-wear industries vigorously appropriated Native American aesthetics to cultivate a commercial and design identity apart from Europe. Most studies of the circulation of Indigenous idioms in these industries focus on Southwestern or South Pacific regionalisms, and scholarship on studio and commercial fabric and fashion design from the Northwest Coast in the twentieth century is limited. This paper contributes by raising Indigenous and non-Indigenous use of Northwest Coast design forms during the politically turbulent 1940s–1960s and analyzing the impact of this aesthetic vocabulary within broader North American textiles and fashion. Throughout, I engage with the approaches of critical fashion theory and multiple modernisms, considering the frictions of property and power relations within settler-colonial states, then and now. Drawing from study of objects, periodicals, and archival materials as well as first-person perspectives, I contextualize these representations within entangled art, museum, and design worlds in the Northwest Coast, New York City, and the Southwest. My examination illustrates that Northwest Coast artists and art ideas asserted a peripheral but locatable role in mid-century textiles and fashion, facilitating the development of today's robust Indigenous fashion network on the Northwest Coast and its cultural politics. [ABSTRACT FROM AUTHOR]

Lateral roots, including adventitious roots, are the main component of rapeseed roots with support, absorb, and synthesis functions and their morphological parameters directly affecting the plant's aboveground growth and yield. Root biomass, as a material base for lateral root growth, can be used as a link between plant phenotypes and their physiological processes, as well as to enhance root 3D growth model mechanisms and accuracy. To quantify the relationships between lateral root morphological indices and the corresponding organ biomass for rapeseed, we used two cultivars, NY 22 (conventional) and NZ 1818 (hybrid), and conducted cultivar and fertilizing cylindrical tube experiments during the 2016–2019, with two fertilizer levels, no fertilizer, and 180 kg N ha−1 fertilizer. The lateral root biomass and morphological parameters were determined during the whole growth period. The biomass‐based lateral root morphological parameter models were developed by analyzing the quantitative relationship between the lateral root morphological indices and their corresponding biomass, and the descriptive models were verified with independent experimental data. The results showed that the correlation (r) of simulated and observed values for the lateral root morphological parameters are all greater than 0.9 with significant levels at p < 0.001. The absolute values of the average absolute difference (da) of simulated and observed values for the lateral root length (LLR), lateral root average diameter (ADLR), lateral root surface area (SALR), and lateral root volume (VLR) are −30.408 cm, −0.003 mm, 12.902 cm2, and 0.039 cm3, respectively. The RMSE values are 175.183 cm, 0.010 mm, 59.710 cm2, and 1.513 cm3, respectively. The ratio of da to the average observed values (dap) for the LLR and VLR are all less than 5%, and the ADLR and SALR are all <6%. The models developed in this paper have good performance and reliability for predicting lateral root morphological parameters of rapeseed. The study provides a mechanistic method for linking the rapeseed growth model with the morphological model using corresponding organic biomass and laying a good foundation for establishing a 3D morphological model for rapeseed root system based on biomass. [ABSTRACT FROM AUTHOR]

The critical platform studies literature is increasingly considering the role of social difference as a structuring logic in the platform economy, complementing understandings of worker precarity facilitated by worker misclassification and algorithmic management. Contributing to this literature, this paper demonstrates how platforms and police produce carceral geographies that manage and exploit immigrant delivery workers as surplus populations. The carceral geographies of the platform economy account for both how carceral space produces and manages the surplus populations from which platform capital draws its workers, facilitating the disposability and exploitation of workers. Focusing on South Asian delivery workers in New York City, the paper uses the example of bike registrations to show how police and platforms expand carceral spaces in immigrant communities, increasing their vulnerability to premature death and violence. Finally, it suggests how delivery worker organising offers instances of situated resistance that challenge platform capital and carceral logics. [ABSTRACT FROM AUTHOR]

This research is concerned with individuals' symbolic interactions with the Charging Bull statue. We chose this statue because it is an extremely popular tourist attraction and the most visited nonhuman statue in New York City. However, there is no research devoted to understanding how visitors interact with the statue. To fill this gap in the literature, we examine people's interactions as a unique way of communicating with the Charging Bull statue in New York City through a photo analysis approach. Using the general framework of symbolic interactionism, the paper investigates poses, gestures, and more generally interactions of individuals near or with the statue to gain insights into the impact of the Charging Bull beyond a mere visual representation. The findings reveal various forms of interaction, including souvenir photography, active participation, unexpected interactions, and public-made symbolism. This study of these interactions contributes to the literature on collective memory and the study of statues. Additionally, this research highlights the inventiveness of the dynamic relationship between individuals and statues as symbols in the urban environment. [ABSTRACT FROM AUTHOR]

This paper provides a mathematical optimization strategy for optimal municipal solid waste management in the context of the COVID-19 epidemic. This strategy integrates two approaches: optimization and machine learning models. First, the optimization model determines the optimal supply chain for the municipal waste management system. Then, machine learning prediction models estimate the required parameters over time, which helps generate future projections for the proposed strategy. The optimization model was coded in the General Algebraic Modeling System, while the prediction model was coded in the Python programming environment. A case study of New York City was addressed to evaluate the proposed strategy, which includes extensive socioeconomic data sets to train the machine learning model. We found the predicted waste collection over time based on the socioeconomic data. The results show trade-offs between the economic (profit) and environmental (waste sent to landfill) objectives for future scenarios, which can be helpful for possible pandemic scenarios in the following years. [ABSTRACT FROM AUTHOR]

