Human Choice Research Articles

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

AbstractNumerous 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.

Melting glaciers, emerging pandemics?

The world contains over 198,000 to 200,000 glaciers, covering in total over 726,000 square kilometers of Earth’s surface (Davies; “Glacier Quick Facts”). The repetitive cycle of snowfall forming layers and compressing into ice sheets over the course of centuries has allowed the formation of these unique, massive masses of ice. Apart from being huge reservoirs of water, glaciers are also hosts of many interconnected microbiomes, fostering active and dormant bacteria, fungi, viruses and other extremophiles. During the Last Glacial Maximum (LGM), or the peak of the ice age around 23,000-19,000 years ago, the sea surface temperature was at its lowest accompanied by low atmospheric Carbon Dioxide (CO2) concentration (“How Does Present Glacier Extent”; Quamar et al.). This was when glaciers covered over 32% of Earth’s total surface. However, today, glaciers account for just around 10% of land (“Glacier Quick Facts”). The rise of human choices, especially our indulgence in activities like industrialisation, consumerism and wastage have contributed to the emission of greenhouse gasses, which has in turn led to global warming. A consequence of this phenomenon is the melting of glaciers. Melting glaciers not only results in the release of water and rising sea levels, but also the unveiling of previously trapped microbiomes. This raised the hypothesis that melting glaciers, and other sections of the cryosphere can expose previously frozen, potentially pandemic-causing pathogens to the world. This descriptive research paper will serve the purpose of encapsulating existing research regarding whether the disintegration of the cryosphere can cause pandemics.

Exploring the decision-making process in model development: focus on the Arctic snowpack

Abstract. The Arctic poses many challenges for Earth system and snow physics models, which are commonly unable to simulate crucial Arctic snowpack processes,such as vapour gradients and rain-on-snow-induced ice layers. These limitations raise concerns about the current understanding of Arctic warming and its impact on biodiversity, livelihoods, permafrost, and the global carbon budget. Recognizing that models are shaped by human choices, 18 Arctic researchers were interviewed to delve into the decision-making process behind model construction. Although data availability, issues of scale, internal model consistency, and historical and numerical model legacies were cited as obstacles to developing an Arctic snowpack model, no opinion was unanimous. Divergences were not merely scientific disagreements about the Arctic snowpack but reflected the broader research context. Inadequate and insufficient resources, partly driven by short-term priorities dominating research landscapes, impeded progress. Nevertheless, modellers were found to be both adaptable to shifting strategic research priorities – an adaptability demonstrated by the fact that interdisciplinary collaborations were the key motivation for model development – and anchored in the past. This anchoring and non-epistemic values led to diverging opinions about whether existing models were “good enough” and whether investing time and effort to build a new model was a useful strategy when addressing pressing research challenges. Moving forward, we recommend that both stakeholders and modellers be involved in future snow model intercomparison projects in order to drive developments that address snow model limitations currently impeding progress in various disciplines. We also argue for more transparency about the contextual factors that shape research decisions. Otherwise, the reality of our scientific process will remain hidden, limiting the changes necessary to our research practice.

Prospective control by reinforcers in human choice: Misallocation and bias, but not time orientation, influences reinforcer control

Research with nonhuman animals and children suggests reinforcer control is prospective; that is, behaviour is organised according to the likely future, as extrapolated from past experience. The present experiment extended this work to adult choice, and also explored the effects of individual differences in past, present, and future time-orientation on reinforcer control. Participants (N = 163) responded in a concurrent schedule in which the probability of a reinforcer at the same location as the previous reinforcer varied across conditions. Choice tracked these probabilities, albeit imperfectly, indicating that reinforcers controlled behaviour prospectively. Deviations in choice from reinforcer probabilities were well-captured by a quantitative model assuming that such deviations arise because reinforcers are misallocated to the wrong alternative and because of biases towards one alternative. This replicates previous findings in pigeons and children, hence demonstrating the cross-species generality, and developmental continuity, of prospective reinforcer control. Individual differences in time orientation appeared not to influence reinforcer control, although further work is needed to explore the conditions under which time orientation modulates prospective reinforcer control.

