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Democracy requires some sort of exchange of knowledge between holders of different knowledge positions. The concept of epistemic justice brings the ability to know and the right to be recognised as a knowledgeable person under a scheme of justice. It problematises social conditions that potentially compromise the ability to share knowledge and thereby effectuate change and the possibility of being recognised as a knowing subject and being granted access to equitable means of producing knowledge. This paper engages with temporal aspects of epistemic justice. What role do temporalities play in people’s possibilities to create knowledge and the way they create knowledge? What role does time play in the valuation and circulation of knowledges? How do hegemonic conceptions of time potentially make some knowledges circulate more freely than others? Since conceptions of time connect to specific forms of knowledge, hierarchies and speakabilities of temporalities form an immediate correlate of hierarchies of knowledge. By extension, such hierarchies feed into schemes of epistemic justice. Thus, democracy’s duty to emancipate suppressed voices requires emancipating the times from which those suppressed voices speak.

This paper analyses expert and regulatory perspectives on car driver-monitoring systems that measure bodies to infer and react to emotions, fatigue, and attentiveness. Developers of driver-monitoring systems promise increased safety on the road, alongside comfort for cabin occupants through personalisation and automation. The impetus is three-fold, namely: (1) European road safety policy seeks to vastly reduce road deaths using computational surveillance; (2) there is a growing interest around in cabin safety solutions that sense emotion and affective states of drivers and passengers; and (3) autonomous driving trends are changing the nature of interactions between vehicle and driver. Safety led applications are of special interest because they are backed by policy and standards initiatives including the European Union’s Vision Zero policy and the industry led New Car Assessment Programme (NCAP). Informed by 13 interviews with experts working in and around in-cabin sensing technologies, this paper first identifies and explores features of emergent in-cabin profiling through emotional artificial intelligence (AI) and biometric measures. It then examines how in-car sensing should be regulated by analysing data protection laws and the proposed EU AI Act. A deep ambivalence emerged from our participants around the emergence of emotional AI in cars, and how best to regulate these technologies.

Amidst public concern surrounding the proprietary and exploitative use of personal data by corporations and public institutions, and its consequences from a sociotechnical perspective, narratives around digital commons have recently emerged framing potential alternatives. This paper presents the results of an experimental approach, methodology and process, through which two main questions are addressed. First, how to articulate co-creation dynamics for the structured and participatory elaboration of the Digital Democracy and Data Commons Manifesto following openness, diversity and inclusivity principles. Second, how the manifesto, as a narrative and discursive artifact, can follow and conclude a wider process of sociotechnical discussion and positioning about data commons. Our approach is based on participatory design methods, more concretely on a collaborative writing sprint, to co-create a manifesto on alternatives to current datafication, digital inequalities and lack of citizen control over personal data. On the one hand we describe the process to implement a sprint approach for collaboratively writing a topic-specific manifesto, in the context of the broader EU project DECODE (Decentralized Citizen Owned Data Ecosystems). On the other hand, we present and analyze main results from the content structure of the manifesto over its initial and final versions, which moved progressively as a cohesive text away from a scholarly and policy-oriented tone.

Open science hardware (OSH) is a term frequently used to refer to artifacts, but also to a practice, a discipline and a collective of people worldwide pushing for open access to the design of tools to produce scientific knowledge. The Global Open Science Hardware (GOSH) movement gathers actors from academia, education, the private sector and civil society advocating for OSH to be ubiquitous by 2025. This paper examines the GOSH movement’s emergence and main features through the lens of transitions theory and the grassroots innovation movements framework. GOSH is here described embedded in the context of the wider open hardware movement and analyzed in terms of framings that inform it, spaces opened up for action and strategies developed to open them. It is expected that this approach provides insights on niche development in the particular case of transitions towards more plural and democratic sociotechnical systems.

Abstract This article interprets emerging scholarship on rental housing platforms—particularly the most well-known and used short- and long-term rental housing platforms—and considers how the technological processes connecting both short-term and long-term rentals to the platform economy are transforming cities. It discusses potential policy approaches to more equitably distribute benefits and mitigate harms. We argue that information technology is not value-neutral. While rental housing platforms may empower data analysts and certain market participants, the same cannot be said for all users or society at large. First, user-generated online data frequently reproduce the systematic biases found in traditional sources of housing information. Evidence is growing that the information broadcasting potential of rental housing platforms may increase rather than mitigate sociospatial inequality. Second, technology platforms curate and shape information according to their creators’ own financial and political interests. The question of which data—and people—are hidden or marginalized on these platforms is just as important as the question of which data are available. Finally, important differences in benefits and drawbacks exist between short-term and long-term rental housing platforms, but are underexplored in the literature: this article unpacks these differences and proposes policy recommendations. Policy and practice recommendations As rental housing technologies upend traditional market processes in favor of platform oligopolies, policymakers must reorient these processes toward the public good. Long-term and short-term rental platforms offer different market benefits and drawbacks, but the latter in particular requires proactive regulation to mitigate harm. At a minimum, policymakers must require that short-term rental platforms provide the information necessary for cities to enforce current, let alone new, housing regulations. Practitioners should be cautious inferring market conditions from rental housing platform data, due to difficult-to-measure sampling biases.