Drones are becoming indispensable in emergency search and rescue (SAR), particularly in intricate urban areas where rapid and accurate response is crucial. This study addresses the pressing need for enhancing drone navigation in such complex, dynamic urban environments, where obstacles like building layouts and varying wind conditions create unique challenges. Particularly, the need for adapting drone autonomous navigation in correspondence with dynamic wind conditions in urban settings is emphasized because it is important for drones to avoid loss of control or crashes during SAR. This paper introduces a pioneering method integrating multiobjective reinforcement learning (MORL) with a convolutional autoencoder to train autonomous drones in comprehending and reacting to aerodynamic features in urban SAR. MORL enables the drone to optimize multiple goals, whereas the convolutional autoencoder generates synthetic wind simulations with a substantially lower computation cost compared to traditional computational fluid dynamics (CFD) simulations. A unique data transfer structure is also proposed, which fosters a seamless integration of perception and decision-making between machine learning (ML) and reinforcement learning (RL) components. This approach uses imagery data, specific to building layouts, allowing the drone to autonomously formulate policies, prioritize navigation decisions, optimize paths, and mitigate the impact of wind, all while negating the necessity for conventional aerodynamic force sensors. The method was validated with a model of New York City, offering substantial implications for enhancing automation algorithms in urban SAR. This innovation enables the possibility of more efficient, precise, and timely drone SAR operations within intricate urban landscapes. [ABSTRACT FROM AUTHOR]

This paper explores an interdisciplinary approach that researchers can use to understand how people feel about their movement in the cityscape and their risk-taking activities by visualizing it. Author 1, a visual artist, and Author 2, a criminologist, used a psychogeography method where participants hand-drew maps of their everyday operations in the sex marketplace. Researchers, artists, and activists have used mapmaking to elucidate how individuals conceptualize physical space and place or their subjective, emotional relationship to the city's geography. Psychogeographers Lynch and Debord have used it to understand how participants feel about moving, inhabiting, navigating risk, and subverting space in the metropolis. We use this method as a vehicle to show how sex market facilitators' imagine the physical geographic space where they work in the nighttime economy, their embodiment in managing a business in the urban landscape, their emotions in this risk-taking activity, and how they feel rerouting city blocks and subverting formal capitalism. In addition, this technique enabled participants to feel and recall emotions of this lived experience, such as excitement, control, authenticity, shame, and freedom. Sixty participants who worked in New York City hand drew mental maps or visual depictions of where they worked within the city. This visual storytelling method provides an avenue for what O'Neill terms an ethno-mimetic process where images/performances make lived experiences palpable to viewers. In this case, we see a glimpse of the sensations of this high-risk activity in the sex marketplace, allowing us to understand participants' social relations, lived experiences, and motivations. [ABSTRACT FROM AUTHOR]

Throughout the 1970s, a drive towards the diversification of mediums available to artists led to artists working across numerous mediums not usually associated with visual art. While some came to work with sound as a central focus in their practice, most used sound as a medium to be employed in particular artworks for conceptual purposes. The paper is focused on five audio and sound exhibitions presented in New York City between 1978 and 1984. These large group exhibitions were held in alternative art spaces and not-for-profit art galleries and have received little critical attention beyond reviews published in local newspapers and art magazines. As such, these exhibitions have all but disappeared from the history of sound in art and from art history in general. I will argue that this cluster of group shows signal to an emergent practice that was moving past the post-medium condition and conceptual art towards the postmodernism of the 1980s. These exhibitions point to an understanding of sound as a medium of visual art that is at odds with contemporary scholarship in the sonic arts, which favours a music-based understanding of approaches to sound within the art gallery. [ABSTRACT FROM AUTHOR]

[Objective] Tiger nut is a cash crop in southern Xinjiang and its production relies on irrigation. This paper presents the results of an experimental study on the effect of irrigation amounts on physiological traits, yield, and water use efficiency of different varieties of tiger nuts. [Method] The experiment studied two varieties: the Henan Round Grain (HY) and the Inner Mongolia Round Grain (NY), each irrigated by 18 mm (W1), 27 mm (W2), 36 mm (W3), and 45 mm (W4) of water, respectively. In each treatment, we measured the changes in soil water storage, plant height, tiller numbers, photosynthetic traits, yield, water consumption, and water use efficiency of the plants at different growing stages. [Result] Soil water storage and water consumption of both varieties increased with irrigation amount. Compared to W1, W4 increased average soil water storage and water consumption of the plants by 24.84% and 60.57% for the HY, and 18.46% and 55.61% for the NY, respectively. The plant height, tiller numbers, net photosynthesis (Pn), stomatal conductance (Gs), transpiration rate (Tr) and the yield of HY increased with irrigation amount (P<0.05), peaking in W2 with increases of 24.60%, 15.11%, 28.14%, 34.86%, 40.49% and 13.92% compared to W1. Intercellular carbon content (Ci) decreased with increasing irrigation amount. With the increase in irrigation amount, the plant height, tiller numbers, Pn, Gs, Tr, and the yield of NY all increased first followed by a decline; their associated values in W2 were 26.07%, 20.26%, 19.69%, 38.38%, 44.92% and 20.83% higher than those in W1. On average, Ci decreased with irrigation amount, being lowest in W2. Water use efficiency and irrigation water use efficiency of both varieties decreased with irrigation amount. Principal component analysis showed the net photosynthetic rate and water use efficiency can be used as indicators for variety selection. [Conclusion] The optimal irrigation amounts for the varieties HY and NY are 45 mm and 27 mm respectively, which can promote healthy growth, improve yields, and enhance water use efficiency of the plants. [ABSTRACT FROM AUTHOR]

