News & Comment

Citizen participation in water governance can improve the relevance, implementation, and effectiveness of public policies. However, participation can be expressed in a great diversity of forms, on a gradient ranging from mere public consultation to shared governance of natural resources. Positive outcomes ultimately depend on the conditions under which participation takes place, with key factors such as leadership, the degree of trust among stakeholders, and the interaction of public authorities with citizens. Social network analysis has been used to operationalize participatory processes, contributing to the identification of leaders, intersectoral integration, strategic planning, and conflict resolution. In this commentary, we analyze the potential and limitations of participation in water governance and illustrate it with the case of the Campina de Faro aquifer in southern Portugal. We propose that stakeholder network analysis is particularly useful for promoting decentralized decision-making and consensual water resources management. The delegation of power to different interest groups is a key process in the effectiveness of governance, which can be operationalized with network analysis techniques.

Behavioral researchers tend to study behavior in highly controlled laboratory settings to minimize the effects of potential confounders. Yet, while doing so, the artificial setup itself might unintentionally introduce noise or confounders, such as boredom. In this perspective, we draw upon theoretical and empirical evidence to make the case that (a) some experimental setups are likely to induce boredom in participants, (b) the degree of boredom induced might differ between individuals as a function of differences in trait boredom, (c) boredom can impair participants’ attention, can make study participation more effortful, and can increase the urge to do something else (i.e., to disengage from the study). Most importantly, we argue that some participants might adjust their behavior because they are bored. Considering boredom’s potential for adding noise to data, or for being an unwanted confound, we discuss a set of recommendations on how to control for and deal with the occurrence and effects of boredom in behavioral science research.

Should healthcare professionals use the term ‘patient’? A patient is a social construct, in a biomedical model, in which each actor has their role to play. This model has been criticised as belonging to an era of medical hegemony and (mis)represents an individual seeking healthcare as one who is simply a passive participant and recipient of care. The ‘Language Matters’ campaign, for people living with diabetes, has sought to address the role of language in interactions between healthcare providers. A key point raised in the campaign is whether someone who feels well, but has ongoing healthcare input, should be referred to as a patient? In this article, we address the concept of a patient and how its use can belie a particular mindset (or ‘discourse’) in which power is established in a relationship and can lead to individuals being defined by their condition. However, for some linguistic communities (such as nurses and doctors), a patient may be considered less as one over whom they have dominion, but rather someone for whom they have specific responsibilities and duty of care. Drawing upon the philosophical theories of language—that the meaning and inference of a word is dependent on its use—we argue that the context in which use of the term patient occurs is crucial. Without more fundamental cultural disruption of the biomedical model, word substitution, in itself, will not change perception.

Recent years have seen an increase in calls for ethnography as a method to study Artificial Intelligence (AI). Scholars from diverse backgrounds have been encouraged to move beyond quantitative methods and embrace qualitative methods, particularly ethnography. As anthropologists of data and AI, we appreciate the growing recognition of qualitative methods. However, we emphasize the importance of grounding ethnography in specific ways of engaging with one’s field site for this method to be valuable. Without this grounding, research outcomes on AI may become distorted. In this commentary, we highlight three key aspects of the ethnographic method that require special attention to conduct robust ethnographic studies of AI: committed fieldwork (even if the fieldwork period is short), trusting relationships between researchers and participants, and, importantly, attentiveness to subtle, ambiguous, or absent-present data. This last aspect is often overlooked but is crucial in ethnography. By sharing examples from our own and other researchers’ ethnographic fieldwork, we showcase the significance of conducting ethnography with careful attention to such data and shed light on the challenges one might encounter in AI research.

Parents’ beliefs and behavior act as both explicit and implicit ways of communicating the value of science and their confidence that their child can be successful in science-related classes. Using the NCES High School Longitudinal Survey (HSLS:09), we examined how parent beliefs and behaviors regarding their 9th grader’s science education predicted the students’ motivation in science. Using multiple regression indicates that the combination of parental education, beliefs, and involvement in science-related activities with their child are weak but significant predictors of students’ academic motivation in science (adjR² = 0.04, F(6, 14,933) = 26.32, P < 0.001). In particular, parent education and parent involvement have positive and significant effects on students’ science identity and science self-efficacy. These findings suggest that students may have a stronger academic motivation in science with parents who have higher levels of education, more confidence in their ability to help their child in science, and who engage in more science activities with their child.