Misinformation online poses a range of threats, from subverting democratic processes to undermining public health measures. Proposed solutions range from encouraging more selective sharing by individuals, to platform removal of false content and accounts that create or promote it. How, whether, and which strategies to implement depends on their relative and combined ability to reduce viral misinformation spread at plausible levels of enforcement. Here we provide a framework to evaluate interventions aimed at reducing viral misinformation online both in isolation and when used in combination. We begin by deriving a generative model of viral misinformation spread, inspired by research on infectious disease. Applying this model to a large corpus of misinformation events that occurred during the 2020 US election, we reveal that commonly proposed interventions--including removal of content, virality circuit breakers, nudges, and banning---are unlikely to be effective in isolation without extreme censorship or major breakthroughs in how to control misinformation. However, our framework demonstrates that a combined approach can achieve a substantial ~50% reduction in the spread of misinformation. Our results challenge claims that combating misinformation will require new ideas or high costs to user expression. Instead, we highlight a practical path forward as misinformation online continues to threaten vaccination efforts, equity, and democratic processes around the globe.

Artificial Intelligence (AI) technologies have the potential to dramatically impact the lives and life chances of people with disabilities seeking employment and throughout their career progression. While these systems are marketed as highly capable and objective tools for decision making, a growing body of research demonstrates a record of inaccurate results as well as inherent disadvantages for historically marginalised groups. Assessments of fairness in Recruitment AI for people with disabilities have thus far received little attention or have been overlooked. This paper examines the impacts to and concerns of disabled employment seekers using AI systems for recruitment, and discusses recommendations for the steps employers can take to ensure innovation in recruitment is also fair to all users. In doing so, we further the point that making systems fairer for disabled employment seekers ensures systems are fairer for all.

This report is based on a 2016 survey of members and affiliates of three institutes of data science at major U.S. research universities, focusing on career paths for data scientists within academia. After considering how our respondents define data science, we identify various activities, priorities, resources, and concerns around data science in academia, especially with respect to data science careers. We end by providing recommendations about how universities can better support an emerging set of roles and responsibilities around data and computation within and across academic fields.

What are the challenges and best practices for doing data-intensive research in teams, labs, and other groups? This paper reports from a discussion in which researchers from many different disciplines and departments shared their experiences on doing data science in their domains. The issues we discuss range from the technical to the social, including issues with getting on the same computational stack, workflow and pipeline management, handoffs, composing a well-balanced team, dealing with fluid membership, fostering coordination and communication, and not abandoning best practices when deadlines loom. We conclude by reflecting about the extent to which there are universal best practices for all teams, as well as how these kinds of informal discussions around the challenges of doing research can help combat impostor syndrome.

This report is a high-level summary analysis of the 2017 GitHub Open Source Survey dataset, presenting frequency counts, proportions, and frequency or proportion bar plots for every question asked in the survey., Comment: 58 pages

As cities become more involved in data-driven processes of growth and governance, critical scholarship has highlighted the formidable issues around ownership, uses and the ethics of collecting, storing, and circulating such data. However, there has been less focus on the physical infrastructure as the ‘last mile’ problem for Internet access, between a revanchist perspective on the ‘broken Internet’ delivered by digital capitalism and the liberal rhetoric of the Internet as a human right. Through two case studies, the paper plots a pragmatic trajectory in the adoption of the Internet for people and ‘things’, in which city and users take different roles and responsibilities. It highlights benefits and challenges around the long-term sustainability and maintenance of the Internet as an infrastructure of the commons. An attention to ‘commoning’, instead, reveals the exclusionary or enabling practices the smart city might foster. Thus, the paper advocates for the direct involvement of the city and its citizens in maintaining and reproducing connectivity networks in the smart city.

This short data visualisation and accompanying perspective explains recent trends and outlines three reasons to be even more optimistic about the future of Machine Learning in the academic Social Sciences.

When firms engage in lobbying, their intended outcome is a regulatory change that benefits them. However, prior literature suggests that there may also be an unintended outcome of lobbying—the leakage of knowledge to competitors. In this paper, I explore when the intended and the unintended outcomes are more likely by theorizing about the relationship between lobbying and innovation. I predict that innovations that are novel are likely to benefit from the intended regulatory changes. However, innovations that use knowledge uniquely possessed by a few firms may be compromised. I use new data from 1999-2013 on public U.S. firms that engaged in lobbying to federal agencies, the regulatory changes made by those federal agencies, and the 6,600 patents granted to the lobbying firms. I analyze the text of federal documents to measure regulatory change and patent abstracts to detect knowledge leakage. To test the theory, I conduct an instrumental variable 2SLS mediation analyses. The results suggest that the intended regulatory changes that follow lobbying can benefit innovations by reducing uncertainty and facilitating wider adoption. However, unique technological knowledge that only a few firms possess may be expropriated by competitors during the process of lobbying. Overall, this paper demonstrates that fundamental aspects of innovations—such as institutional change, knowledge transfer, and technological outcomes—are closely related to lobbying, a form of nonmarket activity.

The Sustainable Development Goals (SDGs) recognise the importance of action across all scales to achieve a sustainable future. To contribute to overall national- and global-scale SDG achievement, local communities need to focus on a locally-relevant subset of goals and understand potential future pathways for key drivers which influence local sustainability. We developed a participatory method to co-create local socioeconomic pathways by downscaling the SDGs and driving forces of the shared socioeconomic pathways (SSPs) via a local case study in southern Australia through contextual analysis and community engagement. We linked the SSPs and SDGs by identifying driving forces and describing how they affect the achievement of local SDGs. We co-created six local socioeconomic pathways with the local community which track towards futures with different levels of fulfilment of the SDGs and each encompasses a narrative storyline incorporating locally-specific ideas from the community. We tested and validated the local pathways with the community. This method extends the SSPs in two dimensions–into the broader field of sustainability via the SDGs, and by recontextualizing them at the local scale. The local socioeconomic pathways can contribute to achieving local sustainability goals from the bottom up in alignment with global initiatives. Electronic supplementary material The online version of this article (10.1007/s11625-021-00921-2) contains supplementary material, which is available to authorized users.