The built environment anchors social, economic, and political community. A limited neighbourhood milieu fosters and maintains relationships that enable a community to realize its values. Fundamental civic activities such as getting out the vote depend on this empowerment. Voting has declined across New York City, but especially in the Bronx, which experienced the largest decline in voting between the 1969 and 2021 mayoral elections. The South and Central Bronx is now the largest city area of extremely low voter participation. This paper explores how public policies generated by the real estate industry – specifically redlining, urban renewal, and planned shrinkage – in conjunction with the Permanent Registration article in the 1938 New York State Constitution suppressed voting. The distribution of premature mortality and other health problems in the Bronx appear to be another consequence of these policies. That is, disempowerment and health erosion appear related and stem from influence of the real estate industry on mayoral policy. [ABSTRACT FROM AUTHOR]

This paper explores the role of 'informal' financial practices in shaping the resilience of immigrant urban communities, many of which are centered around families—nuclear, extended, and chosen. It looks at financial transactions and services, with particular attention to Rotating Credit and Savings Associations (ROSCAs), whose members are frequently related to each other through ties of kinship, especially in Hispanic circles. In a pioneering study documenting ROSCAs, they were defined as associations where members agree to make regular contributions of money to a fund that is given to each contributor in rotation. Because of their presence in various cultures and geographies, researchers from various disciplines have studied them, mostly in developing countries and immigrant communities within the United States. It is argued that such mechanisms substitute or complement formal financial services that do not fulfill their needs and play a key role in the infrastructures of immigrant communities to be resilient in the face of adverse circumstances. Findings from the present study's fieldwork, conducted in one neighborhood in New York City's South Bronx, show that these kinds of groups address the members' short-term safety and resilience needs. However, given their low returns and unclear procedures to address wrongdoings, they entail higher risks for long term planning and social mobility. Nevertheless, given their persistent and organic nature across cultures and borders, they provide important insights to address those gaps and shed light on the contributions of family dynamics to the public domain. [ABSTRACT FROM AUTHOR]

Examining the impacts of ranked choice voting (RCV) on voter efficacy is important as more areas consider adoption. The greater number of choices provided by longer RCV ballots may introduce opportunities for voters to misunderstand the ballot, make errant marks, or accidentally mark two or more candidates for one ranking, resulting in voidable ballots due to "overvoting." Using ballot data from the 2013 general election, the 2017, and 2021 New York City democratic mayoral primaries, this paper asks whether voidable overvote ballots are more concentrated in constituencies with lower levels of educational attainment, average household incomes, and differing racial make-ups, and if this relationship is more pronounced under RCV than traditional elections. In the first RCV election in 2021, voters in locations with lower levels of educational attainment and median household incomes had higher shares of overvote voidable ballots than those in locations with higher educational attainment and incomes. [ABSTRACT FROM AUTHOR]

Human movements in urban areas are essential to understand human–environment interactions. However, activities and associated movements are full of uncertainties due to the complexity of a city. In this paper, we propose a novel sensor-based approach for spatiotemporal event detection based on the Discrete Empirical Interpolation Method. Specifically, we first identify the key locations, defined as "sensors", which have the strongest correlation with the whole dataset. We then simulate a regular uneventful scenario with the observation data points from those key locations. By comparing the simulated and observation scenarios, events are extracted both spatially and temporally. We apply this method in New York City with taxi trip record data. Results show that this method is effective in detecting when and where events occur. [ABSTRACT FROM AUTHOR]

Community-clinical linkage models (CCLM) have the potential to reduce health disparities, especially in underserved communities; however, the COVID-19 pandemic drastically impacted their implementation. This paper explores the impact of the pandemic on the implementation of CCLM intervention led by community health workers (CHWs) to address diabetes disparities among South Asian patients in New York City. Guided by the Consolidated Framework for Implementation Research (CFIR), 22 stakeholders were interviewed: 7 primary care providers, 7 CHWs, 5 community-based organization (CBO) representatives, and 3 research staff. Semi-structured interviews were conducted; interviews were audio-recorded and transcribed. CFIR constructs guided the identification of barriers and adaptations made across several dimensions of the study's implementation context. We also explored stakeholder-identified adaptations used to mitigate the challenges in the intervention delivery using the Model for Adaptation Design and Impact (MADI) framework. (1) Communication and engagement refers to how stakeholders communicated with participants during the intervention period, including difficulties experienced staying connected with intervention activities during the lockdown. The study team and CHWs developed simple, plain-language guides designed to enhance digital literacy. (2) Intervention/research process describes intervention characteristics and challenges stakeholders faced in implementing components of the intervention during the lockdown. CHWs modified the health curriculum materials delivered remotely to support engagement in the intervention and health promotion. (3) community and implementation context pertains to the social and economic consequences of the lockdown and their effect on intervention implementation. CHWs and CBOs enhanced efforts to provide emotional/mental health support and connected community members to resources to address social needs. Study findings articulate a repository of recommendations for the adaptation of community-delivered programs in under-served communities during a time of public health crises. [ABSTRACT FROM AUTHOR]