High‐Latitude Eddy Covariance Temporal Network Design and Optimization

AbstractEcosystems at high latitudes are changing rapidly in response to climate change. To understand changes in carbon fluxes across seasonal to multi‐decadal timescales, long‐term in situ measurements from eddy covariance networks are needed. However, there are large spatiotemporal gaps in the high‐latitude eddy covariance network. Here we used the relative extrapolation error index in machine learning‐based upscaled gross primary production as a measure of network representativeness and as the basis for a network optimization. We show that the relative extrapolation error index has steadily decreased from 2001 to 2020, suggesting diminishing upscaling errors. In experiments where we limit site activity by either setting a maximum duration or by ending measurements at a fixed time those errors increase significantly, in some cases setting the network status back more than a decade. Our experiments also show that with equal site activity across different theoretical network setups, a more spread out design with shorter‐term measurements functions better in terms of larger‐scale representativeness than a network with fewer long‐term towers. We developed a method to select optimized site additions for a network extension, which blends an objective modeling approach with expert knowledge. This method greatly outperforms an unguided network extension and can compensate for suboptimal human choices. For the Canadian Arctic we show several optimization scenarios and find that especially the Canadian high Arctic and north east tundra benefit greatly from addition sites. Overall, it is important to keep sites active and where possible make the extra investment to survey new strategic locations.

Does scarcity induce hostility? An experimental investigation of common-pool resources

Climate change is leading to an increased scarcity of resources such as freshwater, energy, arable land and wildlife. This is perceived as a major security threat. However, the literature remains unclear on whether scarcity mitigates or exacerbates conflict. We design a novel laboratory experiment to investigate hostile behavior under scarcity. Participants interact repeatedly in a dynamic common-pool resource (CPR) and a joy-of-destruction game. The experiment distinguishes between two types of scarcity: Endogenous scarcity in the form of a deliberate human choice to overexploit resources and exogenous scarcity in the form of adverse environmental conditions. Our results show that endogenous scarcity exacerbates hostility. We trace this to participants being guided by negative reciprocity while finding no support for inequality aversion. The results indicate that to avoid hostility, policy makers will have to reduce human-induced scarcity. However, our results also show that exogenous scarcity mitigates hostility. This is in line with a vast body of literature from psychology, anthropology and biology finding increased levels of cooperation for all forms of life under environmental distress. It suggests that managing perceptions around increasing scarcities could be a second potential avenue for policy action.

Further Support for the Impact of Altruistic Costs in Human Mate Choice

Further Support for the Impact of Altruistic Costs in Human Mate Choice

Multiple and subject-specific roles of uncertainty in reward-guided decision-making.

Decision-making in noisy, changing, and partially observable environments entails a basic tradeoff between immediate reward and longer-term information gain, known as the exploration-exploitation dilemma. Computationally, an effective way to balance this tradeoff is by leveraging uncertainty to guide exploration. Yet, in humans, empirical findings are mixed, from suggesting uncertainty-seeking to indifference and avoidance. In a novel bandit task that better captures uncertainty-driven behavior, we find multiple roles for uncertainty in human choices. First, stable and psychologically meaningful individual differences in uncertainty preferences actually range from seeking to avoidance, which can manifest as null group-level effects. Second, uncertainty modulates the use of basic decision heuristics that imperfectly exploit immediate rewards: a repetition bias and win-stay-lose-shift heuristic. These heuristics interact with uncertainty, favoring heuristic choices under higher uncertainty. These results, highlighting the rich and varied structure of reward-based choice, are a step to understanding its functional basis and dysfunction in psychopathology.

Small populations of Palaeolithic humans in Cyprus hunted endemic megafauna to extinction.

The hypothesized main drivers of megafauna extinctions in the late Quaternary have wavered between over-exploitation by humans and environmental change, with recent investigations demonstrating more nuanced synergies between these drivers depending on taxon, spatial scale, and region. However, most studies still rely on comparing archaeologically based chronologies of timing of initial human arrival into naïve ecosystems and palaeontologically inferred dates of megafauna extinctions. Conclusions arising from comparing chronologies also depend on the reliability of dated evidence, dating uncertainties, and correcting for the low probability of preservation (Signor-Lipps effect). While some models have been developed to test the susceptibility of megafauna to theoretical offtake rates, none has explicitly linked human energetic needs, prey choice, and hunting efficiency to examine the plausibility of human-driven extinctions. Using the island of Cyprus in the terminal Pleistocene as an ideal test case because of its late human settlement (~14.2-13.2 ka), small area (~11 000 km2), and low megafauna diversity (2 species), we developed stochastic models of megafauna population dynamics, with offtake dictated by human energetic requirements, prey choice, and hunting-efficiency functions to test whether the human population at the end of the Pleistocene could have caused the extinction of dwarf hippopotamus (Phanourios minor) and dwarf elephants (Palaeoloxodon cypriotes). Our models reveal not only that the estimated human population sizes (n = 3000-7000) in Late Pleistocene Cyprus could have easily driven both species to extinction within < 1000 years, the model predictions match the observed, Signor-Lipps-corrected chronological sequence of megafauna extinctions inferred from the palaeontological record (P. minor at ~12-11.1 ka, followed by P. cypriotes at ~10.3-9.1 ka).