Some individuals do not limit their self-tracking efforts to passively collecting and observing gathered data about themselves, but rather develop it into forms of self-research and self-experimentation, also called “personal science”. This type of N-of-1 research is relevant to the fields of personal informatics, patient-led research and social studies of science, but as a knowledge generation practice is still poorly understood. To fill this gap, we conducted 22 semi-structured interviews to investigate the intrinsic and extrinsic motivations of individuals engaging in personal science activities, as well as shared goals and values present in self-research communities. Our analysis is based on a conceptual framework that integrates previous approaches in self-research, as well as in connection with citizen science, the scientific ethos and cooperation in peer production. We identify how self-researchers seek to go beyond personal metrics about their health and wellbeing regarding data provided by wearables, are engaged over time by individual involvement in technology and scientific-related activity, and collaborate following similar goals and values when learning and sharing empirical knowledge with peers. In this sense, personal science can be understood as a specific type of citizen science and an example of a more participatory and inclusive scientific culture driven by self-reflection, critical thinking and openness.

Neglected diseases have been characterised as a misalignment in the research system because so little research is directed towards such a large burden of disease. By focusing on one of the most extreme cases of misalignment, we highlight opportunities and potential pitfalls of targeting research towards specific social outcomes more generally. We trace how the category of neglected diseases came to prominence, largely framed as a problem to be addressed by scientific research. This mobilised R&D investment but there have been unintended consequences, particularly for broader health system strengthening and research capacity building efforts. These developments may contribute to a 'tragedy of the evaluation commons', where the effectiveness of broad remit research programs remain poorly characterised. This exacerbates a lack of evidence, relative to targeting specific diseases where the evaluation challenge is narrower. Research targeting then, is intimately tied to evaluation practice. A new research and policy agenda oriented towards broader research evaluation may support further investments not just for biomedical R&D in high-income countries, but also for researchers in other countries, for interdisciplinary, applied and social sciences, and ultimately, for poor patients.

Here, we argue that polygenic risk scores (PRSs) are different epistemic objects as compared to other biomarkers such as blood pressure or sodium level. While the latter two may be subject to variation, measured inaccurately or interpreted in various ways, blood flow has a pressure and sodium is available in a concentration that can be quantified and visualised. In stark contrast, PRSs are calculated, compiled or constructed through the statistical assemblage of genetic variants. How researchers frame and name PRSs has consequences for how we interpret and value their results. We distinguish between the tangible and inferential understanding of PRS and the corresponding languages of measurement and computation, respectively. The conflation of these frames obscures important questions we need to ask: what PRS seeks to represent, whether current ways of ‘doing PRS’ are optimal and responsible, and upon what we base the credibility of PRS-based knowledge claims.

A variety of social movements across the world and the political spectrum are now taking advantage of peer production mechanisms such as collaboration, co-production, and self-organisation. This essay investigates the consequences of peer production for social protest, looking at how peer production reshuffles and remediates social change activism today. It explores the convergences and tensions between peer networks and contemporary social movements ranging from informal coalitions and amorphous grouping to traditional social movement organisations. First, it traces the historical trajectory of peer production as it has come to permeate the progressive social movements of the last three decades, linking distinct approaches to organizing to technological innovation. Second, it reflects on the so-called social affordances (and constraints) of digital infrastructure and their role in fostering specific modes of creativity and convergence apt to support protest actors. Third, it explores three types of consequences of peer production for social movements, namely cultural production and norm change, collective identity, and the commons. The chapter then examines three tensions that might emerge in the process of embedding peer production mechanisms and values in instances of collective action, namely: individual vs. collective engagements, peer networks vs. social movement organizations, and self-organized vs. commercial infrastructure.

Research on Artificial Intelligence (AI) applications has spread over many scientific disciplines. Scientists have tested the power of intelligent algorithms developed to predict (or learn from) natural, physical and social phenomena. This also applies to crime-related research problems. Nonetheless, studies that map the current state of the art at the intersection between AI and crime are lacking. What are the current research trends in terms of topics in this area? What is the structure of scientific collaboration when considering works investigating criminal issues using machine learning, deep learning, and AI in general? What are the most active countries in this specific scientific sphere? Using data retrieved from the Scopus database, this work quantitatively analyzes 692 published works at the intersection between AI and crime employing network science to respond to these questions. Results show that researchers are mainly focusing on cyber-related criminal topics and that relevant themes such as algorithmic discrimination, fairness, and ethics are considerably overlooked. Furthermore, data highlight the extremely disconnected structure of co-authorship networks. Such disconnectedness may represent a substantial obstacle to a more solid community of scientists interested in these topics. Additionally, the graph of scientific collaboration indicates that countries that are more prone to engage in international partnerships are generally less central in the network. This means that scholars working in highly productive countries (e.g. the United States, China) tend to mostly collaborate domestically. Finally, current issues and future developments within this scientific area are also discussed., Comment: 25 pages, 12 figures, pre-print (currently R&R in JCSS)

3D printers are hailed as the next revolutionary technology, yet few scholars have studied whether 3D printing will decrease poverty and inequality. This paper determines the availability and accessibility of 3D printing technology in low-income communities through public libraries and gives insights on how libraries use 3D printers. By examining the 2013 Digital Inclusion Survey and conducting interviews, we found that libraries are quickly acquiring 3D printers; however, the technology is not being fully adopted by the patrons due to the lack of training, software and practical applications of the technology. Also, we found out that the cost to use a 3D printer in public libraries is relatively low, and does not prevent patrons from accessing the technology. Overall, we believe that libraries will only play a small role in providing availability and accessibility to 3D printing technology for marginalized communities.

