Human Choice Research Articles

Human choice dynamics when the grass looks greener

Human choice dynamics when the grass looks greener

Analysing the Shema in the Light of the Neurobiology of Virtue

Moses’s great command, known to us as the Shema, taught the Jewish people that the great goal of one’s entire being must be love of God but that this outcome can be easily obscured in the face of distractions and competing pleasures. The task he describes may be understood as an exhortation to live and teach moral virtues, informed by faith in God: self-management of impulses and conditionings so that we can think clearly about the goals we pursue and love wisely. This study offers an analysis of the Shema through the lens of neurobiology. This approach supports a literal interpretation of the Shema to the extent that it provides a neurobiological explanation for the role of memory, positive emotion, and curated attention in establishing positive convictions and holding to them in the face of contrary stimuli. In doing so, it demonstrates that such applications of neurobiology can enrich our understanding of human behaviour because they offer insights into the internal dynamics at work in human choices and motivations, and into the need for coherence between our emotional responses and our convictions.

Environmental Metrics of World Cuisine Recipes' Plant-Based Substitutes: Greenhouse Gas Emissions, Water Footprint, and Land Use

Introduction/Objective: Evidence has shown that consuming plant-based foods instead of animal-based foods has positive effects on human and planet health. The current study aimed to compare animal-based recipes (ABRs) and plant-based recipes (PBRs) nutritionally and environmentally. Methods: Plant-based recipes (adapted from animal-based recipes) were obtained from the “Vegan Nutrition with Healthy and Delicious Recipes” book for inclusion in this study. Nutrient components, including energy content, energy density (ED), macro and micronutrient profiles, such as environmental metrics, which are greenhouse gas emissions (GHGE), water footprint (WF), and land use (LU), were calculated and compared between animal-based and plant-based recipes. Results: While dietary fiber and insoluble fiber were higher, protein, total fat, saturated fatty acids, monounsaturated fatty acids, vitamin B12, and zinc contents were lower in PBRs, compared to ABRs. With exceptions (magnolia, muffins, and vegan souffle), medians GHGS, WF, and LU of PBRs were lower than those of ABRs(). Plant-based hamburgers and meatballs, whose main ingredients were fresh vegetables, had the lowest environmental impact. Conclusion: It is well known that human diet and food choices are among the main components that contribute to environmental impact. Although the ecological footprints of foods and recipes are essential in the diet, their nutrient densities should not be overlooked. Enriching the nutritional values of the foods used in PBRs may improve their dietary values. In addition, it should also be forgotten that using high amounts of non-nutritious foods, such as sugar, in PBRs due to their low ecological impact is incorrect.

An event-based account of conformity: evidence from attention manipulations targeting event-file encoding and retrieval

ABSTRACT Previous findings have raised doubt in whether comparable conformity effects can be obtained for information from humans and computers or other systems of little or no social importance. In the present study, we compared the impact of “other choices” (i.e. choices of another agent that did or did not match the participant’s initial choices) of humans and computers on preferences of participants for one of two pictures. In Experiment 1, we found conformity effects only when the other choices came from humans. In Experiment 2, we manipulated the attention allocated to encoding picture-choice combinations by means of a secondary go/nogo task. Conformity effects were found for humans and computers if the secondary task did not require a response. In Experiment 3, we manipulated the attention allocated to retrieving picture-choice combinations, which resulted in conformity effects for all conditions. Taken altogether, our findings suggest that conformity effects can be obtained for “computerized” informational sources under attentional conditions that reduce the specificity of encoding or the selectivity of retrieving event files.

News Diversity Under Algorithms: The Effects of Pre-Selected and Self-Selected Personalization on Chinese TikTok (Douyin)

Existing journalism scholarship has raised the concern of people’s limited news exposure on algorithm-driven social media. Using a series of novel agent-based testing (ABT) experiments, this study collects data from Douyin (the Chinese version of TikTok) and attempts to capture the dynamics of news diversity with complex interaction of algorithm and human agency. Results indicate that the personalized news consumption on Douyin is more diverse in news categories than it would be when occurs by chance. Additionally, algorithmic decisions more than human choices promote exposure to diverse topics in news consumption. We have further quantified whether users can obtain a more balanced news consumption through modifying their interest scope and tendency to engage with unmatched content. These findings are crucial for us to grasp how algorithms shapes users’ news consumption and determine the effectiveness human users can adjust their exposure to a more diverse, opinion-challenging news environment.

