Does the use of unusual combinations of datasets contribute to greater scientific impact?

Scientific datasets play a crucial role in contemporary data-driven research, as they allow for the progress of science by facilitating the discovery of new patterns and phenomena. This mounting demand for empirical research raises important questions on how strategic data utilization in research projects can stimulate scientific advancement. In this study, we examine the hypothesis inspired by the recombination theory, which suggests that innovative combinations of existing knowledge, including the use of unusual combinations of datasets, can lead to high-impact discoveries. Focusing on social science, we investigate the scientific outcomes of such atypical data combinations in more than 30,000 publications that leverage over 5,000 datasets curated within one of the largest social science databases, Interuniversity Consortium for Political and Social Research. This study offers four important insights. First, combining datasets, particularly those infrequently paired, significantly contributes to both scientific and broader impacts (e.g., dissemination to the general public). Second, infrequently paired datasets maintain a strong association with citation even after controlling for the atypicality of dataset topics. In contrast, the atypicality of dataset topics has a much smaller positive impact on citation counts. Third, smaller and less experienced research teams tend to use atypical combinations of datasets in research more frequently than their larger and more experienced counterparts. Last, despite the benefits of data combination, papers that amalgamate data remain infrequent. This finding suggests that the unconventional combination of datasets is an underutilized but powerful strategy correlated with the scientific impact and broader dissemination of scientific discoveries.

Democratizing social scientists' impact on federal policy: Using the evidence act to help government and ourselves.

It is common for social scientists to discuss the implications of our research for policy. However, what actions can we take to inform policy in more immediate and impactful ways, regardless of our existing institutional affiliations or personal connections? Focusing on federal policy, I suggest that the answer requires understanding a basic coordination problem. On the government side, the Foundations of Evidence-based Policymaking Act (2018) requires that large federal agencies pose, communicate, and answer research questions related to their effects on people and communities. This advancement has opened the black box of federal agency policy priorities, but it has not addressed capacity challenges: These agencies often do not have the financial resources or staff to answer the research questions they pose. On the higher education side, we have more than 150,000 academic social scientists who are knowledge producers and educators by training and vocation. However, especially among those in disciplinary departments, or those without existing institutional or personal connections to federal agencies, we often feel locked out of federal policymaking processes. In this article, I define the coordination problem and offer concrete actions that the academic and federal government communities can take to address it. I also offer leading examples of how academics and universities are making public policy impact possible in multiple governmental spheres. I conclude by arguing that both higher education institutions and all levels of government can do more to help academic social scientists put our knowledge to work in service of the public good.

Can Generative AI improve social science?

Generative AI that can produce realistic text, images, and other human-like outputs is currently transforming many different industries. Yet it is not yet known how such tools might influence social science research. I argue Generative AI has the potential to improve survey research, online experiments, automated content analyses, agent-based models, and other techniques commonly used to study human behavior. In the second section of this article, I discuss the many limitations of Generative. I examine how bias in the data used to train these tools can negatively impact social science research-as well as a range of other challenges related to ethics, replication, environmental impact, and the proliferation of low-quality research. I conclude by arguing that social scientists can address many of these limitations by creating open-source infrastructure for research on human behavior. Such infrastructure is not only necessary to ensure broad access to high-quality research tools, I argue, but also because the progress of AI will require deeper understanding of the social forces that guide human behavior.

Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale.

Political discourse is the soul of democracy, but misunderstanding and conflict can fester in divisive conversations. The widespread shift to online discourse exacerbates many of these problems and corrodes the capacity of diverse societies to cooperate in solving social problems. Scholars and civil society groups promote interventions that make conversations less divisive or more productive, but scaling these efforts to online discourse is challenging. We conduct a large-scale experiment that demonstrates how online conversations about divisive topics can be improved with AI tools. Specifically, we employ a large language model to make real-time, evidence-based recommendations intended to improve participants' perception of feeling understood. These interventions improve reported conversation quality, promote democratic reciprocity, and improve the tone, without systematically changing the content of the conversation or moving people's policy attitudes.

Founder personality and entrepreneurial outcomes: A large-scale field study of technology startups.