CAN ARTIFICIAL INTELLIGENCE PREFERENCES BE AN ALTERNATIVE TO HUMAN LINGUISTIC CHOICES? A MULTIDIMENSIONAL ANALYSIS OF RESEARCH ABSTRACTS OF ENGLISH LINGUISTICS

Background and Purpose: With the rapid advancements in generative AI, understanding its ability to emulate human language conventions is crucial. This work aims to analyze the possibility of applying AI technology in language production by comparing the lexico-grammatical features of abstracts created with the help of ChatGPT and written by British and American researchers. Methodology: Twenty papers written by researchers affiliated with UK universities and twenty by researchers affiliated with American universities were selected from the journals listed under the first quartile of the Web of Science and Scopus. Using the titles that were from the selected works, 40 abstracts were generated from ChatGPT for comparison. Each article was introduced with its title, and ChatGPT was asked to create an abstract based on the title. Subsequently, the subjects were examined with the help of Biber’s (1991) multivariate model considering five dimensions, which include the Informational vs Involved discourse, the Narrative vs Non-narrative, the Explicit vs. Situation- dependent discourse, Overt expression of argumentation/persuasion and the Impersonal/Abstract style as opposed to the Non-impersonal/Non-abstract style. Findings: The five factors analysed in the texts give evidence that ChatGPT generates more information-centric, non-narrative, argumentative, and less abstractive discourse than human researchers. Contributions: The results of the study show the possibilities for the further development of AI that helps to create language closer to human language. Keywords: Abstracts, ChatGPT, lexico-grammatical patterns, multidimensional analysis, research articles. Cite as: Ali, M., &amp; Ali, S. (2024). Can artificial intelligence preferences be an alternative to human linguistic choices? A multidimensional analysis of research abstracts of English linguistics. Journal of Nusantara Studies, 9(2), 514-536. http://dx.doi.org/10.24200/jonus.vol9iss2pp514-536

Sensory choices as logistic classification

Logistic classification is a simple way to make choices based on a set of factors: give each factor a weight, sum the results, and use the sum to set the log odds of a random draw. This operation is known to describe human and animal choices based on value (economic decisions). There is increasing evidence that it also describes choices based on sensory inputs (perceptual decisions), presented across sensory modalities (multisensory integration) and combined with non-sensory factors such as prior probability, expected value, overall motivation, and recent actions. Logistic classification can also capture the effects of brain manipulations such as local inactivations. The brain may implement it by thresholding stochastic inputs (as in signal detection theory) acquired over time (as in the drift diffusion model). It is the optimal strategy under certain conditions, and the brain appears to use it as a heuristic in a wider set of conditions.

Sensory choices as logistic classification.

Logistic classification is a simple way to make choices based on a set of factors: give each factor a weight, sum the results, and use the sum to set the log odds of a random draw. This operation is known to describe human and animal choices based on value (economic decisions). There is increasing evidence that it also describes choices based on sensory inputs (perceptual decisions), presented across sensory modalities (multisensory integration) and combined with non-sensory factors such as prior probability, expected value, overall motivation, and recent actions. Logistic classification can also capture the effects of brain manipulations such as local inactivations. The brain may implement by thresholding stochastic inputs (as in signal detection theory) acquired over time (as in the drift diffusion model). It is the optimal strategy under certain conditions, and the brain appears to use it as a heuristic in a wider set of conditions.