It is widely documented that population growth is closely related to overall economic growth. Given the close link between the two, the global decline in fertility rates has led to an increasing number of governments implementing pro-natal policies aimed at encouraging childbearing. However, this article seeks to emphasise the significance of policy solutions that prioritise the needs, choices, and decisions of individuals. Rather than compelling people to have (or not have) children, it is imperative that the reproductive autonomy of individuals be respected and supported. In a global environment that demands continuous population growth, the spotlight should always remain on the people behind the fertility numbers. A shift in the pro-natal policy paradigm towards a rights-based approach is necessary to prioritise individuals’ family aspirations, break down institutional barriers, and promote equity in family formation.

The COVID-19 pandemic has been the scene of several epistemic battles at the science-society interface, creating deadlocks that have been hard to overcome. To cut through the paralysing elements of these discussions, we present an analysis of three epistemic battles, concerning empirical evidence, expertise, and model projections. Our analysis singles out a crucial factor that drives unhelpful disputes like these: the contested prioritisation of specific types of scientific knowledge, which are considered adequate for policy only if they meet predetermined standards. To move beyond these deadlocks, we introduce the conceptual tools of epistemic pluralism and contextualism, which give concrete indications in the three controversies we discuss and show us the way forward in debates on science-based policy.

Suicide, one of the top causes of life lost in developed countries, is a major health problem, especially today, with the dramatic increase in mental health difficulties that was triggered during the Coronavirus pandemic (COVID-19). Opportunely, the recent emergence of internet-based crowdsourcing platforms (e.g., Amazon’s Mechanical Turk) may accelerate research on suicide prevention, however, this type of suicide research online involves a difficult ethical challenge: how to keep participants’ safe without compromising their privacy. To address this ethical challenge, a consortium of experts from multiple research institutions was assembled. The consortium discussed the advantages and disadvantages for participants involved in crowdsourcing-based studies that address suicide risk. This discussion resulted in a consensual step-by-step protocol for researchers who wish to conduct suicide research online, using the crowdsourcing platforms. This article provides a detailed description of the protocol and outlines key ethical arguments that led to its formulation. Unresolved issues are discussed as well and other researchers are encouraged to implement the proposed protocol and suggest further improvements. It is our hope that the current protocol will facilitate the research on large and diverse populations online and thus contribute to the global efforts to reduce suicide rates around the world.

ChatGPT is a chatbot based on a large language model. Its application possibilities are extensive, and it is freely accessible to all people, including psychotherapists and individuals with mental illnesses. Some blog posts about the possible use of ChatGPT as a psychotherapist or as a supplement to psychotherapy already exist. Based on three detailed chats, the author analyzed the chatbot’s responses to psychotherapists seeking assistance, to patients looking for support between psychotherapy sessions, during their psychotherapists’ vacations, and to people suffering from mental illnesses who are not yet in psychotherapy. The results suggest that ChatGPT offers an interesting complement to psychotherapy and an easily accessible, good (and currently free) place to go for people with mental-health problems who have not yet sought professional help and have no psychotherapeutic experience. The information is, however, one-sided, and in any future regulation of AI it must also be made clear that the proposals are not only insufficient as a psychotherapy substitute, but also have a bias that favors certain methods while not even mentioning other approaches that may be more helpful for some people.

The recent debate about whether climate activists should employ disruptive tactics tends to conflate all forms of disruption. The debate typically focuses on the public’s reaction to protesters, yet the more important question is whether a given tactic imposes disruption on elite decision makers. Most external analysts, and many activists themselves, fail to specify what approaches are most disruptive of elite interests and which elite institutions the movement should target. They also often misinterpret the lessons of historical social movements. We reconsider one of those movements, the Birmingham civil rights campaign of 1963, in light of the current strategic debate. We argue that disruption is necessary, but that not all “disruptive” strategies are equally effective. In particular, we advocate a strategy that can impose sustained and escalating costs on the elite sectors that can force politicians to confront the climate emergency. Priority targets include financial institutions that fund and underwrite fossil fuels as well as corporations, universities, pension funds, and other institutions that consume and invest in fossil fuels.