This paper explores the ways in which Mexican immigrants experience, narrate, and describe stress and the extent to which it impacts their efforts at engaging in physical activity using a biocitizenship framework. Data were derived from a mixed-method study among Mexicans living in New York City recruited from a large Catholic church. The qualitative sample of 25 participated in quantitative and qualitative components of the study and as such we include some of these quantitative indicators as descriptors. Our main qualitative findings reveal that study participants experience stress and time constraint as factors that contribute to the waning of their physical and mental well-being. As such, time constraints for many of our participants were among the factors that contributed to high perceived levels of stress. They attributed this to their difficulty maintaining a physically active lifestyle due to factors like the fast-paced lifestyle in New York, working long hours, and not having enough time to exercise, though some important differences in narratives were noted across gender. Findings have implications for interventions aimed at improving the health of immigrants in general and Mexican immigrants in New York City specifically. [ABSTRACT FROM AUTHOR]

Ridesharing effectively tackles urban mobility challenges by providing a service comparable to private vehicles while minimising resource usage. Our research primarily concentrates on dynamic ridesharing, which conventionally involves connecting drivers with passengers in need of transportation. The process of one-to-one matching presents a complex challenge, particularly when addressing it on a large scale, as the substantial number of potential matches make the attainment of a global optimum a challenging endeavour. This paper aims to address the absence of an optimal approach for dynamic ridesharing by refraining from the conventional heuristic-based methods commonly used to achieve timely solutions in large-scale ride-matching. Instead, we propose a novel approach that provides snapshot-optimal solutions for various forms of one-to-one matching while ensuring they are generated within an acceptable timeframe for service providers. Additionally, we introduce and solve a new variant in which the system itself provides the vehicles. The efficacy of our methodology is substantiated through experiments carried out with real-world data extracted from the openly available New York City taxicab dataset. [ABSTRACT FROM AUTHOR]

This paper presents methods to proactively choose individuals to test for infection during a pandemic such as COVID-19, characterized by high contagion and presence of asymptomatic carriers. We show that by a smart integration of exploration/exploitation balancing, contact tracing, and location-based sampling, one can effectively mitigate the disease spread and significantly reduce the infection rates and death rates. Under different vaccination policies and under different compliance levels to quarantine order and/or testing requests, our smart testing algorithm can bring down the death rate significantly by 20% to 30%, as well as the percentage of infected drops by approximately 30%. The load on hospitals at peak times, a crucial aspect of managing COVID-19, drops, by 50% when implementing smart testing. We also show how procedural fairness can be incorporated into our method and present results that show that this can be done without hurting the effectiveness of the mitigation that can be achieved. This paper presents methods to choose individuals to test for infection during a pandemic such as COVID-19, characterized by high contagion and presence of asymptomatic carriers. The smart-testing ideas presented here are motivated by active learning and multi-armed bandit techniques in machine learning. Our active sampling method works in conjunction with quarantine policies, can handle different objectives, and is dynamic and adaptive in the sense that it continually adapts to changes in real-time data. The bandit algorithm uses contact tracing, location-based sampling and random sampling in order to select specific individuals to test. Using a data-driven agent-based model simulating New York City we show that the algorithm samples individuals to test in a manner that rapidly traces infected individuals. Experiments also suggest that smart-testing can significantly reduce the death rates as compared with current methods, with or without vaccination. While smart testing strategies can help mitigate disease spread, there could be unintended consequences with fairness or bias when deployed in real-world settings. To this end we show how procedural fairness can be incorporated into our method and present results that show that this can be done without hurting the effectiveness of the mitigation that can be achieved. History: Ahmed Abbasi, Senior Editor; Maytal Saar-Tsechansky, Associate Editor. Funding: W. Yahav is supported by the Jeremy Coller Foundation and the Henry Crown Institute of Business Research in Israel. Supplemental Material: The e-companion is available at https://doi.org/10.1287/isre.2023.1215. [ABSTRACT FROM AUTHOR]

In this article, I argue that indigenous Latin American food delivery workers organize to defy information and knowledge asymmetries by utilizing technology built to mediate online social interactions. Drawing on ethnographic fieldwork, this paper investigates transnational modes of community-building and network formation and examines how these networks are instrumental for delivery workers in New York City to exercise agency, forge their narrative, and resist platform control by resisting, pushing, and extending a variety of digital and communication technologies. I analyze how public and private means of communication facilitate and constrain social forms of organization by mapping how delivery workers communicate and engage collectively both in the physical and the digital worlds. My research reveals two platforms that workers use to share information: one that operates inwards (WhatsApp) and another that operates outwards (Facebook). These channels represent opposite sides of the spectrum between public and private and synergize to form a transnational distributed knowledge network to shape and interpret the collective identity of Latin American delivery workers. Overall, this article sheds light on how the flow of information through different spaces and times enables delivery workers to construct a place for subversion and negotiation with roles assigned to them by broader socio-political forces. [ABSTRACT FROM AUTHOR]

