Everyday People Research Articles

Asking to Listen: Engaging Social Scientific Methods as a Listening Practice in Global Catholicism

Asking enables listening. This paper explores how the practice of asking, when enacted as an intentional social scientific process, can facilitate the synodal value of listening across the global Catholic Church. Drawing upon social science methodologies and evidence, it demonstrates that effective listening is not merely passive reception but proactive invitation to engage diverse or silenced perspectives. Systematic asking incorporates everyday people and experiences otherwise overlooked and creates space for difficult topics. Seeing listening as a practice of asking underscores the value of setting rules for engagement that promote a posture of reception that fosters trust and openness through humility, curiosity, and willingness to step into worlds different from one’s own. Embracing this mutual approach can prompt a more inclusive synodal process, enhancing the church’s ability to engage meaningfully with all in its midst.

Introduction to special issue: youth, rural places and marginalisation

ABSTRACT This Special Issue on Youth, Rural Places and Marginalisation, brings together nine papers from six countries – Australia, England, Denmark, Finland, Norway and Sweden – to explore young people's experiences of living in rural locations. We focused on rural youth for two main reasons: firstly, there are relatively few sociological studies of young people's experience of rural life and, secondly, academics and policymakers have tended to frame discussions about young people and rural places in negative terms. Together the papers here use a wide range of methods – quantitative and qualitative longitudinal approaches, questionnaire surveying, face-to-face and online qualitative interviews, ethnography, visual methods, ‘mobile probes', ‘walk-along' and ‘drive-along' interviews – in order to understand young people's everyday life. We were particularly interested in the stories of young people who appeared to resist ‘the mobility imperative' and chose to stay rather than leave their rural homes. Our introduction focuses on ‘rethinking concepts of staying'; ‘gender and the risks of staying' and ‘geographies of rural opportunities'. We conclude with a call for a sociological imagination of rural youth that avoids romanticizing narratives of ‘the rural idyll’ or which paints rural places and populations as backward or lacking.

Amazon vs the Amazon: Green Capitalist Imaginaries and the Death of Biodiversity

ABSTRACT Capitalist forces shape public consciousness and, by extension, how everyday people imagine environmental matters of concern. This article investigates the historical cycling of the three most influential green imaginaries of Western neoliberalism: biodiversity, ecosystem services, and climate change. Using the Amazon rainforest and Amazon.com as icons of the clash between capitalism and nature, we investigate how shifting neoliberal fashions create opportunities for capital to evacuate place consciousness from U.S. environmental politics. The destruction of place consciousness enables corporations to damage the biosphere while minimizing political interruption. We show how place-erasure works through historical cases linked to each phase: the sustainable tropical forest sourcing of The Body Shop and Ben & Jerry’s (1990s), compensatory wetland mitigation in the Midwest (2000s), and Amazon.com’s carbon offset program (2010s–present). In our discussion of these imaginaries or “waves,” we contend that the current mainstream neoliberal climate paradigm is the most pernicious as it diverts the public's attention to the sky and away from accelerating ecological violence on the ground.

Mental Health Conditions Between Neurodiversity and the Medical Model

Scholarship in neuroethics and related disciplines has long reflected on the value of different conceptual models of disability and impairment. While this theoretical work is valuable, centering the voices of people with mental health conditions in neuroethics research can help us better understand how such models apply in everyday people’s lives. Drawing on qualitative data from a study on mental health peer providers’ lived experiences of recovery, this paper will demonstrate that peers borrow from both a neurodiversity framework and the medical model of disability, though their feelings toward the two models were often complex and ambivalent. These findings advance neuroethics by indicating that future research and clinical practice should take a nuanced approach to responding to the needs of people with mental health conditions and turn to peers as experts, honoring their values and recognizing both the promise and pitfalls of living with a mental health condition.