The distribution of credit, resources and opportunities in science is heavily skewed due to unjust practices and incentives, hardwired into science's rules, guidelines and conventions. A form of resistance widely available is to break those rules. We review instances of rule-breaking in scientific authorship to allow for a redefinition of the concept of civil disobedience in the context of academic research, as well as the conditions on which the label applies. We show that, in contrast to whistleblowing or conscientious objection, civil disobedience targets science's injustice on a more systemic level. Its further development will ease critical evaluation of deviant actions as well as helping us evaluate deviance, defiance and discontent in science beyond issues of authorship. However, empirically, civil disobedience in science engenders uncertainties and disagreements on the local status of both act and label.

This study analyses the patenting activities of university science and engineering professors in Canada between 1920 and 1975. Unlike most studies on commercial activities in academia, which typically focus on the post-1980 period and on university practices, we focus on the pre-1980 period and on the individual decisions of professors to patent their inventions. Based on quantitative patent data, we show that patenting, and thus professors’ interest in the possible commercial value of their scientific discoveries made in university laboratories, was relatively common on an individual and informal basis well before the 1980s and the advent of what is now called “academic capitalism”. This contradicts the belief that before that period, universities were a kind of ivory towers in which professors isolated themselves from external influences and engaged only in pure and disinterested research.

Low public concern about anthropogenic climate change (ACC) – due in part to distrust toward the global scientific community – may decrease demand for policies aimed at mitigating and adapting to the deleterious effects of climate change. Encouragingly, though, recent public opinion research suggests that experiences with the COVID-19 pandemic has elevated trust in scientific expertise worldwide. Consequently, amid the suffering associated with global pandemic, one “silver lining” might be that trust in the scientific community attributable to COVID-19 pandemic response is spilling over to increase public acceptance of other contentious aspects of scientific consensus: such as the reality of ACC. We explore this possibility by turning to globally-representative survey data from 111 countries (N = 119,088) conducted during the COVID-19 pandemic. We show that trust medical experts’ handling of the COVID-19 pandemic is associated with increased acceptance of ACC, worldwide. These findings hold even when accounting for individuals’ broader trust in the scientific community, and therefore do not appear to be confounded by more-general orientations toward science. Problematically, though, we also show that effect of trust in medical professionals is strongest in countries experiencing the most positive change in attitudes toward the scientific community, which we demonstrate (via multivariate country-level analyses) tend to be disproportionately wealthy, and perhaps less likely to bear the deleterious and unequal effects of ACC. We conclude by discussing how this work helps elucidate the role of pandemic psychology on “post-pandemic life,” and discuss the potentially-far-reaching benefits of improving trust in medical institutions in the developing world.

What determines whether a country imports high-technology artificial intelligence (A.I.) products from the United States and China? Over the last decade, a growing body of literature began focusing on regime types and argue that authoritarian countries tend to import A.I. from China, whereas democratic countries from the United States. In this study, we test this regime-type hypothesis and find that both the US and China export to authoritarian and democratic countries alike, with China exporting to a larger number of countries. By employing multinomial logit with three leading A.I. trade datasets from Stanford University, Carnegie Endowment and World Bank, we find that Chinese A.I. exports are not driven by regime type, whereas American exports are. US A.I. exports are geared towards a smaller market of wealthy nations, whereas China supplies to a broader market that is made up of a variety of regime types and GDP levels. Furthermore, we find that more countries import surveillance and policing-related A.I. products from the United States, compared to China, debunking a common mainstream view. We conclude by arguing military spending and GDP per capita are two of the strongest determinants of US A.I. exports, while a robust export pattern doesn’t emerge with Chinese A.I.

Despite recent efforts to understand and improve work environments, motivated by the need of designers and stakeholders to grasp their social and spatial dynamics –and better respond to users’ needs– co-working spaces remain an under-investigated typology of workspace. These community-driven workplaces differ in many ways from traditional offices, however, existing studies on office spaces aid the design of a research tailored to enquire into this sub-type. The development of a methodological framework for the analysis of co-working spaces is one of the main objectives of this thesis. Space syntax theory guides the exploration of this type of complex building, an evidence-based approach that is demonstrated here to have a significant contribution to the understanding of the built environment and social phenomena. By systematically observing human behaviour in space and performing analytical models of it, this research investigates the social dimensions of collaboration: a progressive consideration of collaboration as a practice that begins with spatial awareness of others, potentially leads to interaction, and ultimately gives the affordance for collaboration. The focus is on the potential of co-working spaces to facilitate professional collaboration between independent yet co-located workers. Through the study of a co-working space in London, this research has found that interaction and collaboration are complex behaviours that can be better understood through the combination of analytical tools derived from space syntax theory and social networks analysis, an innovative approach to interpret and represent spatial data applied to co-working spaces.