The New York City Department of Health and Mental Hygiene (Health Department) has responded to an article that claimed their workforce discriminated against Asian restaurants during the early months of the COVID-19 pandemic. The Health Department conducted an investigation and found no evidence of bias against Asian restaurants in their inspectional data. They also criticized the authors of the article for using an incomplete dataset and not reaching out for assistance or collaboration. The Health Department presented their own analysis of inspection results, which showed no evidence of an uptick in violations among Asian restaurants. They concluded that the findings of the article are erroneous and rejected the accusations of discrimination. [Extracted from the article]

In this paper we consider working-class abolitionist feminists' conceptualizations of safety. Taking seriously the notion that "freedom is a place," we look at how working-class South Asians and Indo Caribbeans in New York City build livable worlds at the intersecting crises of capitalism, white supremacy, and patriarchy. We look at Desis Rising Up and Moving (DRUM)'s organizing efforts following the expansion of immigrant detention and policing that came after the 1996 immigration laws and their contemporary organizing around gender-based violence and oppression as examples of a materialist articulation of abolition feminism. Drawing on DRUM's archive and autoethnographic reflections, we show how DRUM develops and practices an abolition feminism that addresses both systematized racial state violence and patriarchal violence in working-class Asian American communities. We show how DRUM's experiments with community-based intervention (CBI) around domestic violence aims to reduce violence and meet the material needs of gender-oppressed individuals in the community, while expanding the horizon for socialized care and a world without police. [ABSTRACT FROM AUTHOR]

In 2018, the New York City (NYC) Department of Health and Mental Hygiene piloted a novel jurisdictional risk assessment (JRA) for public health disasters using the analytic hierarchy process (2018 JRA‐AHP). This new approach offers a replicable and equitable model for consensus decision‐making that incorporates the complexities of disaster preparedness. Its main contribution to the field is to offer a practical manifestation of emergency management's Whole Community Approach. The 2018 JRA‐AHP applied this principle by expanding traditional definitions of 'expertise' to include lived experience of disaster and facilitating direct participation in the risk decision by a variety of individuals with diverse backgrounds, expertise and knowledge of public health disasters. This paper describes the theory, methods and results behind the JRA‐AHP. The paper also presents a critical analysis of public health disaster risk assessments; contextualizes the Whole Community Approach using models of the relationship between democratic governments and communities; and addresses the practical applications of the 2018 JRA‐AHP in NYC while exploring the potential challenges that other jurisdictions may face in attempted adaptation. [ABSTRACT FROM AUTHOR]

Greenery initiatives, such as green infrastructures (GIs), create sustainable and climate-resilient environments. However, they can also have unintended consequences, such as displacement and gentrification in low-income areas. This paper proposes an integrated machine learning (ML) approach that combines both unsupervised and supervised ML algorithms. First, 35 indicators that contribute to green gentrification were identified and categorised into 7 categories: social, economic, demographic, housing, household, amenities, and GIs. Second, data was collected for all census tracts in New York City. Third, the green gentrification susceptibility was modelled into 6 levels using k-means clustering analysis, which is an unsupervised ML model. Fourth, the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) was used to map the census tracts to their green gentrification susceptibility level. Finally, different supervised ML algorithms were trained and tested to predict the green gentrification susceptibility. The results showed that the artificial neural network (ANN) model is the most accurate in classifying and predicting the green gentrification susceptibility with an overall accuracy of 96%. Moreover, the outcomes showed that the Normal Difference Vegetation Index (NDVI), the proximity to GIs, the GIs frequency, and the total area of GIs were identified as the most important indicators to predict green gentrification susceptibility. Ultimately, the proposed approach allows practitioners and researchers to perform micro-level (i.e. on the census-tracts level) predictions and inferences about green gentrification susceptibility. This allows more focused and targeted mitigation actions to be designed and implemented in the most affected communities, thus promoting environmental justice. [ABSTRACT FROM AUTHOR]

Puerto Rico is one of the world's oldest colonies, with thousands of its people dislocated to the United States (U.S.) mainland in the wake of Hurricane Maria and the ongoing economic crisis. However, since the 2019 protests ousting then governor Rosello, Puerto Ricans across the Diaspora are imagining new emancipatory realities, including the possibility of independence. This paper draws on data from the Colonial Mentality Study in New York City (CMS‐NYC, N = 19) to explore how Puerto Ricans in the Diaspora narrativize new political possibilities despite the challenges posed by post‐disaster migration and racial and economic inequality. Using a decolonial psychoanalytic approach, we show how two colonial logics—moving "up and out" of Puerto Rico and "up and in" American capitalism—are textured by discourses of racial inferiority and upward mobility, and illustrate how these are experienced by Puerto Ricans who identify as Multiracial (Multiracial‐Identified Puerto Rican, N = 11), and Puerto Ricans who identify as Black (BIPR, N = 8). Reading our findings in the sociogenic context of race, class, and colonialism in Puerto Rico, and race and class among Puerto Ricans in NYC, we explore how racism toward Puerto Ricans and racism among Puerto Ricans intersect with notions of upward mobility, revealing how anti‐Blackness supports economic inequality in the U.S. mainland alongside with Puerto Rico's colonial situation. Complementing decolonial psychoanalytic theory with the Afro‐Puerto Rican radical tradition, we outline the implications of this research for future scholarship, clinical practice, and political action. [ABSTRACT FROM AUTHOR]