Advanced trust classification in social networks using a triple generative adversarial network-assisted capsule network enhanced by gannet optimization

Over the past ten years, social networks (SN) have evolved into the primary infrastructure for people's everyday activities. Trust classification in social networks involves evaluating the trustworthiness of users or the information they share. Traditional trust classification methods often rely on explicit features, such as user ratings, reviews, and social ties. These methods utilize rule-based to assign trust scores for users or entities. However, they face challenges in capturing the exact nature of trust. In this manuscript, Advanced Trust Classification in Social Networks using a Triple Generative Adversarial Network-Assisted Capsule Network Enhanced by Gannet Optimization (Trust-TripleGAN-CapsNet-GOA) is proposed. In this manuscript, the feature vector has computed to every social network users pair after the raw data from the Sentiment140 dataset, is analysed. The membership of trust is then ranked according to five-class classifications by incorporating Tanimoto Trust Similarity coefficient. Then, Triple Generative Adversarial Network-Assisted Capsule Network (TripleGAN-CapsNet) is used to categorise the trust values of users. Finally, the weight parameters of TripleGAN-CapsNet is optimized by the Gannet Optimization Algorithm (GOA) to enhance the accuracy of the trust behaviour in SN. The proposed Trust-TripleGAN-CapsNet-GOA method attains 22.94 %, 32.36 % and 21.96 % higher accuracy, 30.27 %, 19.46 % and 12.39 %, higher precision when analyzed with the existing models, such as a method for trust mirroring assessment under social networks parameters with fuzzy system (Trust-SNP-FS), deep matrix factorization in social networks for trust-aware recommendation (Trust-DMF-SN) and towards time-aware context-aware deep trust prediction on the online social networks (TACADTrust-SN). The simulation outcomes exhibit that the proposed method attains 99 % accuracy.

Sentiment analysis of passenger feedback on U.S. airlines using machine learning classification methods

Twitter, a platform for micro-blogging, has contained as a novel information architecture. Everyday People worldwide publish about 200 million status messages, known as tweets. Twitter users express their opinions by posting concise text messages. Twitter data is useful for sentiment analysis and consumer feedback tweets. This study employed multi-class sentiment analysis to analyze tweets from 6 major US airlines (American, United, US Airways, Southwest, Delta and Virgin America). Airlines are essential for travel, and this study has helped people choose the best ones. Classification model with the lowest error rate could help airline companies improve their business by figuring out why information is being misclassified. This analysis of airline evaluations can help us identify good airlines and apply this model to our own journeys. This helps the airline identify its weaknesses so they can improve them. A technique of natural language processing (NLP) known as sentiment analysis (or opinion mining) classifies the tone of data as positive, negative, or neutral. The analysis was conducted with seven distinct classification strategies: Linear Discriminant Analysis, Quadratic Discriminant Analysis, Decision Tree, Random Forest, K-Nearest Neighbors, Gradient Boosting, and AdaBoost to utilize the split validation (80% as train data set, 20% as test data set) and 10 folds cross validation process. The suggested model demonstrates superior accuracy and efficiency compared to all others, achieving an accuracy score of 90.13% for the Random Forest with 10 folds cross validation approach. The project aims to utilize machine learning techniques to estimate the reasons for misclassified information since the lowest error rate means the airline sentiment provides less wrong prediction.

Sign language video to text conversion via optimised LSTM with improved motion estimation

ABSTRACT A method of communication for the deaf and the dumb is sign language (SL). Knowing SL allows speakers and listeners to converse effectively with deaf and dumb people. Yet, while they can acquire sign language (SL) to communicate with the dumb and the deaf, untrained persons are unable to speak with them. For such individuals, an SL to text system is more beneficial in enabling them to communicate more effectively with everyday people. To interact with the deaf and dumb, SL is a tactile gesture that employs the hands and eyes. This proposes a new model for translating SL video to text conversion or generation. Frame Conversion is the initial step, where the given input video is converted into frames. Subsequently, features considered are hierarchy of skeleton and Improved Motion estimation (ME). For generating the text, this work uses an optimised LSTM model, where training of weights is done by hybrid Combined Pelican and BES algorithm (CP-BES). Moreover, the mean value for dataset ISL-CSLTR has achieved the proposed method is 27.3%, 31.6%, 28.7%, 33.4%, 29.8%, 24.5%, 36.2%, and 34.8% greater than the conventional schemes like CNN, FSU-CNN, ASL – CNN, RNN, LSTM +POA, LSTM +ARCHOA, LSTM +HGS, LSTM +PRO and LSTM +BES.