Books are important in the social sciences. Monographs and edited books allow for presenting original research based on methodologies or forms of collaboration that the format of the journal article does not serve as appropriately. Books are also used to engage directly with society. This chapter first introduces book publishing in the social sciences as a diversity of genres, purposes, and audiences. We then limit the scope to peer-reviewed scholarly book publishing and describe how publication patterns differ among the disciplines of the social sciences in the dimensions of books versus journal articles and national versus international publishing. Then we focus on the structure of the scholarly book publishing market with particular attention to developments towards open access publishing. The chapter ends with our suggestions for principles that can guide proper evaluation of book publishing in the social sciences.

The paper is focused on practical advice for the use of bibliometrics in research assessment in the social sciences. Guidelines are presented from three official sources of advice with a particular focus on individual-level assessments of applications for positions, promotions, and external funding. General problems with applying bibliometrics in evaluations of the social sciences are also discussed, as well as the specific problems with using the Journal Impact Factor and the H-Index. The conclusion is not that bibliometrics should be avoided in research assessment of social scientists. Used with care and competence, bibliometrics can be a valuable extra source of information, but not replace judgement in research evaluation.

The paper describes the full range of publishing and its purposes in the social sciences – from scholarly publishing via professional communication to societal interaction in public media – and how it is represented in five different contexts for research evaluation and funding. The five contexts are: applications for external project funding, applications for positions or promotions, indicator-based institutional funding systems, summative organizational evaluation systems, and formative organizational evaluation systems. The chapter provides a critical discussion of how publications from the social sciences may be filtered out or placed in predetermined hierarchies in these evaluation and funding contexts, and also of how the evaluation and funding procedures can be improved to appropriately represent social science research and publishing.

Literature shows that, facing the neo-liberal definition of academic excellence, early career investigators (ECIs) in the social sciences and the humanities (SSH) have developed particular professional identities and behaviours towards the requirements of the academic career. Specificities of the SSH make the compliance to the assessment procedures of the “neo-liberal university” particularly challenging. Furthermore ECIs in the SSH are caught in an unprecedented “triple bind”. While pursuing their post-doctoral career in the context of the neo-liberal university, they are still academically trained in the disciplinary and collegial values of the “traditional university”. Although most career rewards and evaluation criteria are bound to the neo-liberal university, researchers now in the early stages of their career also constitute the first generation of academics to be exposed to the new requirements of the “open university”, through the Open Science policies and the Impact Agenda. In such context of uncertainty and conflicting rationalities, more efficient “early career building information ecosystems” should be put in place within academia. We also recommend to better integrate ECIs in the design and implementation of research evaluation principles and processes.

International audience; Agriculture is considered to be a vital aspect of Algeria's national economy and rural development. Achieving sustainable agricultural production, generating employment, reducing imports and minimising post-harvest crops losses are the major objectives of the Algerian government. However, based on the evaluation of existing policies, this study found that poor governance is hampering the agriculture sector, particularly in terms of management of financial resources, where most financial investments are made only for short-term gains. The lack of awareness about the importance of post-harvest practices and lack of using modern technology threaten the growth of this sector. Adopting sound post-harvest methods can reduce food losses and wastage in every stage of the food supply chain, and integration of modern techniques, skilled labour, and education training systems are very important if agriculture in Algeria is to progress.

Epidemiology is one of the foundational subjects of public health sciences that is widely taught in academic and non-academic settings. Considering a growing interest in epidemiology in diverse learners, the scholarly community should learn and use effective strategies for teaching epidemiologic concepts and methods. This article reviewed the existing literature and explored useful approaches for teaching epidemiology such as determining the scope of teaching epidemiology for learners with varying learning needs and interests, using conceptual frameworks, allocating academic resources, using realistic epidemiologic studies, deploying innovative educational technologies, strengthening mentoring capacities, using problem-solving practices, promoting experiential and team-based learning, developing academia-practice partnerships, and facilitating continued epidemiologic education. These strategies should be contextualized based on the academic and practical needs of the learners in different contexts. Moreover, implementation research on epidemiologic education is recommended for better understanding the operational challenges and opportunities for teaching-learning practices. Lastly, inclusive and collaborative approaches should be adopted to ensure epidemiologic education and practice continuum that may improve public health policymaking and outcomes.

Technological advances embedded within algorithmic decision systems are being deployed every day. Some of these investments are unquestionably worthwhile, while some others prioritize commercialization of technology ahead of societal impact. The article uses a real-world case from the healthcare sector to demonstrate the design and governance shortfalls of an algorithmic tool through its lifecycle. The healthcare sector sits on a mine of data, making it one of the most lucrative fields for big data–based analytics. However, the remunerative healthcare sector is particularly sensitive to the quality of data and algorithmic design decisions, making it paramount for all stakeholders to safely and ethically develop, deploy and implement the algorithmic tools. Otherwise, these systems can have detrimental effects on the life, well-being, and safety of patients. The authors provide guidance on responsible and sustainable deployment practices applicable across industries. The systematic dissection of this case can be applied to different systems across different domains like employment, credit scoring, housing, education, criminal justice, and many others. Every business automating and streamlining processes and core functions through digital transformation needs to implement new accountability and governance mechanisms and invest in the inevitable culture change necessary.