Technology startups play an essential role in the economy-with seven of the ten largest companies rooted in technology, and venture capital investments totaling approximately $300B annually. Yet, important startup outcomes (e.g., whether a startup raises venture capital or gets acquired) remain difficult to forecast-particularly during the early stages of venture formation. Here, we examine the impact of an essential, yet underexplored, factor that can be observed from the moment of startup creation: founder personality. We predict psychological traits from digital footprints to explore how founder personality is associated with critical startup milestones. Observing 10,541 founder-startup dyads, we provide large-scale, ecologically valid evidence that founder personality is associated with outcomes across all phases of a venture's life (i.e., from raising the earliest funding round to exiting via acquisition or initial public offering). We find that openness and agreeableness are positively related to the likelihood of raising an initial round of funding (but unrelated to all subsequent conditional outcomes). Neuroticism is negatively related to all outcomes, highlighting the importance of founders' resilience. Finally, conscientiousness is positively related to early-stage investment, but negatively related to exit conditional on funding. While prior work has painted conscientiousness as a major benefactor of performance, our findings highlight a potential boundary condition: The fast-moving world of technology startups affords founders with lower or moderate levels of conscientiousness a competitive advantage when it comes to monetizing their business via acquisition or IPO.

Incentivizing free riders improves collective intelligence in social dilemmas.

Collective intelligence challenges are often entangled with collective action problems. For example, voting, rating, and social innovation are collective intelligence tasks that require costly individual contributions. As a result, members of a group often free ride on the information contributed by intrinsically motivated people. Are intrinsically motivated agents the best participants in collective decisions? We embedded a collective intelligence task in a large-scale, virtual world public good game and found that participants who joined the information system but were reluctant to contribute to the public good (free riders) provided more accurate evaluations, whereas participants who rated frequently underperformed. Testing the underlying mechanism revealed that a negative rating bias in free riders is associated with higher accuracy. Importantly, incentivizing evaluations amplifies the relative influence of participants who tend to free ride without altering the (higher) quality of their evaluations, thereby improving collective intelligence. These results suggest that many of the currently available information systems, which strongly select for intrinsically motivated participants, underperform and that collective intelligence can benefit from incentivizing free riding members to engage. More generally, enhancing the diversity of contributor motivations can improve collective intelligence in settings that are entangled with collective action problems.

Computational Social Psychology.

Social psychologists attempt to explain how we interact by appealing to basic principles of how we think. To make good on this ambition, they are increasingly relying on an interconnected set of formal tools that model inference, attribution, value-guided decision making, and multi-agent interactions. By reviewing progress in each of these areas and highlighting the connections between them, we can better appreciate the structure of social thought and behavior, while also coming to understand when, why, and how formal tools can be useful for social psychologists.

Why postmortems fail.

Most high-profile disasters are followed by demands for an investigation into what went wrong. Even before they start, calls for finding the missed warning signs and an explanation for why people did not "connect the dots" will be common. Unfortunately, however, the same combination of political pressures and the failure to adopt good social science methods that contributed to the initial failure usually lead to postmortems that are badly flawed. The high stakes mean that powerful actors will have strong incentives to see that certain conclusions are-and are not-drawn. Most postmortems also are marred by strong psychological biases, especially the assumption that incorrect inferences must have been the product of wrong ways of thinking, premature cognitive closure, the naive use of hindsight, and the neglect of the comparative method. Given this experience, I predict that the forthcoming inquiries into the January 6, 2021, storming of the US Capitol and the abrupt end to the Afghan government will stumble in many ways.

Gender-diverse teams produce more novel and higher-impact scientific ideas.

Science's changing demographics raise new questions about research team diversity and research outcomes. We study mixed-gender research teams, examining 6.6 million papers published across the medical sciences since 2000 and establishing several core findings. First, the fraction of publications by mixed-gender teams has grown rapidly, yet mixed-gender teams continue to be underrepresented compared to the expectations of a null model. Second, despite their underrepresentation, the publications of mixed-gender teams are substantially more novel and impactful than the publications of same-gender teams of equivalent size. Third, the greater the gender balance on a team, the better the team scores on these performance measures. Fourth, these patterns generalize across medical subfields. Finally, the novelty and impact advantages seen with mixed-gender teams persist when considering numerous controls and potential related features, including fixed effects for the individual researchers, team structures, and network positioning, suggesting that a team's gender balance is an underrecognized yet powerful correlate of novel and impactful scientific discoveries.

'There's too much power in this number. It's freaking the whole response out': The views of key informants on evidence and targets to achieve hepatitis C elimination goals in Australia.