Attraction effect in crowded decision spaces: exploring the impact of decoys in choices among numerous options

ABSTRACT Human choices are context-dependent, and options evaluation is biased by the quality and quantity of available alternatives. In the attraction effect, dominated decoys have proven effective in shifting preferences in numerous experiments, yet its relevance in real-life choices remains disputed. Part of the problem lies in the differences between laboratory settings and realistic scenarios: in the lab, participants are tested on ternary choices; in real life, consumers face choices among many options, and interactions with other context effects are frequent. We present two experiments investigating how these factors modulate the attraction effect: we manipulate the number of decoys (study1), and the number of available options (study2). Findings suggest that: (i) the attraction effect remains significant in larger sets; (ii) two decoys are more effective than one, but (iii) adding more undermines the effect; (iv) compromise options have a dampening influence on decoys, making them ineffective at targeting the intermediate option.

Proactive Assignment Strategy With Human Choice Models for Boosting Pooled Rideshare Service

Proactive Assignment Strategy With Human Choice Models for Boosting Pooled Rideshare Service

The Influence of Company Reputation, Service Quality and Directors’ Tax Knowledge on Tax Compliance Behaviour of Malaysian Large Companies

Tax compliance behaviour among Malaysian large companies is a crucial area of investigation, particularly considering the significant contribution of corporate taxes to national revenue. Researchers have suggested that tax compliance behaviour of large companies in Malaysia is likely influenced by their surrounding compliance practices. However, to date, no published studies have explored the relationship between company reputation, service quality, and directors’ tax knowledge, and corporate tax compliance behavior, which has led to this research. For the purpose of this study, the Behavioural Decision Theory (BDT) was employed to explain optimality in decision-making, judgment, and human choice, in tax compliance behaviour. An online questionnaire was distributed to 500 Malaysian large companies in Peninsular Malaysia through the systematic random sampling method, of which 161 companies (32.2%) responded. The data was analysed using Partial Least Squares-Structural Equation Modelling (PLS-SEM). The results reveal a significantly positive relationship between directors’ tax knowledge and large companies’ tax compliance behaviour. On the other hand, negative relationships are documented for company reputation and service quality, and tax compliance behaviour. The results, however, are not significant. This study recommends that the tax knowledge of company directors is important to ensure companies comply with the tax law voluntarily. Hence, training programmes for directors should be conducted regularly so as to assure their knowledge is current, ultimately promoting ethical decision-making, i.e., minimising tax evasion and misreporting.

Postingestive reward acts through behavioral reinforcement and is conserved in obesity and after bariatric surgery.

Postingestive nutrient stimulation conditions food preferences through striatal dopamine and may be associated with blunted brain responses in obesity. In a cross-sectional study, we tested flavor-nutrient conditioning (FNC) with maltodextrin-enriched yogurt, with maltodextrin previously optimized for concentration and dextrose equivalents (n = 57), and to mask texture cues (n = 102). After conditioning, healthy volunteers (n = 52) increased preference for maltodextrin-paired (+102 kcal, CS+), relative to control (+1.8 kcal, CS-) flavors, as assessed according to intake, but not pleasantness. In a clinical study (n = 61), behavioral conditioning without effects on pleasantness was confirmed across pre-bariatric candidates with obesity, weight-stable post-surgery patients, and healthy controls, without significant differences between groups. Striatal dopamine D2-like receptor (DD2lR) availability, assessed with [123I]IBZM SPECT, was reduced in the obesity group and strongly correlated with conditioning strength and a measure of restrained eating in patients with gastric bypass. These results show that postingestive nutrient stimulation influences human food choices through behavioral reinforcement, and is conserved in obesity and after bariatric surgery. Trial Registration: ISRCTN17965026: Dopaminergic neurotransmission in dietary learning and obesity.