The term ‘radiophobia’ has been a cornerstone in the nuclear discourse over the past 70 years, and has been used extensively to dismiss fears of radiation as being emotional overreactions to a risk that is actuarially very low, stemming from public ignorance. Despite its longevity in nuclear discourse, little attention has been afforded to the term, its history, and the factors that underpin the extreme divergence in risk perception that the term de facto refers to, threatening to severely hamper any efforts to redress said divergence. This article will explore these factors, mostly sociopsychological in nature, and conclude that the powerful affective imagery associated with radiation, compounded by various heuristics and biases, renders public discomfort with ionising radiation from nuclear power plants rational – despite the actuarial safety record of nuclear energy globally. The article will note that. whilst its often ostracising usage towards the public should render the term obsolete, radiophobia can still be regarded as a useful concept to try and explain the extreme risk perception divergence that exists between nuclear experts and the public. In order for a more constructive discourse, a paradigm shift that acknowledges the complex historical and sociopsychological factors that have shaped radiation into becoming a uniquely feared process will be required. Such an acknowledgement will likely be a prerequisite for any efforts towards normalising humanity’s relationship with radiation, and would require considerable changes in communication practices.

Proposals for slowing climate change by reflecting sunlight back to space, known as solar geoengineering (SG), are gaining traction in climate policy. Given SG’s capacity to slow warming without reducing carbon emissions, prominent criticism suggests that it will enable fossil fueled business-as-usual. This assessment is not without merit, yet the primary funders of SG research do not emanate from fossil capital. We analyze sources of funding for SG research, finding close ties to financial and technological capital as well as a number of billionaire philanthropists. These corporate sectors and associated philanthropies comprise part of “climate capital” – the fraction of the capitalist class aligned with climate action. We argue that SG is being positioned as a tactic for enabling incremental, market-driven decarbonization, explore key institutions advocating this approach in US climate policy, and conclude that SG is poised to serve as a tool for class compromise between fossil and climate capital.

Scientific conferences are not only sites of knowledge exchange and networking. They are also spaces of valuation that are constitutive of epistemic cultures. At conferences, scholars (re-) negotiate what counts as good research, what kind of scholarship is considered valuable and which epistemic properties matter for their field. This negotiation sometimes happens explicitly, but more often through evaluative acts: statements of reasoning and justification, questions and remarks, and evaluative emotional utterances that include literal and figurative expressions of appreciation, scepticism, rejection, etc. Combining conference ethnography with a pragmatic approach borrowing insights from linguistics offers a way to identify and interpret such evaluative acts in conference talk. An analysis of data from the 3rd International Forest Policy Meeting (IFPM3), a virtual event with participants from across the globe, serves as illustrative case. Text materials generated through observing participation (field notes, transcripts, chat comments and abstracts) show how forest policy researchers ascribe worth to studies characterised by methodical rigour and praxis orientation, and guided by an objectivistic ideal of science. However, the latter was also challenged by panelists who enthusiatically appraised reflexive research that acknowledged the role of emotions in knowledge production.The IFPM3 case shows that conferences offer a unique space for observing academic valuation practice. Exploring how scholars enact values through conference discourse will not only help to better understand the specificities of particular research fields and their epistemic cultures. It can also more generally enhance the understanding of how social and epistemic levels in science intersect.

El objetivo en estas páginas es desarrollar un cartografiado de las controversias que atraviesan las publicaciones en revistas científicas a partir del despliegue de las propuestas de la teoría del actor-red. Contextualizaremos en primer lugar el lugar central que ha sido otorgado al artículo científico como formato predilecto de publicación científica, entendiendo cómo se sitúa en un mapa con respecto de los diferentes actantes relevantes que intervienen prominentemente en la producción científica. Tras situar la caja negra de las publicaciones en revistas científicas, la abriremos para ver cómo se construyen las publicaciones científicas, permitiéndonos cartografiar las controversias que se producen en el seno las mismas; colisiones y sinergias con respecto a tres epicentros clave: peer review, índices de impacto y propiedad intelectual. Dispositivos que son parte de un complejo entramado de posiciones y discursos diversos donde se articulan tanto los marcos más elitistas con respecto a la ciencia como los marcos contrahegemónicos más aperturistas. Desplazamientos y puntos de paso obligado concretos son apuntados como problemáticos en estos diferentes epicentros, siendo éstos las mismas bases del marco hegemónico actualmente presente en la ciencia. Este mapa nos permite por un lado describir las presentes resistencias y al mismo tiempo plantear la posibilidad de que otras formas de publicación científica son posibles.

In this chapter we first discuss how interdisciplinarity is perceived in research policy making and in applied bibliometric research. We put forward a processual view on disciplines and interdisciplinarity in the social sciences which emphasizes the changing nature of disciplines and the heterogeneity of individual fields. This view challenges the current status quo in the development of bibliometric indicators as well as qualitative research assessment exercises. We propose a stance in which the focus is shifted to the changing dynamics of the social sciences in order to develop a better understanding of interdisciplinarity. We point out that the cognitive and socio-cultural diversity of disciplines makes it difficult to transfer current disciplinary peer review practices to the evaluation of interdisciplinarity. We reiterate seven principles proposed by Klein which might guide more appropriate evaluation practices suitable for the assessment of interdisciplinarity in the social sciences.

Wikipedia, a collaborative crowd-sourced platform, is the largest, most visited online encyclopedia. Since it spreads information freely in more than 300 languages, many users, tools, and dashboards rely on its content. Hence, there is a need to maintain its fairness and completeness. However, previous research has indicated the existence of a significant gender gap in Wikipedia biographical articles. We already know that a minimal proportion of those articles portray women and there are gender asymmetries in the textual content of these articles, but little has been reported about the visual aspects (e.g., image volume or image quality) of the gender gap. Here, we analyze all biographies available on Wikipedia across 300 occupations in the ten most widely spoken languages, and undertake quantitative and qualitative analysis of gender differences in the written and visual content. The cross-lingual results indicate that (1) much of the male bias in content arises when editors select which personalities should have a Wikipedia page, (2) the trends in written and visual content are quite dissimilar, (3) men biographies tend to have more images across languages, and (4) female biographies average better visual quality. A more granular analysis is performed on English Wikipedia, distinguishing trends in occupations and qualitatively analyzing science and technology biographies. The overall results shed light on the kinds of visual biases that emerge in the collaborative creation of Wikipedia and yield guidelines for future management of contributions on the platform.