Enumeration of disease is a key management tool. Setting of targets, like for hepatitis C elimination, have deep meaning and effect. We use the case of elimination in New South Wales (NSW), Australia to examine key informants' understandings of the use of targets, and the evidence that informs them, to drive action in elimination. Twenty-eight key informants working in NSW, elsewhere in Australia and internationally in high-income countries participated in a semi-structured qualitative interview in 2022. Analysis was informed by scholarship calling for examination of the ways in which science constructs what is thought possible in action. Participants pointed to the power of quantified evidence and targets and their complex effects, and questioned the usefulness and certainty derived from these at the "pointy end" of elimination. Although a range of targets exist in global and local strategies, reaching testing targets was the assumed solution to achieving elimination. Achieving elimination was thought to require "off piste" and experimental approaches that went beyond available evidence. The different types of work that participants felt necessary for late-stage elimination may require additional metrics to explain return on investment ratios. What threshold would be used to reduce efforts in elimination was a major concern. These data indicate that understandings of the evidence underpinning elimination targets and how to achieve them are far from settled. At this point, elimination efforts may need to rely on locally produced and community-driven evidence and shift from evidence-based to evidence-making paradigm.

Recall and Appraisal of the Risks, Benefits, and Objectives of Interrupting HIV Treatment in an HIV Cure-Related Study.

The goal of HIV cure research is to either eliminate HIV from the body or durably suppress it in the absence of antiretroviral therapy (ART). This research often requires participants to interrupt ART. However, there are numerous risks associated with ART interruptions and therefore it is critical to understand how people with HIV (PWH) who participate recall the elements of consent, to safeguard their rights and welfare. Participants were recruited from the SCOPE Analytic Treatment Interruption (SCOPE-ATI: NCT04359186) study at the University of California San Francisco. We interviewed 12 SCOPE-ATI participants to assess their recall of informed consent elements and therapeutic misconception, using the Brief Informed Consent Evaluation Protocol (BICEP). Interviewees were primarily older adults, male, White, and non-Hispanic/Latinx. Their responses indicated that they understood the primary purpose of the SCOPE-ATI study to be scientific research. Nearly all participants demonstrated high recall of key elements of consent and no therapeutic misconception. We also found that the role of study staff was a major factor in participants' appraisal of risks and that associated psychosocial risks of pausing ART were of minimal concern (e.g., anxiety off ART, possible forward HIV transmission to sex partners). As HIV cure research expands, it is important to reiterate the duty of the investigative team to clearly communicate with participants about the associated risks and to assess their understanding throughout these studies.

A poetic inquiry: the role of the social sciences and humanities in revitalising AIDS.

For the past four decades, biomedical science has transformed clinical outcomes for HIV and AIDS. However, the social, economic and gendered determinants of HIV remain largely intact. The social science and humanities offer concepts and methods for articulating why these remain intractable. I used poetic inquiry - an arts-based, qualitative approach - as I reviewed literature on the "end of AIDS, and post-AIDS". As I did so, I considered what contribution the social sciences and humanities could make in moving us closer to these ideals. Several themes and found poems emerged in this reading: (1) how language oversimplifies complex social realities; (2) the voices of people living with HIV and AIDS must be included; (3) HIV and AIDS intersects with social inequalities; (4) social and structural issues are no barrier to HIV prevention and (5) the need for radical interdisciplinarity. The paper concludes that the end of AIDS requires responses that are integrated, holistic and that radically challenge our silo'd disciplinary boundaries and frames. The social sciences and humanities are key to this charge.

The scope of empowerment for conservation and communities.

Conservationists increasingly position conservation that is mutually beneficial to people and biodiversity on the promise of empowerment of people through participatory discourse, metrics, processes, and outcomes. Empowerment represents multidimensional concepts and theories that permeate the interlinking levels of power, from the psychological to the political, and social scales in which conservation operates. The multifaceted nature of empowerment makes it challenging to understand, pursue, and evaluate as a central philosophical commitment and goal-oriented practice in conservation. Moreover, definitional and methodological uncertainty may disempower interested and affected groups because they can foster conceptual assumptions that reinforce institutionalized barriers to systemic changes. Despite these complexities, there are no targeted reviews of empowerment in conservation. We conducted a scoping review of the conservation literature to synthesize the meanings and uses of empowerment in the field. We reviewed 121 of the most cited conservation articles that invoked or assessed empowerment from 1992 to 2017 to document geographic, conceptual, and methodological trends in the scales and theories of empowerment deployed by conservationists. Research claiming or assessing empowerment through conservation often focused on communities in the Global South. Most studies relied on qualitative and mixed methods (78%) collected largely from male or non-Indigenous participants. Few studies (30%) defined the 20 types of empowerment they referenced. Fewer studies (3%) applied empowerment theories in their work. Our findings show that empowerment discourse of local and Indigenous communities permeates the discourse of people-centered conservation. Yet, overreliance on empowerment's rhetorical promise and minimal engagement with theory (e.g., postcolonial theory) risks disempowering people by obscuring empowerment's foundational value to conservation and communities and oversimplifying the complex realities of people-centered conservation. Lasting change could come from more meaningful engagement with empowerment, including coproducing definitions and measures with and for disempowered social groups to tackle widespread power disparities in conservation today.