Capitalist Dreams, Posthuman Nightmares: AI and the Neoliberal Reordering of Humanity in Ian McEwan’s Machines Like Me and Kazuo Ishiguro’s Klara and the Sun

ABSTRACT This article examines the portrayal of AI in Ian McEwan’s Machines Like Me and Kazuo Ishiguro’s Klara and the Sun through Deleuze and Guattari’s framework of the twofold movement of capitalist deterritorialization and reterritorialization. It highlights how neoliberal capitalism leverages AI to create new markets, reinforces social inequalities, and ultimately alienates individuals from their communities and identities through processes of deterritorialization and reterritorialization. The commercialization of AI reflects capitalist dynamics, disrupts social interactions, and challenges human moral choices. The analysis reveals how AI contributes to technological divides, human displacement, and the creation of new territories of alienation and economic disparities. Both novels serve as cautionary tales, depicting dystopian futures where AI-driven automation leads to widespread unemployment and social unrest, highlighting the potential for AI to exacerbate existing inequalities. The novels expose the profit-driven promise of technological progress – particularly the allure of increased productivity and efficiency – and its impact on society. This paper emphasizes the urgent need for a critical reflection on the ethical and social implications of AI to ensure a more equitable and human-centered technological future.

Development Strategy for Village Owned Enterprises: A Case Study in Majalengka Regency, West Jawa Province, Indonesia

Village-Owned organizations (BUMDes) are one of the strategic units in empowering village communities. South Maja BUMDes is one of the BUMDes which has several commercial enterprise units inside it and up to now, it has survived. This studies objectives to determine the internal and outside factors of BUMDes South Maja and to decide the strategic priorities that want to be taken for BUMDes development. The research technique used became quantitative descriptive research via taking 33 respondents. The evaluation finished is a SWOT analysis preceded with the aid of an hobby degree analysis. The effects of the IFE matrix analysis are the primary power in control which does now not involve many human beings, making operations and choice making easier. meanwhile, the principle weak spot is that there may be no era that can facilitate communique among administrators, managers and consumers. The outcomes of the IE matrix show that BUMDes South Maja is in cellular or box which has function presents an outline of the country of BUMDes South Maja which is in a maintain and maintain circumstance.

Investigating day-to-day route choices based on multi-scenario laboratory experiments, Part II: Route-dependent attraction-based stochastic process model

Laboratory experiments are one of the important means used to investigate travel choice behavior under strategic uncertainty. Many experiment-based studies have shown that the Nash equilibrium can predict aggregated route choices, while the fluctuations, whose mechanisms are still unclear, continue to exist until the end. To understand the fluctuations, this paper proposes a route-dependent attraction-based stochastic process model, which shares exactly the same behavioral foundation introduced in Part I of the study (Qi et al., 2023), i.e., route-dependent inertia and route-dependent preference. The model predictions are carefully compared with the experimental observations obtained from the congestible parallel-route laboratory experiments containing 312 subjects and eight decision-making scenarios (Qi et al., 2023). The results show that the proposed stochastic process model can precisely reproduce the random oscillations both in terms of flow switching and route flow evolution. Subsequently, an approximated model is developed to enhance the efficiency in evaluating the equilibrium distribution, providing a practical tool to evaluate the impacts of transportation policies in both long- and short-term runs. To the best of our knowledge, this paper is the first attempt to model and explain experimental phenomena by introducing stochastic process theories, as well as a successful example of applying experimental economics methodology to improve our understanding of human travel choice behavior.

Mitigating Exposure Bias in Recommender Systems—A Comparative Analysis of Discrete Choice Models

When implicit feedback recommender systems expose users to items, they influence the users’ choices and, consequently, their own future recommendations. This effect is known as exposure bias, and it can cause undesired effects such as filter bubbles and echo chambers. Previous research has used multinomial logit models to reduce exposure bias through over-exposure on synthesized data. We hypothesized that these findings hold true for human choice data to a limited degree and that advanced discrete choice models further reduced bias. We also investigated whether the composition of choice sets can cause exposure bias. In pursuing our research questions, we collected partially biased human choices in a controlled online user study. In two experiments, we evaluated how discrete choice–based recommender systems and baselines react to over-exposure and to over- and under-competitive choice sets. Our results confirmed that leveraging choice set information mitigates exposure bias. The multinomial logit model reduced exposure bias, comparably with the other discrete choice models. Choice set competitiveness biased the models that did not consider choice alternatives. Our findings suggest that discrete choice models are highly effective at mitigating exposure bias in recommender systems and that existing recommender systems may suffer more exposure bias than previously thought.