Assaults on science have led scientists to demand “politics-free/values-free” science that safeguards science against error by grounding it in “politically neutral” evidence. Considering racial disparities in lead poisoning, HIV/AIDS, and COVID-19, we show the solution is doomed. Politically charged beliefs are essential for assessing public-health research; thus, the beliefs’ truth affects the research's accuracy. However, science's sociopolitical uses systematically distort politically charged beliefs. Since errors assimilate into our scientific corpus and inform new hypotheses, scientists need accurate sociopolitical theories of distorting forces to identify errors. Analyzing Black-Panther opposition to violence research, we argue since racial disparities structure society and science has been distorted to buttress racial inequities, knowledgeable anti-racist scientists exert corrective forces on research. They hold accurate politically charged beliefs about sociopolitical forces shaping science and health, and are committed to eradicating distortions. Thus, rather than quarantining politically charged beliefs, scientists should sharpen their sociopolitical theories and normative commitments.

The prioritisation of research funding towards a small elite of researchers and research topics of "strategic" importance are becoming a norm across national research systems. Researchers are increasingly worried that such steering hampers the diversity of scientific approaches and problems addressed. However, the effects of increased steering of who and what receives research funds are not well known. I use evidence from 65,000 research grants awarded by seven research councils in the United Kingdom and fifteen Danish research funders to investigate how strong funding concentration and thematic targeting leads to less topical diversity. Researchers in the very top of the funding distribution primarily investigate topics and disciplines with the most funding success, and research output form targeted funding schemes overlaps with that from investigatorledgrants. Moreover, priorities from private funders line up with the type of researchfunded by public research councils. The findings highlight how steering through funding decisions can multiply

Understanding the artificiality of belief is crucial for the image it generates regarding task performance in the course of problem-solving. This paper examines the contribution of the artificial as a model of human intervention and its relationship to a model of human participation. Specifically, it details the logical differences underlying how belief operationalizes the perception of complexity and its effects on task performance in human and machine problem-solving. Three configurations of artificiality are presented to explain these differences and their effects on the relationship between representation and computation in problem-solving. The first describes the “natural artifact” that arises from a symbolic model of intelligence and the design of a maze. The second describes the “natural artifact” that arises from a sub-symbolic model of intelligence and the design of a mold. The third examines how a hybrid model of intelligence requires “socio-cognitive artifacts” in which a means of adaptation is primarily mediated by discourse rather than design. In doing so, the paper examines how momentary beliefs explain the situational rationality of task performance. The paper concludes with a commentary on the requisites of artificial intelligibility in machine problem-solving.

Studies of the political power of economic knowledge have tended to foreground the role of causal claims in the form of grand theories or more narrow findings produced by experimental methods. In contrast, scholars have paid relatively little attention to the role of economic experts' descriptions. This article highlights one category of influential, quantitative descriptive claim: stylized facts. Stylized facts are simple empirical regularities in need of explanation. Focusing on the example of the gender wage gap in the United States, this article showcases how stylized facts travel into political debates, and how the choices made in characterizing an aspect of economic life (such as controlling for full-time work, but little else) interact with social movement activism, and folk understandings of economic life shaped by legal consciousness. The gender wage gap was first calculated in the 1950s, but did not take on special importance until the 1960s-1970s when feminists rallied around the statistic as a useful aggregate measure of women's economic disempowerment. Academics soon followed, and sociologists and economists began to publish studies documenting trends in the gap and trying to account for its sources. The comparable worth movement of the 1980s explicitly argued that the wage gap resulted from occupational segregation and the devaluation of women's work. As that movement faltered in the late 1980s, the gender wage gap became increasingly understood through the lens of women's choices and tradeoffs between work and family, and occupational segregation dropped out of the narrative, even as academics documented the persistent importance of segregation in explaining the remaining gap. Throughout this period, the gap was frequently misunderstood or misrepresented as reflecting the narrow sort of same-job, different-pay discrimination made illegal by the 1963 Equal Pay Act, adding confusion to the public debate over women's economic position. These dynamics showcase how technical choices made in the identification of stylized facts, such as statistical controls, are simultaneously deeply political choices.

Evaluation systems have been long criticized for abusing and misusing bibliometric indicators. This has created a culture by which academics are constantly exposing their daily work to the standards they are expected to perform. In this study, we investigate whether researchers’ own values and expectations are in line with the expectations of the evaluation system. We conduct a multiple case study of five departments in two Dutch universities to examine how they balance between their own valuation regimes and the evaluation schemes. For this, we combine curriculum analysis with a series of semi-structured interviews. We propose a model to study the diversity of academic activities and apply it to the multiple case study to understand how such diversity is shaped by discipline and career stage. We conclude that the observed misalignment is not only resulting from an abuse of metrics but also by a lack of tools to evaluate performance in a contextualized and adaptable way.