Large-scale and global explanatory models for past, current, and future human behaviour are currently the focus of all the natural sciences and humanities. But to which extent do such models enable the theoretical and methodological discourse that explains the complexity of human patterns in different geographic and ecological set-ups? Such an effort incorporates principles of geography, ecology, and archaeology, as well as attempts for model parameterisation and adaptation. Building on local behaviour with global implications, this paper explores fundamental parameters of environmental connectivity and ecological functionalities in archaeological and ecological research. As a consequence, I hypothesise a Divergence Problem in archaeological and particularly in socio-environmental models—a mismatch between archaeological data complexity, environmental explanatory variables, and simplicity of the resulting model. Theoretically, the adjustment of global models to regional contextualisation can be achieved by introducing a correction coefficient, hereafter referred to as Glocalization Coefficient, which could allow for the comparison between regional environmental driving factors and individual human activity spheres.

The world faces multiple intersecting crises, several of which are existential. The current dominant economic design is at their root cause, leading to increased advocacy for alternative economic approaches, including Wellbeing Economy. However, the role of culture, both as an objective and as a means of achieving a Wellbeing Economy, is largely absent. In this article, we review how culture has been misunderstood as being dependent on the attainment of basic needs rather than an ever-present, vital, but undervalued attribute of all societies. We discuss how neoliberal economics has individualised and commodified culture, valuing it only as an engine of economic growth and tradeable capital, all of which has led to a substantial diminution and fraying of the social fabric which any positive social transformation will rely upon. Finally, we demonstrate why culture is an essential precondition for the creation of momentum for change through the conversations, shared understandings, new narratives, and communal spaces of all forms which cultural flourishing creates. We conclude by arguing that advocates for a Wellbeing Economy, and similar economic models, such as Doughnut Economics and Foundational Economies, should prioritise and embed support for cultural development as a non-commodified social asset if we are to adequately respond to current crises and navigate to a flourishing and habitable future for ourselves and our descendants.

Parties to the Paris Agreement face mounting social pressure to raise their ambition, thereby reducing the gap between individual pledges and collective temperature goals. Although crucial for inciting positive change, especially given that the Paris Agreement lacks an enforcement mechanism, it is also important to consider social pressure’s potential negative unintended consequences. First, it might undermine the Paris Agreement’s celebrated flexibility, which allows countries to design their Nationally Determined Contributions according to domestic conditions and capabilities. Second, it might result in widespread noncompliance by inciting pledges that the countries concerned prove unwilling or even unable to fulfill. Should that happen, confidence in the Paris Agreement and its institutions might falter. Further research is therefore needed to identify the scope conditions for social pressure to work effectively in the domain of international climate policy.

Social media has expanded the possibilities for citizens around the world to share knowledge and interact about scientific advancements, facilitating to raise public awareness of and interest in science. Amidst this context, scientists in all disciplines are intensifying the use of social media as a data source to capture what citizens express about their achievements, beyond dissemination purposes. Content analysis is the generalised method used by researchers to explore the interactions of citizens in social media about science. In this commentary paper, we explore the social media communicative observations as an emerging technique in the social media analytics to include the communicative dimension of science in the analysis of interactions between scientists and citizens. The implications to empower dialogically the social media communities interested in science are shared.

The development of care robots has been accompanied by a number of technical and social challenges, which are guided by the question: “What is a robot for?” Debates guided by this question have discussed the functionalities and tasks that can be delegated to a machine that does not harm human dignity. However, we argue that these ethical debates do not offer any alternatives for designing care robots for the common good. In particular, we stress the need to shift the current ethical discussion on care robots towards a reflection on the politics of robotics, understanding politics as the search for the common good. To develop this proposal, we use the theoretical perspective of science and technology studies, which we integrate into the analysis of disagreement inspired by a consensus-dissensus way of thinking, based on discussing and rethinking the relationships of care robots with the common good and the subjects of such good. Thus, the politics of care robots allows for the emergence of a set of discussions on how human-machine configurations are designed and practiced, as well as the role of the market of technological innovation in the organisation of care.