It is well known that the increase in coastal flood hazard is expected to continue due primarily to climate change. While, previous studies have advanced probabilistic approaches for estimating future coastal flood hazard, two seminal issues have received little attention: (1) sea level trend projections that arise as a consequence of climate change not being incorporated in nonstationary coastal flood frequency analysis and (2) traditional stationary approaches that estimate return periods are not suited for analysis of nonstationary water levels. In this paper, a regression approach for sea level rise estimation is proposed to detrend water levels. The peak-over-threshold approach is used to analyze the probabilistic behavior of detrended water levels via a generalized Pareto distribution. Two interpretations of return period—the expected waiting time until an exceedance event occurs and the time associated with the expected number of exceedance events equal to one—are elaborated in a nonstationary context. By incorporating the existing sea level trend projections and using two interpretations of return period, flood hazard curves with uncertainty (i.e., water levels vs. return periods) are developed to describe the probabilistic behavior of future coastal flood hazards. Two case studies are conducted: one for Boston, Massachusetts, and one for New York City, New York. [ABSTRACT FROM AUTHOR]

This paper analyses how Vision Zero (VZ) efforts in New York City (NYC) account for equity and social justice implications of road safety work. VZ policy documents, research literature, popular science and opinion articles on road safety work in the city were studied with a prime focus on equity and social justice. Twelve semi-structured interviews with stakeholders involved in road safety and transport planning in the city and at national level were conducted to gain an in-depth understanding of policy design, the adoption process, and the role of equity considerations in the city's road safety work. The results show that major equity and social justice issues arise in the adoption and implementation of VZ. These issues are primarily related to equity and fairness in the distribution of life saving interventions, the socio-economic impacts of road safety strategies, and the nature of community engagement in policy design and implementation. The findings point to a need for VZ practitioners to give due considerations to equity and social justice implications of VZ policies and strategies. Among others, it supports the need for understanding the nature of past equity and social justice problems in road safety and transport planning in the VZ policy design process. Moreover, the findings suggest the need for empirical studies on the socio-economic implications of VZ strategies and interventions. • There were major road safety related inequities and injustices prior to the adoption of Vision Zero in New York City. • The promotion of Vision Zero also gives rise novel equity and social justice concerns related to its adoption process and the choice of road safety strategies and interventions. • A successful and morally acceptable implementation of Vision Zero demands recognizing and proactively accounting for ethically problematic aspects of road safety work, including those related to equity and social justice. • Vision Zero should integrate equity and social justice into road safety work, for example, by adopting a broader conceptualization of a data driven approach that includes socioeconomic and community data in addition to quantitative crash data. • The promotion of Vision Zero should allow meaningful inclusion and participation of different road user and socioeconomic groups in the goal setting and implementation of Vision Zero policies. [ABSTRACT FROM AUTHOR]

Nature-based instruction offers students the benefits of experiential learning while spending time in nature. Research supports nature-based learning (NBL) with younger students (Pre-K--12), yet there is a dearth of research focused on students in post-secondary education. To advance research in higher education, an NBL project was launched with 16 faculty members (two cohorts) from different disciplines at a commuter community college in New York City to pilot the implementation of NBL into the curriculum. This paper offers a model to guide the implementation of NBL in a variety of disciplines. It is hoped that this model may be used by other undergraduate institutions who aim to integrate novel approaches to experiential learning. [ABSTRACT FROM AUTHOR]

The geography of sex work has received attention from scholars exploring its ebb and flow based on how police, neighbors, and gentrification influence sex work zones; however, there are few studies about how sex market facilitators move within and feel about working in these zones. Researchers, artists, and activists have used psychogeography maps or maps that elucidate how individuals conceptualize place and their personal, emotional relationship to the city's geography. We, a criminologist and a visual artist, used this psychogeography technique adapted from Debord and Lynch's work. Sixty sex market facilitators working in NYC from the 1970s–2012 drew maps of their everyday operations. This participatory method enabled participants to feel and recall the emotions of this high-risk activity. This paper analyzes participants' maps and corresponding narratives by exploring Lyng's idea of edgework, the synergy of risk-taking activity, and feelings of mastery, authenticity, excitement, control, and a search for respect. This study addresses how participants map urban space from positions of 'advanced marginalization,' showing the impacts of spatial and mental boundaries of possibility. Through this psychogeography method, participants engaged in 'countermapping' as a form of resistance. The sensations and emotions derived from facilitation and its evolution moved us closer to understanding sex market facilitation from the inside. [ABSTRACT FROM AUTHOR]