The Effect of Sexual Orientation on Preferences for Altruism in Human Mate Choice

The Effect of Sexual Orientation on Preferences for Altruism in Human Mate Choice

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data

BackgroundThe preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potential of machine learning models for understanding the connections between soil and biological phenotypes. We investigate an integrative framework performing accurate machine learning-based prediction of plant performance from biological, chemical, and physical properties of the soil via two models: random forest and Bayesian neural network.ResultsPrediction improves when we add environmental features, such as soil properties and microbial density, along with microbiome data. Different preprocessing strategies show that human decisions significantly impact predictive performance. We show that the naive total sum scaling normalization that is commonly used in microbiome research is one of the optimal strategies to maximize predictive power. Also, we find that accurately defined labels are more important than normalization, taxonomic level, or model characteristics. ML performance is limited when humans can’t classify samples accurately. Lastly, we provide domain scientists via a full model selection decision tree to identify the human choices that optimize model prediction power.ConclusionsOur study highlights the importance of incorporating diverse environmental features and careful data preprocessing in enhancing the predictive power of machine learning models for soil and biological phenotype connections. This approach can significantly contribute to advancing agricultural practices and soil health management.

Development of Home Economics Lesson Plans Aimed at Enhancing Digital Literacy: Focusing on the 2022 Revised Home Economics Curriculum for Clothing Life Field

The purpose of this study is to develop a lesson plans for clothing life that will improve digital literacy competencies at home economics education. For this purpose, lesson plans were developed that reflects the three components of digital literacy, content and digital technologies. The lesson plans are divided into five topics: self-image expression, clothing materials and care practices, sustainable clothing planning, resource cycles and human choices, and culture and future change in the clothing life-cycle. Each of these themes uses digital resources to develop digital literacy abilities in accordance with the STPCR's instructional stages. Gané's goal statement is used to express the general goal of each topic, which is then followed by particular objectives to achieve it. The lesson plans have the following characteristics: 1) Using digital tools to improve digital literacy skills; 2) Understanding and applying the value of resource circulation and sustainability; 3) Increasing class engagement and learning motivation; and 4)Fostering collaboration and critical thinking abilities through peer assessment and feedback. One weakness of this study is that the lessons learned were not used in the field. However, a limitation of this study is that the developed lesson plans have not been applied in the field. Therefore, it is necessary to verify the effectiveness of the lesson-plan in enhancing digital literacy skills through field application. Further research is needed to identify optimized digital tools and platforms and provide practical utilization strategies for educators.

Faecal microbiota composition and impulsivity in a cohort of older adults with metabolic syndrome

Impulsivity is an important determinant of human behaviour, affecting self-control, reasonable thinking and food choices. Recent evidence suggests a role for gut microbiota in human behaviour, but the relationship between gut microbiota and impulsive behaviours remains largely unexplored. To address this knowledge gap, the present study aims to explore the associations between faecal microbiota composition with trait and behavioural impulsivity, in a subcohort of the PREDIMED-Plus trial, including older adults presenting overweight/obesity. Fecal samples (n = 231) were profiled for their microbiota composition using 16 S rRNA amplicon sequencing and impulsivity was determined through four different assessments. Adherence to different dietary patterns was estimated through questionnaires. Beta diversity analyses showed a significant association with the Conner’s Performance Test (CPT) in multivariate-adjusted models, and, in total, 13 bacterial genera associated with CPT. Erysipelotrichaceae UCG 003 showed the highest association with CPT and known butyrate producers such as Butyricicoccus spp., Roseburia spp., and Eubacterium hallii were among the identified bacteria. The bacteria Lachnospiraceae UCG 001, Anaerostipes and Blautia were associated with CPT and also the adherence to healthy and unhealthy plant-based diets. In addition, functional analysis showed a significant negative association between the CPT and the glucuronate and galacturonate metabolic pathways. From the other impulsivity assessments, two more associations were identified, for the genus Phascolarctobacterium with the Stroop test, and the genus Lachnospiraceae GAG 54 with the positive urgency subscore of UPPS-P Impulsive Behaviour Scale. Overall, our findings suggest potential links between the faecal microbiota composition and function with behavioural impulsive inattention as determined by the CPT.