Gentrification of Taste and Lifestyle: Shanghai as an Instagrammable Wanghong City

Gentrification parallels with massive demolition and displacement in Chinese cities in the post‐Reform era. The article studies the ways in which gentrification of cultural taste and lifestyle is played into state‐sponsored neoliberal space and class making. Focusing on Shanghai—China's gateway to modernity and leading Instagrammable Internet‐famous (wanghong) city—the article examines how the new Shanghai middle class becomes the patron of gentrification and how spatial consumption in the age of social media produces new forms of urban inauthenticity and social distinction. Through case studies of the transformation of two major historic Shanghai architectural forms—vernacular alleyway (longtang) houses and Western‐style garden villas (laoyangfang)—into wanghong scenes, the article argues that by “wanghongnizing” cities like Shanghai and gentrifying ordinary people's everyday life, the Chinese state strategically replaces collective memories of radical urbanism and displacement with propagation of an aestheticized middle‐class xiaokang society and romanticized “Chinese Dream.”

Young people's experiences of addiction to nicotine vaping products: A qualitative analysis from Aotearoa New Zealand.

Young people who use nicotine-containing electronic cigarettes, or 'vapes', risk becoming addicted to these products. While several studies document dependency symptoms, few report in-depth qualitative analyses of addiction. We explored experiences of self-reported vaping addiction using in-depth interviews with 22 young people aged 16-20 years who vaped and lived in Aotearoa New Zealand. Our semi-structured interview guide probed participants' early experiences and how they progressed from experimentation to addiction and explored how addiction affected their perceptions and daily routines. We used an inductive reflexive thematic analysis approach to interpret the data. Vaping's pervasiveness piqued participants' curiosity and encouraged trial. Most transitioned from experimentation to addiction within a couple of months; while a minority described a slower progression, nearly all felt irritable, angry or uncomfortable if they had to delay vaping. Intense cravings disrupted school and work routines and dictated how they spent their time. Many deeply regretted vaping and some suffered shame and embarrassment. These participants saw vaping as a threat to the well-being of younger youth, which they tried to shield from addiction. We go beyond earlier studies by probing the burden vaping comes to represent, offering new insights into young people's everyday experiences of vaping addiction. In addition to informing health promotion campaigns, our findings could inform policy directions. Understanding the speed with which addiction can occur, its impact on daily life, and the considerable regret many felt could help inform a more strategic and sorely needed approach to reducing youth vaping.

Social Media Use and Sleep Quality Among Secondary School Students in Aseer Region: A Cross-Sectional Study.

Use of different social media platforms has increased radically over the past decade, emerging as an important part of adolescents and young people's everyday life. This might exert potential adverse effects on sleep quality and daytime performance of young adults. To assess the relation between use of social media platforms and sleep quality among public secondary school students. A cross-sectional study was conducted on 961 students in Aseer region, Saudi Arabia. Students were asked to fill in a structured interview questionnaire covering personal data, pattern of social media use, sleep quality using The Pittsburgh Sleep Quality Index (PSQI) and their mental health status using the depression, anxiety and stress scale (DASS-21). Students' ages ranged from 15 to 20 years with a mean age of 16.7 ± 2.1 years old. A total of 570 (59.3%) students were females. Tiktok (80%), Snapchat (77.9%), Instagram (63.8%) and YouTube (58.8%) were the most reported platforms used. Regarding their sleep quality, 34.7% of students were poor sleepers. TikTok use (OR 1.33, 95% CI 1.01-1.77), hours spent on social media (OR 1.26, 95% CI 1.16-1.37) and having moderate to severe depressive symptoms (OR 1.69, 95% CI 1.19-2.40) were significant independent predictors of poor sleep among the studied sample. The present study emphasized the association between prolonged use of social media and poor sleep quality among Saudi adolescents. Awareness and behavioral change strategies and activities concerning the drawbacks of poor sleep and proper use of social media are urgently called for to control mental and physical health consequences of poor sleep and social media addiction.