Existing studies suggest that platform access restriction may cause restricted complementors to switch to competing platforms, which will increase complement quantity on competing platforms. We re-examine this prediction by accounting for the impact of economies of scope on complementor responses to platform access restriction. We argue that restricting a complementor's access on a platform may prevent it from achieving economies of scope from multi-homing, thereby incentivizing it to abandon both the restricted and (unrestricted) competing platforms. Using rideshare data in New York City, we compare the numbers of trips made by Lyft and Uber drivers, respectively, before and after Lyft restricted drivers' access on its platform. We find that Lyft's access restriction reduced trip numbers not only on Lyft but also on Uber. In addition, both Lyft's and Uber's trip numbers decreased not only during the restricted low-demand periods (e.g., non-rush hours) but also during the unrestricted high-demand periods (e.g., rush hours). In contrast, after a substantial number of multi-homing drivers left both platforms following Lyft's access restriction, a subsequent access restriction by Uber led to an increase in trip numbers on Lyft. These results highlight the importance of accounting for interdependencies across complementor activities when designing platform governance policies. This paper was accepted by Alfonso Gambardella, business strategy. Funding: H. D. Chung acknowledges support from the Strategic Research Foundation's Dissertation Research [Grant SRF-2021-DRG-8363]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4706. [ABSTRACT FROM AUTHOR]

Ride-sharing contributes significantly to lowering trip expenses, easing traffic congestion and decreasing air pollution. However, current order pairing approaches in ride-sharing usually focus on minimizing total trip distances or maximizing platform profits, overlooking the drivers' desire for increased earnings. As a result, drivers might provide dishonest information to gain higher profits, leading to inefficient order pairing for the ride-sharing platform and potential losses for both the platform and drivers. In this paper, we address this challenging issue by developing efficient order pairing mechanisms that maximize the social welfare of the platform and drivers. Specifically, we introduce two truthful auction-based order pairing mechanisms, SWMOM-VCG and SWMOM-GM, where drivers bid on platform-published orders to complete them and earn profits. We provide theoretical proof that both mechanisms fulfill the criteria of individual rationality, profitability, truthfulness and so on. Using real taxi order data from New York City, we assess the performance of both mechanisms and show that they achieve greater social welfare compared to existing methods. Additionally, we find that SWMOM-GM requires less computation time than SWMOM-VCG for order pairing, with only a minor reduction in social welfare. [ABSTRACT FROM AUTHOR]

Several observational studies from locations around the globe have documented a positive correlation between air pollution and the severity of COVID-19 disease. Observational studies cannot identify the causal link between air quality and the severity of COVID-19 outcomes, and these studies face three key identification challenges: 1) air pollution is not randomly distributed across geographies; 2) air-quality monitoring networks are sparse spatially; and 3) defensive behaviors to mediate exposure to air pollution and COVID-19 are not equally available to all, leading to large measurement error bias when using rate-based COVID-19 outcome measures (e.g., incidence rate or mortality rate). Using a quasi-experimental design, we explore whether traffic-related air pollutants cause people with COVID-19 to suffer more extreme health outcomes in New York City (NYC). When we address the previously overlooked challenges to identification, we do not detect causal impacts of increased chronic concentrations of traffic-related air pollutants on COVID-19 death or hospitalization counts in NYC census tracts. [ABSTRACT FROM AUTHOR]

As resilience planning gains prominence in urban sustainable development, green infrastructures (GIs) are widely recognized as effective solutions to address climate risks and environmental challenges. While urban greening initiatives have multiple benefits, they can also lead to unintended consequences such as environmental injustice, increasing property values, and the displacement and gentrification of vulnerable residents in the affected areas. While gentrification remains a significant concern for urban sustainability initiatives that aim to promote environmental justice, a consensus upon approaches and methods for precisely identifying communities undergoing gentrification is still lacking. While most of the existing research studies focused on examining the relationship between GIs and gentrification, little-to-no research was conducted to quantify the green gentrification vulnerability of different communities. To this end, and to bridge this knowledge gap, this paper proposes and develops a novel index called the green gentrification vulnerability index (GGVI). First, an extensive list of 35 indicators that contribute to green gentrification was identified and grouped into 7 categories: economic, social, housing, household, demographic, amenities, and GIs. Second, data were gathered on the 35 indicators for all the 2325 census tracts across New York City (NYC) in the US. Third, the data were preprocessed to ensure their suitability for implementing Principal Component Analysis (PCA). Fourth, PCA was implemented for each of the 7 categories separately to weight their respective green gentrification indicators and calculate vulnerability scores. Finally, these vulnerability scores were used to develop the GGVI. The research findings provided insights on the importance of the 35 indicators as well as the 7 green gentrification-related vulnerability categories in relation to their contribution to the GGVI. The 7 categories were ranked as follows: amenities, GIs, economic, demographic, social, housing, and households. In addition, proximity to parks, frequency of parks, proximity to GIs, and total area of parks were found to be the most important GIs-related indicators that could lead to green gentrification. Overall, this paper contributes to the growing body of research that addresses green gentrification by being the first study that proposes and develops a GGVI that can be used to identify at-risk communities from green gentrification and ultimately help practitioners, urban planners, decision-makers, and researchers in developing new policies and strategies aimed to mitigate the unintended consequences of green gentrification (i.e., displacement of vulnerable communities) and promote environmental justice and urban sustainability. • Green gentrification vulnerability was studied based on 35 indicators. • The importance of the different indicators was determined. • Principal Component Analysis was used to develop a GGVI. • The proposed index allows census-track green gentrification vulnerability analysis. [ABSTRACT FROM AUTHOR]