The Covid-19 pandemic initially led to high demands for scientific expertise, while at the same time scientific results, for example in the form of preprints, being widely and sometimes critically discussed in public almost as soon as they were published. It is an open question how Scientists react and adopt to the changed situation. With data from the (German) Scientists Survey, it is possible to map the scientists' involvement in the pandemic - across academic positions and disciplines. Our results show that scientists from all disciplines are involved in corona-related research, have started or acquired projects and already published with relation to COVID-19. Social Sciences are even more involved than e.g. life science. Gender effects emerge I such a way that women actually less rapidly adopt to the new situation.

Background Sexually Transmitted Infections, including Neisseria gonorrhoeae (NG) and Chlamydia trachomatis (CT), continue to be a global health problem. Increased access to point-of-care-tests (POCTs) could help detect infection and lead to appropriate management of cases and contacts, reducing transmission and development of reproductive health sequelae. Yet diagnostics with good clinical effectiveness evidence can fail to be implemented into routine care. Here we assess values beyond clinical effectiveness for molecular CT/NG POCTs implemented across diverse routine practice settings. Methods We conducted a systematic review of peer-reviewed primary research and conference abstract publications in Medline and Embase reporting on molecular CT/NG POCT implementation in routine clinical practice until 16th February 2021. Results were extracted into EndNote software and initially screened by title and abstract by one author according to the inclusion and exclusion criteria. Articles that met the criteria, or were unclear, were included for full-text assessment by all authors. Results were synthesised to assess the tests against guidance criteria and develop a CT/NG POCT value proposition for multiple stakeholders and settings. Findings The systematic review search returned 440 articles; 28 were included overall. The Cepheid CT/NG GeneXpert was the only molecular CT/NG POCT implemented and evaluated in routine practice. It did not fulfil all test guidance criteria, however, studies of test implementation showed multiple values for test use across various healthcare settings and locations. Our value proposition highlights that the majority of values are setting-specific. Sexual health services and outreach services have the least overlap, with General Practice and other non-sexual health specialist services serving as a “bridge” between the two. Conclusions Those wishing to improve CT/NG diagnosis should be supported to identify the values most relevant to their settings and context, and prioritise implementation of tests that are most closely aligned with those values.

In this paper, we attempt to philosophically eliminate the conceptual problems in develop-ing affective artificial agents, and then put forward an industry and research direction called Raw Social AI. We first provide a set of laws for affective concepts understanding, and then suggest that we should build unconscious concepts with uncertainty. We address the problem of qualia supply, and discuss how to implement the initiative of affective agents. We suggest that initiative be the cue of utility of affective agents. We advocate that the initiative of affective agents must be realized as social services. Raw social AI is about using AI to record, model and predict people's emotional reactions in the real or virtual world. It is necessary for us to establish the infrastructure of raw social AI.

This chapter draws on the literature reviews of 387 books and articles about sex differences to argue that the scientific authority of the sex binary is often rhetorically established through misleading, revisionist histories of the field.

This article draws on an ethnographic investigation of product development at an engineering organization to examine the struggle faced by designers in justifying design proposals when cooperating with engineers and managers. Frustrated by the priority given to numbers over other modes of evaluation traditionally used in design, designers in this case developed and mobilized their own evaluation device to quantitatively prove the validity and worth of their work. This quasi-parodic form of evaluation enables designers to criticize and influence strategic project decisions. At the same time, this cynical act of resistance paradoxically endorses the quantitative approach and undermines designers’ own professional expertise as a valid way of conceiving worth, which ultimately renders this move more indeterminate than what a distinction between resistance and conformity denotes. Overall, the study adds to our understanding of how modes and principles of justification typically embraced by professional groups can be unsettled by attempts to protect them. In doing so, it brings to light the ambivalent nature of resistance through a cynical embrace of quantification.

The recently constituted association stsing offers scholars a new platform to “do” STS in and through Germany (therefore the wording stsing). Specific about this platform is its creative and open understanding of collaboration on the one hand and critical reflection of national, international, institutional, and intergenerational challenges of STS research on the other. Germany’s specific funding and institutional structure is of central importance to stsing. At the same time, stsing is responding to the internationally integrated practices of STS. It addresses the frictions between local bureaucracies and hierarchies as well as global doings and (self-)understandings of STS. We briefly unfold the (hi)story of stsing: a process of negotiating imaginaries, institutional settings, conflicts and mutual recognition. The challenge is to open spaces and account for the heterogeneous people and disciplines engaged with the ideas, methodologies and politics of STS. stsing experiments with configuring infrastructures and organisational policies to support transnationally and interdisciplinarily oriented STS research practice. This experimentation works across generations and encounters troubles between and within generations of STS.

Research blogging has received a rather good amount of attention from the scholarly literature, but not in the domain of astrophysics. In the present paper, three active astrophysicists’ blogs have been chosen from a previously retrieved much wider corpus and analyzed against the pivotal theory of identity shaping in an online setting. The study, which is essentially mixed-methods, has built on Susan Herring’s definition of computer-mediated conversation and focusses on content analysis as well as on content-based interaction (comments and replies per subject). Special care was taken on ensuring bloggers’ and commenters’ anonimity, in compliance with the British Psychological Society Ethics Guidelines. These blogs’ conversational capacity has emerged and the hypothesis of some degree of professional identity negotiation results to be confirmed, with implications on the invisible colleges. The context is that of an interdisciplinary, provisional junction between ground-based linguistic fieldwork in a 2.0 online setting and the search for appropriate theoretical frameworks about unconscious or semi-conscious aims of communication in a scholarly environment.