One Village in Subcarpathia: Census Data from Hungary and Czechoslovakia

Abstract Census reports—mainly the questions concerning language and nationality, as well as other similar inquiries—can be very useful to think about the everyday people of Central and Eastern Europe, in this case specifically about Subcarpathia. This examination of the census data from 1910, 1921, 1930, and 1941 (mainly from 1910 and 1930) can provide insights into the story of the Jewish (as well as non-Jewish) community of the town of Bilke. Such an examination can complicate our understanding of Subcarpathia and Central and Eastern Europe, as well as modernity in general, and at the same time it can clarify our understanding of these same regions and movements. In this case the censuses concerning Bilke allow us to view a world that is not always in focus.

The Impact of Mouth Masks on Oral Hygiene Status, Seeking Dental Care, Esthetics, and Temporomandibular Joint Disturbances Among the Adult Population in Nellore District: A Cross-sectional Study

Abstract Background: Despite preventing infection transmission, because of its prolonged use, the impact of masks on social life, behavior, and oral hygiene status and habits of everyday people are still unknown. The knowledge of the changes in patients’ esthetic complaints, perceptions, and habits with the use of masks is essential for clinicians. Aim and Objectives: The aim of the study was to evaluate the impact of the continuous use of face masks on oral hygiene habits; dental, smile and oral conditions, and self-perception; current reasons to seek dental care; and the importance attributed to teeth and smile esthetics among the adult population (students/employees) who wear masks 6 h per day for 6 months from August 30, 2021 to February 28, 2022. Materials and Methods: An electronic survey (Google Forms) was used to generate a web-based platform for the responses in the form of a questionnaire. A link to the structured questionnaire was posted on Facebook, Instagram, Twitter, and WhatsApp. The study considered all the individuals willing to participate, and the subjects were informed about the survey’s objectives. Data Analysis Method: The recorded data were analyzed using the SPSS software. Proportions were compared using the Chi-square test. P < 0.05 was selected to denote statistical significance with the confidence level, and the significance level was set at 95% and 5%, respectively. Conclusion: The study gave the current status of participants and their motivational levels toward seeking dental treatment, suggesting further studies in planning preventive strategies for the participants.

The Truth and the Pain: A Reading of Edouard Kayihura’s <i>Inside the Hotel Rwanda</i> and Marie Béatrice Umutesi’s <i>Surviving the Slaughter</i>

Literary realism focuses on everyday people, issues, characters, settings and situations that are real. Some writers engage realism to document their real-life experiences. The readers as well tend to gain access to real life events as vivid as the writers can recollect them. Fictitious approaches are avoided completely in these narrations. This is done to ensure that the readers can identify with the stories being narrated. Hence, the 1994 genocide has been the major focus of contemporary Rwanda prose narratives. They project the experiences of the people before, during and after the genocide. Also, some authors document their experiences as suggested by their therapists, because it usually helps as one of the coping mechanisms for trauma. This study delves into the analysis of two post-genocide prose narratives. It adopts the use of postcolonial and trauma theories as the tools for conceptualizing, understanding and interpretation of these prose narratives. Marie Béatrice Umutesi’s <i>Surviving the Slaughter: The ordeal of a Rwandan Refugee in Zaire </i>and Edouard Kayihura’s<i> Inside the Hotel Rwanda: The Surprising True Story and Why It Matters Today </i>are autobiographies, they depict the causes of the genocide, the outcomes, specifically on the victims and hopefully the solutions. Edouard Kayihura suffers harrowing experiences of perpetual fear, oppression and extortion inside the Hotel des Mille Collines, this is his own truth, debunking the inaccuracies of the movie Hotel Rwanda. While, Marie Béatrice Umutesi, a Hutu woman witnesses and experiences inexplicable brutality and hardship. She endures the pains as she journeys towards safety. This study interrogates the contributions of political hegemony and identity crises to varying degrees of trauma and explains that the experiences and pains of these writers are factual. It also establishes that these prose narratives serve dual purposes of correcting a false claim and projecting the pain of a Hutu woman, a unique diversion from the popular focus on the Tutsis.