Hierarchical glycolytic pathways control the carbohydrate utilization regulator in human gut Bacteroides.

Human dietary choices control the gut microbiome. Industrialized populations consume abundant glucose and fructose, resulting in microbe-dependent intestinal disorders. Simple sugars inhibit the carbohydrate utilization regulator (Cur), a transcription factor in the prominent gut bacterial phylum, Bacteroidetes. Cur encodes products necessary for carbohydrate utilization, host immunomodulation, and intestinal colonization. Here, we demonstrate how simple sugars decrease Cur activity in the mammalian gut. Our findings in two Bacteroides species show that ATP-dependent fructose-1,6-bisphosphate (FBP) synthesis is necessary for glucose or fructose to inhibit Cur, but dispensable for growth because of an essential pyrophosphate (PPi)-dependent enzyme. Furthermore, we show that ATP-dependent FBP synthesis is required to regulate Cur in the gut but does not contribute to fitness when cur is absent, indicating PPi is sufficient to drive glycolysis in these bacteria. Our findings reveal how sugar-rich diets inhibit Cur, thereby disrupting Bacteroides fitness and diminishing products that are beneficial to the host.

Teen parent trap? The education and labor implications of motherhood and fatherhood during the transition from adolescence to adulthood in Cebu, the Philippines

For both males and females, adolescent parenthood can affect human capital investments and labor market choices during the transition from adolescence to adulthood. However, only scant evidence exists on the educational and labor implications of adolescent motherhood in developing countries and there is none on adolescent fatherhood. Using fixed effects, linear, and hazard models on a matched sample, we examine the association between early parenthood and education and labor market outcomes for a cohort of adolescents using longitudinal data from Cebu, the Philippines. While we find that early parenthood is associated with poorer educational outcomes for both teen mothers and fathers, the association is stronger for mothers. Upon becoming parents, labor market participation reduces for teen mothers but increases for teen fathers. Teen parents (both mothers and fathers) face a higher hazard of leaving school early, but teen fathers exhibit a substantially higher hazard of entering the labor market earlier. In young adulthood, conditional on working, both teen mothers and fathers are more likely to be informally employed. This paper highlights the potential gains from delaying first childbirth for adolescent males and females.

Displaying Altruism as a Sexual Signal in Human Mate Choice is an Adaptation – An Interdisciplinary Overview of the Evidence

Numerous studies in humans have shown that altruism may influence mate choice decisions, highlighting its potential role as a sexual signal. Whether using altruism as a signal is an adaptation, however, remains largely unresolved. In this review, we aim to investigate the adaptive nature of altruism as a sexual signal by constructing a comprehensive nomological network of evidence. Drawing upon interdisciplinary scientific modes of evidence (psychology, medicine, physiology, genetics, phylogenetics, hunter-gatherer studies, cross-cultural studies, and theoretical studies), our analysis reveals an extensive breadth of evidence across the various disciplines supporting the hypothesis that altruism is an adaptive sexual signal. However, only the psychological evidence demonstrates substantial depth. Other fields exhibit a lack of variation in research methods or a minimal amount of studies, limiting the strength of their respective contributions. Despite these limitations, there is still sufficient support for the nomological network. Based on the evidence of the various disciplines, we conclude that there is sufficient support that altruism as a sexual signal is an adaptation. We provide considerations for future research that would expand the scope of the evidentiary depth across the various disciplines, which would strengthen our understanding of the role of sexual selection in human altruism.