El alcance del empoderamiento para la conservación y las comunidades Resumen Con frecuencia los conservacionistas posicionan a la conservación como benéfica para las personas y la biodiversidad mediante discursos, medidas, procesos y resultados participativos que prometen el empoderamiento de la gente. El empoderamiento representa conceptos y teorías multidimensionales que permean los niveles interconectados de poder, desde el psicológico al político, y las escalas sociales en las que opera la conservación. La naturaleza multifacética del empoderamiento complica que se entienda, se dé seguimiento y se evalúe como un compromiso filosófico central y una práctica orientada hacia las metas dentro de la conservación. Además, la incertidumbre metodológica y de definición pueden restar autoridad a los grupos interesados o afectados pues pueden promover suposiciones conceptuales que refuerzan las barreras institucionales de los cambios sistémicos. A pesar de estas complejidades, no existen revisiones focalizadas del empoderamiento en la conservación. Realizamos una revisión de alcance de la literatura de conservación para sintetizar los significados y usos de la palabra empoderamiento en este campo. Revisamos 121 de los artículos sobre conservación más citados que invocaron o evaluaron el empoderamiento entre 1992 y 2017 para documentar las tendencias geográficas, conceptuales y metodológicas en las escalas y teorías del empoderamiento usadas por los conservacionistas. La mayoría de los artículos que afirmaban o evaluaban el empoderamiento por medio de la conservación se enfocaron en comunidades del Sur Global. La mayoría de los estudios dependieron de métodos cualitativos y mixtos (78%) tomados principalmente de participantes masculinos o no indígenas. Pocos estudios (30%) definieron los 20 tipos de empoderamiento que referenciaron. Todavía menos estudios (3%) aplicaron las teorías de empoderamiento a su trabajo. Nuestros descubrimientos muestran que el discurso de empoderamiento de las comunidades locales e indígenas permea el discurso de la conservación centrada en la gente. Sin embargo, depender en exceso de la promesa retórica del empoderamiento e involucrarse en lo mínimo con la teoría (p. ej.: teoría postcolonial) arriesga que la gente se pierda autoridad al oscurecer el valor fundamental que tiene el empoderamiento para la conservación y las comunidades y simplificar sobremanera las realidades complejas de la conservación centrada en las personas. El cambio duradero podría venir de involucrarse de forma más significativa con el empoderamiento, lo que incluye la coproducción de definiciones y medidas con y para los grupos sociales no empoderados para resolver la disparidad de poder que existe hoy en día en la conservación.

Bioethicists Today: Results of the Views in Bioethics Survey.

Bioethicists influence practices and policies in medicine, science, and public health. However, little is known about bioethicists' views. We recently surveyed 824 U.S. bioethicists on a wide range of ethical issues, including topics related to abortion, medical aid in dying, and resource allocation, among others. We also asked bioethicists about their demographic, religious, academic, and professional backgrounds. We find that bioethicists' normative commitments predict their views on bioethical issues. We also find that, in important ways, bioethicists' views do not align with those of the U.S. public: for instance, bioethicists are more likely than members of the public to think abortion is ethically permissible but are less likely to believe compensating organ donors is. Our demographic results indicate the field of bioethics is far less diverse than the U.S. population-less diverse even than other academic disciplines-suggesting far more work needs to be done to build an inclusive field.

The consequences of online partisan media.

What role do ideologically extreme media play in the polarization of society? Here we report results from a randomized longitudinal field experiment embedded in a nationally representative online panel survey (N = 1,037) in which participants were incentivized to change their browser default settings and social media following patterns, boosting the likelihood of encountering news with either a left-leaning (HuffPost) or right-leaning (Fox News) slant during the 2018 US midterm election campaign. Data on ≈ 19 million web visits by respondents indicate that resulting changes in news consumption persisted for at least 8 wk. Greater exposure to partisan news can cause immediate but short-lived increases in website visits and knowledge of recent events. After adjusting for multiple comparisons, however, we find little evidence of a direct impact on opinions or affect. Still, results from later survey waves suggest that both treatments produce a lasting and meaningful decrease in trust in the mainstream media up to 1 y later. Consistent with the minimal-effects tradition, direct consequences of online partisan media are limited, although our findings raise questions about the possibility of subtle, cumulative dynamics. The combination of experimentation and computational social science techniques illustrates a powerful approach for studying the long-term consequences of exposure to partisan news.