Evidence-Based Social Sciences and Practices: A Scoping Review

Introduction: The evidence-based medicine (EBM) was introduced in the 1990s, paving the way for the new approaches to science methodology and research evidence that changed medicine-related practices. Following the EBM, social sciences ranging from education to public governance and policymaking entered a new stage of knowledge production and dissemination. Each evidence-based social science field produces its own evidence and evidence synthesis laying the foundation for efficient social practices. Pilot searches failed to bring complex and complete evidence-based methodology for social sciences. Purpose: This scoping review aims to identify the scope of the evidence-based social sciences and practices as an emerging field. Method: The review adhered to the PRISMA extension for scoping reviews, and the PPC framework. The eligibility criteria include problem (population), concept, context, language, time period, types of sources, geographical location, databases, areas of research. The searches to identify relevant publications entail searches in the Scopus database. The studies were identified and selected by screening titles, abstracts and full texts, totalling 35 documents. Results: The results cover search and selection outcomes; a bibliometric analysis, the breakdown of the publications among the four thematic clusters; the findings relating to evidence-based medicine and practice methodology applicable to social sciences; the analysis of the research area of evidence-based social sciences and practices; the social science practices by sectors. Much of the EBM methodology was directly borrowed by social sciences. Though, the major controversy was found in the hierarchy and levels of evidence as social sciences are subject to human choices. Randomized controlled trials and systematic reviews were analysed in the context of social sciences. The most elaborated and fast developing evidence-based areas in social sciences contained evidence-based education and evidence-based policymaking, with systems of governmental agencies and institutions introducing these evidence-based practices. Сonclusion. The review attained the objective and gave answers to the research questions. Only few studies were published to comprehensively address the emerging field of evidence-based social sciences and practices. Fragmentated sub-fields are covered unevenly, with many mythological divergences and disputed issues, including the quality of evidence, their weight and hierarchy, types of research.

Cupping Therapy Modern Medicine Solutions In Islam

Every disease has a cure, this is a form that must be done by humans so that efforts when stricken by disease. If all diseases have a cure, then easily a person will become healthy. Maintaining health is a choice for humans. Someone in maintaining their health has various ways ranging from regulating diet, exercise patterns, regulating rest periods, some are on a diet. Hijamah or cupping is a form of therapy to maintain and treat various diseases. Although in its history cupping is a treatment / therapy that has long been known, namely since the time of the Prophet Muhammad Saw. But until now there are still many people who follow it, in addition to the sunnah taught cupping is also able to provide solutions in health. Cupping is not only done when someone is sick, but can be done to maintain health by paying attention to the time arranged according to Islam. Cupping is not only doing health therapy but also carrying out the sunnah of the Prophet Muhammad (peace be upon him)

Pharmacological characterization of sex differences in the effects of dopaminergic drugs on effort-based decision making in rats.

Motivational dysfunctions related to effort exertion are common in psychiatric disorders. Dopamine systems regulate exertion of effort and effort-based choice in humans and rodents. Previous rodent studies mainly employed male rats, and it is imperative to conduct studies in male and female rats. The present studies compared the effort-related effects of IP injections of the dopamine antagonists ecopipam and haloperidol, and the vesicular monoamine transport-2 inhibitor tetrabenazine (TBZ), in male and female rats using the fixed ratio 5/chow feeding choice task. Ecopipam (0.05-0.2mg/kg) and haloperidol (0.05-0.15mg/kg) induced a low-effort bias, decreasing lever pressing and increasing chow intake in males and females in the same dose range. With lever pressing, there was a modest but significant dose x sex interaction after ecopipam injection, but there was no significant interaction after administration of haloperidol. In the first study with TBZ (0.25-1.0mg/kg), there was a robust sex difference. TBZ shifted choice from lever pressing to chow intake in male rats, but was ineffective in females. In a second experiment, 2.0mg/kg affected choice behavior in both males and females. TBZ increased accumbens c-Fos immunoreactivity in a sex-dependent manner, with males significantly increasing at 1.0mg/kg, while females showed augmented immunoreactivity at 2.0mg/kg. The neural and behavioral effects of TBZ differed across sexes, emphasizing the importance of conducting studies in male and female rats. This research has implications for understanding the effort-related motivational dysfunctions seen in psychopathology.

Human Behavior in Suboptimal Choice Tasks: Defining Optimality.