Violations of the responsibility of humanitarian and development organizations to do no harm are a serious concern. Protection from sexual exploitation and abuse, commonly referred to as PSEA, is a widely used acronym that highlights the need to safeguard vulnerable women, children, and men from acts of sexual exploitation and abuse (SEA) by humanitarian aid and development workers. PSEA safeguarding denotes the responsibilities incumbent upon organizations such as the United Nations, the Red Cross, and international nongovernmental organizations (INGOs) that are involved in the management of international humanitarian and developmental programs. This commentary can be interpreted as an appeal to INGOs to evaluate the potency of established regulations to safeguard individuals from sexual exploitation in communities and workplaces. The central argument of this paper is that INGOs that focus on cultural transformation are more effective in their attempts to address violation than those organizations that adopt a centralized approach wherein attempts to secure power and control emerge as the prevailing drivers. It is incumbent upon INGOs to engage in open discussions about the strengths and weaknesses of their existing approaches to search for innovative solutions and facilitate bold actions designed to enhance their effectiveness on PSEA. Researchers are encouraged to look at gaps in the academic literature that connects PSEA and cultural transformation in the INGOs and do further work in this field as it would contribute to remedying weaknesses in prevailing mechanisms designed to prevent SEA.

Historical linguistics is the study of language change and stability, of the history of individual languages, and of the relatedness between languages. In spite of numerous acknowledgements, the adoption of quantitative methods in historical linguistics is still far from being mainstream and it falls below the level of other branches of linguistics. This comment considers the adoption of quantitative methods in recent historical linguistics research, and compares a study on 2012 publications with a similar study conducted seven years later. This comment argues for the advantages of a wider adoption of quantitative methods among historical linguists, and considers various reasons for the relatively slow progress in this direction. It also clarifies when quantitative methods are not the preferred route.

Self-driving, ‘autonomous’ vehicles (AVs) promise to change the world in profound ways. The suggested benefits include safety, efficiency and accessibility. However, researchers and others have been quick to raise questions about wider implications for mobility and urban environments and responsible development of the technology. In a discussion that has been dominated by science, engineering and narrow questions of ethics, there is a need to draw attention to the old questions of politics: Who wins? Who loses? Who decides? Who pays? AVs will not be defined by their supposed autonomy; they will be defined by a set of social relationships. The special collection that this paper accompanies brings together research from a range of disciplines to explore the politics of autonomous vehicles and provide a foundation for ongoing investigation.

Pandemics affect every aspect of life, and Coronavirus Disease 2019 (COVID-19) is no exception. The impact of COVID-19 might be even greater in medical education, which involves close contact with patients. This comment reviews current trends in medical education in response to COVID-19, especially in the pre-clerkship curriculum, and discusses opportunities and challenges in medical education in the post-pandemic era. COVID-19 has accelerated the adoption of online teaching and learning and is expected to boost innovation in medical education. First, blended learning, which is a mix of online and offline learning intended to incorporate the best of both worlds, is expected to become more widespread. Second, more novel approaches to learning that involve student-led initiatives likely become popular mediated by various technologies. Third, there will be more use of online learning resources and assessments. As online learning is expected to play a prominent role in the post-COVID-19 era, such transitions offer both opportunities and challenges. These challenges include faculty development on online teaching skills, creation and sharing of online resources, and effective design and implementation of online assessments. This comment calls for institutional support and collaborations for faculty development and for the development and sharing of learning resources, more models and guidelines for effective technology integration, and use of the virtual learning environment to promote student-centered learning to embrace the challenges as opportunities to improve medical education in the post-COVID era.

Natural resource management agencies in the United States have a legal responsibility to represent Indigenous Peoples and federally recognized Tribes in environmental stewardship. This comment article is a call to action that argues for genuine representation of Tribes and other Indigenous Peoples through adherence to existing, formal consultation policies and coproduction of knowledge. Agencies must recognize and respect the differences between public involvement and government-to-government consultation with federally-recognized Tribes. Sovereign tribal nations are not the public and have a unique relationship with federal agencies based in the federal trust responsibility. Coproduction of knowledge is an emerging enterprise that has potential for meaningfully engaging and genuinely and equitably representing Indigenous Peoples and Tribes and should be codeveloped and implemented as policy. Agencies should build capacity to properly represent tribal nations in decisions. Agency employees and Indigenous Peoples must spend more time together to increase cultural awareness and build meaningful relationships to facilitate genuine consultation and coproduction of knowledge.