Recent research on police misconduct has adopted a network perspective, while recent work on correctional officer (CO) use of force has similarly framed it as an organizational behavior, learned through socialization and deployed with considerable discretion. This paper leverages the network paradigm in police misconduct research to study the use of force by COs. Using data on lawsuits involving the New York City Department of Correction from 2013 to 2022, this paper forms a co-offending network of those COs who have been sued for excessive force. This paper then uses descriptive social network analysis and key player selection and community detection methods. After describing the basic network structure of COs who use force together, this paper identifies brokers who connect disparate parts of the CO network; it also uses a community detection algorithm to identify clusters of COs involved in force incidents. Finally, the paper compares this network to an analogous network of police use of force, finding structural similarities. This analysis bridges disparate work on correctional officer use of force and police misconduct; for policymakers who seek to curtail COs' excessive use of force, this paper might provide a blueprint for identifying key players and clusters. • Correction officer use of force is an organizational, socialized behavior. • Network methods can be used to study both police and CO use of force. • CO use of force has a networked structure; I identify network brokers and clusters. • These results can guide the targeted disruption of excessive force in jails. [ABSTRACT FROM AUTHOR]

This paper critically examines the concept of "green resilience" – the mobilization of gardens and urban green spaces for enhancing the resilience of communities and cities in the face of increasing uncertainty and risk. Drawing inspiration from seminal work in human-plant geographies, it explores the governmental functions and political implications of green resilience, arguing that these spaces serve as key forms of state rule and biopolitical power. The study employs the notion of green resilience as a "composition," emphasizing the assembling of diverse human and nonhuman actors in resilience projects. The developed compositional ontology highlights the importance of aesthetic and visual practices in green resilience projects and reveals how these are continuously decomposed and recomposed by the involved actors. The paper develops its arguments through a "paradigmatic case study" of various green resilience projects in New York City – including survivor trees, memorial groves, and community gardens. The study illuminates the multiplicity of green resilience initiatives and the underlying governmental logic by comparing these projects. Through its analysis, the paper contributes to the literature on resilience as an emerging governance paradigm. It reveals how green resilience projects embody a multiplicity of practices, uncovers the first comprehensive comparative analysis of various forms of green resilience, and offers a critique of resilience from within. The study concludes by identifying three tensions or contradictions of (green) resilience as a form of biopolitical government: visibility and invisibility, knowledge and ignorance, and control and emergence. [ABSTRACT FROM AUTHOR]

In this paper I bring together scholarship from the 'reparative turn' in the social sciences with the long tradition of critiquing schooling in the sociology of education. Most recently in this tradition, Ball and Collet-Sabé (2021) argue convincingly that the modern school is an 'intolerable institution' bound in its very epistemology to reproduce conditions of future uncertainty and inequity. I draw on Hong's (2014) framing of neoliberalism as a process of erasure and disavowal in order to link Ball and Collet-Sabé 's contention with the concept of reparative futures (Sriprakash et al. 2020). I do so through a consideration of my 2014–15 ethnography of Bronx High, a public high school in New York City. Through the story of seniors at Bronx High, I demonstrate how schooling is profoundly oriented towards particular anticipatory practices - namely, a modernist, neoliberal reckoning of the future that is both illusory in its promises and unsustainable in its ambitions. Bronx High exemplifies the deleterious impacts of living in a future-oriented present that appears wilfully detached from injustices of the past. However, this is not the whole story. The day-to-day actions of teachers and students reveal complex, multiple engagements with future-reckoning, including moments, often at the ambivalent margins of practice, where reparative futures-thinking offers a different way of engaging with the past, the present, and life after high school. • This paper explores reparative futures thinking for reimagining education beyond the modern school. • I explore this through my 2014–15 ethnography of a US public high school. • Through the story of seniors at Bronx High, I demonstrate how schooling is profoundly oriented towards particular anticipatory practices - namely, a modernist reckoning of the future. • However, the day-to-day actions reveal complexengagements with future-reckoning, including examples of reparative futures-thinking. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 caused unprecedented disruptions to public transport services. As such, this paper proposes a methodology for analyzing COVID-19 impact on public transport mobility. The proposed methodology includes: (1) a new unsupervised machine learning (UML) method, which utilizes a decoder-encoder architecture and a flow property-based learning objective function, to estimate the origin-destination (OD) flows of public transport systems from boarding-alighting data; and (2) a temporal-spatial analysis method to analyze OD flow change before and during COVID-19 to unveil its impact on mobility across time and space. The validation of the UML method showed that it achieved a coefficient of determination of 0.836 when estimating OD flows using boarding-alighting data. Upon the successful validation, the proposed methodology was implemented to analyze the impact of COVID-19 on the mobility of the New York City subway system. The implementation results indicate that (1) the rise in the number of weekly new COVID-19 cases intensified the impact on the public transport mobility, but not as strongly as public health interventions; and (2) the inflows to and outflows from the center of the city were more sensitive to the impact of COVID-19. • A new methodology for analyzing COVID-19 impact on public transport mobility. • It includes a proposed unsupervised ML method to estimate public transport system OD flows from boarding-alighting data. • It includes a temporal-spatial analysis method to analyze OD flow changes before and during COVID-19. • The proposed methodology was implemented in analyzing COVID-19 impact in the New York City area. • The methodology could support analyzing the impact of natural disasters on public transport mobility across time and space. [ABSTRACT FROM AUTHOR]