Leveraging multiple digital footprint datasets to predict racial, sex-based, and sexual-orientation bias across US states

Introduction & BackgroundRacial, gender, and sexual-orientation biases are pervasive throughout society. Importantly, modern digitally oriented datasets can elucidate important societal variables and potential solutions. One contemporary theory that attempts to explain these biases is parasite-stress: an evolutionary psychology hypothesis suggesting that increased infectious diseases rates increase out-group biases. We present preliminary findings that suggest that disease rates are a meaningful geospatial predictor of multiple biases. Objectives & ApproachWe explored biases using geospatial analyses throughout multiple datasets based on US participants: Project Implicit, American National Election Studies (ANES), Google Trends, and Twitter/X. We included state-based variables to compare between states and assess the most important environmental-level predictors of biases. We built generalised linear and linear mixed-effect models and general linear models. Within Project implicit (n > 3,000,000) and ANES datasets (n > 30,000), we assessed racial and sexual-orientation biases via explicit and implicit measures. For Google Trends and Twitter/X datasets, we assessed racial and sex-based biases via search and tweet-per-state scores. To analyse the biases, we included environmental-level variables, e.g., infectious disease rates (developed by Thornhill and Fincher in 2014), and individual-level variables, e.g., political orientation. Relevance to Digital FootprintsThese preliminary findings analyse everyday people’s online behaviour including volunteered surveys, searches and posts. We attempt to address the pressing societal issue of bias by leveraging modern datasets. Our primary goal is to aid policy makers by recommending cost-effective solutions that can improve several factors of the population’s quality of life. ResultsWe find that the most consistently significant predictor of racial bias is infectious disease rates. When leveraging Google Trends data including anti-women terminology, infectious disease rates and population density are consistent predictors of bias. Finally, we find preliminary results suggesting that increased levels of infectious diseases increases homophobic bias. Conclusions & ImplicationsOverall, we find that as infectious disease rates increase in a state, the level of racial and sexist bias significantly increases. Consistent with parasite-stress theory, we argue that focusing on reducing infectious disease rates in an area can have a plethora of benefits including improving physical and mental health and reducing biases that damage society.

High economic inequality is linked to greater moralization.

Throughout the 21st century, economic inequality is predicted to increase as we face new challenges, from changes in the technological landscape to the growing climate crisis. It is crucial we understand how these changes in inequality may affect how people think and behave. We propose that economic inequality threatens the social fabric of society, in turn increasing moralization-that is, the greater tendency to employ or emphasize morality in everyday life-as an attempt to restore order and control. Using longitudinal data from X, formerly known as Twitter, our first study demonstrates that high economic inequality is associated with greater use of moral language online (e.g. the use of words such as "disgust", "hurt", and "respect'). Study 2 then examined data from 41 regions around the world, generally showing that higher inequality has a small association with harsher moral judgments of people's everyday actions. Together these findings demonstrate that economic inequality is linked to the tendency to see the world through a moral lens.

Fake Indian Currency Detection

The proliferation of counterfeit currency poses a significant threat to both individuals and the national economy. While existing fake currency detection tools are primarily accessible to banks and large enterprises, everyday people and small businesses remain susceptible. Thus, this project aims to delve into the security features of Indian currency and develop a software solution leveraging advanced image processing and computer vision techniques to detect and neutralize counterfeit notes. Counterfeiting currency poses a genuine menace to both the populace's well-being and the nation's economic stability. Although counterfeit currency detection tools exist, their accessibility is typically confined to banking institutions and corporate entities, leaving ordinary citizens and small enterprises susceptible to fraud. Thus, this project endeavours to examine the diverse security attributes of Indian currency and subsequently craft a software-driven apparatus capable of discerning and nullifying counterfeit Indian currency through sophisticated image processing and computer vision methodologies. Notably, this currency authentication system will be meticulously crafted using the Python programming language within the Jupyter Notebook framework.