Suboptimal choice behavior, or behavior that leads to a loss of resources over time, has been observed in a laboratory setting from multiple species. A procedure commonly used to capture this effect involves presenting two alternatives during choice trials, one of which is optimal whereas the other is suboptimal. The optimal alternative yields reinforcement more often than the suboptimal alternative, but often does not produce signals that indicate whether reinforcement will occur. The suboptimal alternative produces less reinforcement than the optimal alternative but may include reinforcement-predictive stimuli that indicate to the organism whether reinforcement will occur. This procedural framework has consistently produced a preference for the suboptimal alternative in pigeons and, to a lesser extent, rats. However, human participants have demonstrated preference for the optimal alternative. Following a review of past suboptimal choice research, we applied the reinforcement-derived definition of optimality to two sets of our previously published human data. We found that under multiple conditions, human choice behavior was consistent with what was predicted by the proportion of obtained reinforcement, thus supporting that the behavior was optimal. However, we found that participants in two conditions chose the suboptimal alternative more than expected. This finding could be considered as a demonstration of suboptimal choice in humans. We propose that comparing choice behavior to what past obtained reinforcement outcomes would predict might be a more accurate view of whether patterns of choice are within the parameters of this task.

The Mortuary Landscape of the 1st–12th Centuries: Major Research Questions, Approaches, and Methods in the History of Research on the Latvian Iron Age

In archaeology, landscape is studied as a cultural, social, and environmental process that simultaneously influences human thinking and is impacted by human actions. From such a perspective, the establishment of cemeteries, too, results from human choice with respect to the environment, engendering a specific mortuary landscape. This is, overall, a little-studied field in the history of research on the Iron Age in Latvia. Even so, a continuous development of ideas may be traced, both in terms of the broadening of the range of issues addressed, proceeding from basic description of the cemetery’s location to analysis of its significance in the landscape, and in terms of the growing diversity of approaches and methods employed, moving from simple observation of the surrounding area to interdisciplinary studies and various kinds of data analysis.

Surprise-minimization as a solution to the structural credit assignment problem.

The structural credit assignment problem arises when the causal structure between actions and subsequent outcomes is hidden from direct observation. To solve this problem and enable goal-directed behavior, an agent has to infer structure and form a representation thereof. In the scope of this study, we investigate a possible solution in the human brain. We recorded behavioral and electrophysiological data from human participants in a novel variant of the bandit task, where multiple actions lead to multiple outcomes. Crucially, the mapping between actions and outcomes was hidden and not instructed to the participants. Human choice behavior revealed clear hallmarks of credit assignment and learning. Moreover, a computational model which formalizes action selection as the competition between multiple representations of the hidden structure was fit to account for participants data. Starting in a state of uncertainty about the correct representation, the central mechanism of this model is the arbitration of action control towards the representation which minimizes surprise about outcomes. Crucially, single-trial latent-variable analysis reveals that the neural patterns clearly support central quantitative predictions of this surprise minimization model. The results suggest that neural activity is not only related to reinforcement learning under correct as well as incorrect task representations but also reflects central mechanisms of credit assignment and behavioral arbitration.

Det er Herren, der styrer en mands gang

This article discusses the question of agency in the Old Testament (OT) and challenges the view held by some scholars that the OT as a whole depicts human beings as having free will in the sense of being able to choose and having control over the choices they make. Many passages do seem to presuppose human choice and control, but the article presents numerous other passages that highlight God’s control of everything – including, in some cases, what human beings want and choose. Furthermore, several books of the OT describe the human ability to follow God’s commandments as deeply flawed and envisage a future divine intervention that will fundamentally change the way humans behave. Human free will must be understood in the light of this underlying notion of divine control that permeates the OT. However, this is not a fatalistic type of determinism. The tension between the notions of divine and human agency is real and both notions ought to inform our understanding of the theology of the texts.

Foraging in a non-foraging task: Fitness maximization explains human risk preference dynamics under changing environment.

Changes in risk preference have been reported when making a series of independent risky choices or non-foraging economic decisions. Behavioral economics has put forward various explanations for specific changes in risk preference in non-foraging tasks, but a consensus regarding the general principle underlying these effects has not been reached. In contrast, recent studies have investigated human economic risky choices using tasks adapted from foraging theory, which require consideration of past choices and future opportunities to make optimal decisions. In these foraging tasks, human economic risky choices are explained by the ethological principle of fitness maximization, which naturally leads to dynamic risk preference. Here, we conducted two online experiments to investigate whether the principle of fitness maximization can explain risk preference dynamics in a non-foraging task. Participants were asked to make a series of independent risky economic decisions while the environmental richness changed. We found that participants' risk preferences were influenced by the current and past environments, making them more risk-averse during and after the rich environment compared to the poor environment. These changes in risk preference align with fitness maximization. Our findings suggest that the ethological principle of fitness maximization might serve as a generalizable principle for explaining dynamic preferences, including risk preference, in human economic decision-making.