Stewardship of global collective behavior.

Collective behavior provides a framework for understanding how the actions and properties of groups emerge from the way individuals generate and share information. In humans, information flows were initially shaped by natural selection yet are increasingly structured by emerging communication technologies. Our larger, more complex social networks now transfer high-fidelity information over vast distances at low cost. The digital age and the rise of social media have accelerated changes to our social systems, with poorly understood functional consequences. This gap in our knowledge represents a principal challenge to scientific progress, democracy, and actions to address global crises. We argue that the study of collective behavior must rise to a "crisis discipline" just as medicine, conservation, and climate science have, with a focus on providing actionable insight to policymakers and regulators for the stewardship of social systems.

Postmortem memory of public figures in news and social media.

Deceased public figures are often said to live on in collective memory. We quantify this phenomenon by tracking mentions of 2,362 public figures in English-language online news and social media (Twitter) 1 y before and after death. We measure the sharp spike and rapid decay of attention following death and model collective memory as a composition of communicative and cultural memory. Clustering reveals four patterns of postmortem memory, and regression analysis shows that boosts in media attention are largest for premortem popular anglophones who died a young, unnatural death; that long-term boosts are smallest for leaders and largest for artists; and that, while both the news and Twitter are triggered by young and unnatural deaths, the news additionally curates collective memory when old persons or leaders die. Overall, we illuminate the age-old question of who is remembered by society, and the distinct roles of news and social media in collective memory formation.

Bots are less central than verified accounts during contentious political events.

Information manipulation is widespread in today's media environment. Online networks have disrupted the gatekeeping role of traditional media by allowing various actors to influence the public agenda; they have also allowed automated accounts (or bots) to blend with human activity in the flow of information. Here, we assess the impact that bots had on the dissemination of content during two contentious political events that evolved in real time on social media. We focus on events of heightened political tension because they are particularly susceptible to information campaigns designed to mislead or exacerbate conflict. We compare the visibility of bots with human accounts, verified accounts, and mainstream news outlets. Our analyses combine millions of posts from a popular microblogging platform with web-tracking data collected from two different countries and timeframes. We employ tools from network science, natural language processing, and machine learning to analyze the diffusion structure, the content of the messages diffused, and the actors behind those messages as the political events unfolded. We show that verified accounts are significantly more visible than unverified bots in the coverage of the events but also that bots attract more attention than human accounts. Our findings highlight that social media and the web are very different news ecosystems in terms of prevalent news sources and that both humans and bots contribute to generate discrepancy in news visibility with their activity.

Gender inequities in the online dissemination of scholars' work.

Unbiased science dissemination has the potential to alleviate some of the known gender disparities in academia by exposing female scholars' work to other scientists and the public. And yet, we lack comprehensive understanding of the relationship between gender and science dissemination online. Our large-scale analyses, encompassing half a million scholars, revealed that female scholars' work is mentioned less frequently than male scholars' work in all research areas. When exploring the characteristics associated with online success, we found that the impact of prior work, social capital, and gendered tie formation in coauthorship networks are linked with online success for men, but not for women-even in the areas with the highest female representation. These results suggest that while men's scientific impact and collaboration networks are associated with higher visibility online, there are no universally identifiable facets associated with success for women. Our comprehensive empirical evidence indicates that the gender gap in online science dissemination is coupled with a lack of understanding the characteristics that are linked with female scholars' success, which might hinder efforts to close the gender gap in visibility.

Shadows of wisdom: Classifying meta-cognitive and morally grounded narrative content via large language models.

We investigated large language models' (LLMs) efficacy in classifying complex psychological constructs like intellectual humility, perspective-taking, open-mindedness, and search for a compromise in narratives of 347 Canadian and American adults reflecting on a workplace conflict. Using state-of-the-art models like GPT-4 across few-shot and zero-shot paradigms and RoB-ELoC (RoBERTa -fine-tuned-on-Emotion-with-Logistic-Regression-Classifier), we compared their performance with expert human coders. Results showed robust classification by LLMs, with over 80% agreement and F1 scores above 0.85, and high human-model reliability (Cohen's κ Md across top models = .80). RoB-ELoC and few-shot GPT-4 were standout classifiers, although somewhat less effective in categorizing intellectual humility. We offer example workflows for easy integration into research. Our proof-of-concept findings indicate the viability of both open-source and commercial LLMs in automating the coding of complex constructs, potentially transforming social science research.