Água negra (black water) and overwhelming details: For more-than-nexus approaches to global water–energy–food challenges

This paper advances multidisciplinary research, policy, education and activisms which cohere around the concept of the ‘water–energy–food (W–E–F) nexus’ via an evidence-led critique of normative forms of nexus-thinking which draws upon research with 3705 diverse young people's (aged 10–24 years) W–E–F experiences in SE Brazil. We consider how the neat, cool, ostensibly authoritative buzzword style of W–E–F nexus-thinking is radically unsettled – and sometimes conceptually-critically overwhelmed – via encounters with social scientific data in practice. In particular, the paper presents two interlinked analyses of data relating to young people's everyday engagements with water resources. First, we present a quantitative analysis of young people's everyday participation with/in water resources, highlighting diversities and inequities in relation to age, gender, ethnicity and social class, among other modes of social–cultural heterogeneity and intersectionality. Second, we present a qualitative narration of young people's water-related anxieties, evidencing their intimate everyday interrelations with watery materialities and insecurities – ‘black water’, ‘muddy water’, ‘shit water’ and all. In so doing, we advance an argument for what we term more-than-nexus-thinking: i.e., forms of research, theory and practice which value the apparent conceptual-ethical clarity and interoperability of nexus-thinking, whilst actively thinking-with complexities and deeply-affecting lived experiences of W–E–F in everyday spaces.

User-centered circular value propositions – approaches in practice and research

Circular value propositions enable companies to build business models based on value preservation and circular resource flows. Circular value propositions also allow people to live more sustainably by facilitating increased utilization and resource efficiency. However, despite potential, transitions to circular business models remain low. One reason may be that circular value propositions are less attractive because they are often not developed with a user-centered approach and thus fail to meet people's everyday needs. Through interviews with 13 companies and a literature study, this paper explores how companies consider user needs and involve users during development of circular value propositions. It also identifies conditions and actions that aid development of attractive circular offers. The findings are synthesized in a framework describing six enabling conditions and a definition of user-centered circular value propositions useful for circular economy practice and research.

The “Vicious Circle of addictive Social Media Use and Mental Health” Model

Social media use (SMU) is a significant part of many people's everyday life. Research around the globe describes an increase of addictive SMU tendencies since the COVID-19 outbreak. The present work combines available findings in the “Vicious Circle of addictive Social Media Use and Mental Health” model to explain how social media (SM) activity can contribute to the development of addictive tendencies, which consequences they have for mental health, and how to prevent them. Following the model, the interplay between the risk factors negative experiences caused by daily hassles and by unexpected global and traumatic events, SMU (dimension “quality”), and SM flow can directly contribute to addictive SMU through the “vicious circle”. Time spent on SMU (dimension “quantity”), symptoms of depression and anxiety, and the personality trait narcissism contribute to the circle as moderators. Symptoms of stress, insomnia, and suicide-related outcomes are described as potential consequences of addictive SMU. Based on longitudinal intervention studies, a conscious reduction of SMU time and an increase of physical activity, as well as positive mental health and mindfulness are identified as protective factors that reduce the risk of addictive tendencies. The model contributes to a better understanding of addictive SMU. Implications of the model for future research and praxis, specifically for mental health programs and therapeutic treatment are discussed.

Resisting and Reclaiming: Squatting as Contentious Urban Politics in the U.S.

Abstract Squatting as contentious politics has been well studied globally, expanding knowledge of how everyday people resist injustices, strive to remake cities, and respond to local/regional conditions. These histories and contemporary struggles have largely been overlooked in the U.S. This article uses qualitative data to compare three recent cases of organized housing occupations in Detroit (2011), Oakland (2019), and Philadelphia (2020) by mothers of color with their children, to better understand how this form of global urban politics manifests in the U.S. Using this comparison, we identify important dimensions that have shaped these three cases of contentious politics and their outcomes, including differences in goals, tactics, and socio-spatial context. We also uncover the diagnostic and prognostic frames reflected in each case: despite common legal violations, each case purposefully diagnoses locally-rooted housing problems and suggests different property-relations as solutions. We find that each case varies in terms of what kind of property squatters target, how these spaces reflect broader structural problems in the U.S. housing market, and what kind of property-relations they envision with these occupations. In turn, our findings also advance understanding of this global urban politics by showing how squatting efforts may dovetail with place-based legacies, such as racial segregation and settler colonialism in the U.S. Researchers have long attended to organized housing struggles in their varied manifestations, but by foregrounding resistance to and reclaiming of property by squatters, we draw out understudied problems and possibilities related to land and housing occupations that are subverted within broader housing studies.