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There is a well-documented gap between the observed number of works produced by women and by men in science, with clear consequences for the retention and promotion of women 1 . The gap might be a result of productivity differences 2 – 5 , or it might be owing to women’s contributions not being acknowledged 6 , 7 . Here we find that at least part of this gap is the result of unacknowledged contributions: women in research teams are significantly less likely than men to be credited with authorship. The findings are consistent across three very different sources of data. Analysis of the first source—large-scale administrative data on research teams, team scientific output and attribution of credit—show that women are significantly less likely to be named on a given article or patent produced by their team relative to their male peers. The gender gap in attribution is present across most scientific fields and almost all career stages. The second source—an extensive survey of authors—similarly shows that women’s scientific contributions are systematically less likely to be recognized. The third source—qualitative responses—suggests that the reason that women are less likely to be credited is because their work is often not known, is not appreciated or is ignored. At least some of the observed gender gap in scientific output may be owing not to differences in scientific contribution, but rather to differences in attribution. The difference between the number of men and women listed as authors on scientific papers and inventors on patents is at least partly attributable to unacknowledged contributions by women scientists.

ObjectivesTo investigate the relationship between teamwork and clinical performance and potential moderating variables of this relationship.DesignSystematic review and meta-analysis.Data sourcePubMed was searched in June 2018 without a limit on the date of publication. Additional literature was selected through a manual backward search of relevant reviews, manual backward and forward search of studies included in the meta-analysis and contacting of selected authors via email.Eligibility criteriaStudies were included if they reported a relationship between a teamwork process (eg, coordination, non-technical skills) and a performance measure (eg, checklist based expert rating, errors) in an acute care setting.Data extraction and synthesisModerator variables (ie, professional composition, team familiarity, average team size, task type, patient realism and type of performance measure) were coded and random-effect models were estimated. Two investigators independently extracted information on study characteristics in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.ResultsThe review identified 2002 articles of which 31 were included in the meta-analysis comprising 1390 teams. The sample-sized weighted mean correlation was r =0.28 (corresponding to an OR of 2.8), indicating that teamwork is positively related to performance. The test of moderators was not significant, suggesting that the examined factors did not influence the average effect of teamwork on performance.ConclusionTeamwork has a medium-sized effect on performance. The analysis of moderators illustrated that teamwork relates to performance regardless of characteristics of the team or task. Therefore, healthcare organisations should recognise the value of teamwork and emphasise approaches that maintain and improve teamwork for the benefit of their patients.

Teamwork is indispensable in human societies. However, due to the complexity of studying ecologically valid synchronous team actions, requiring multiple members and a range of subjective and objective measures, the mechanism underlying the impact of synchrony on team performance is still unclear. In this paper, we simultaneously measured groups of nine-participants' (total N = 180) fronto-temporal activations during a drum beating task using functional near infrared spectroscopy (fNIRS)-based hyperscanning and multi-brain network modeling, which can assess patterns of shared neural synchrony and attention/information sharing across entire teams. Participants (1) beat randomly without considering others' drumming (random condition), (2) actively coordinated their beats with the entire group without other external cue (team-focus condition), and (3) beat together based on a metronome (shared-focus condition). Behavioral data revealed higher subjective and objective measures of drum-beat synchronization in the team-focus condition, as well as higher felt interdependence. The fNIRS data revealed that participants in the team-focus condition also showed higher interpersonal neural synchronization (INS) and higher Global Network Efficiency in their left TPJ and mPFC. Higher left TPJ Global Network Efficiency also predicted higher actual synchrony in the team-focus condition, with an effect size roughly 1.5 times that of subjective measures, but not in the metronome-enabled shared-focus condition. This result suggests that shared mental representations with high efficiency of information exchange across the entire team may be a key component of synchrony, adding to the understanding of the actual relation to team work.

Economics research is increasingly performed in teams, and team-authored work has a large and increasing impact advantage. This article considers the benefits and costs of this \"rise of teams.\" Among its benefits, teamwork allows individuals to aggregate knowledge in productive and novel ways. For example, as knowledge accumulates over time, individuals become narrower in their expertise, and teamwork is a natural organizational approach to aggregating expertise and maintaining one's reach. But teamwork also brings costs. For example, teamwork divides and obscures credit, which is central to the reward system of science. By clouding credit assignment, teamwork can undermine individual career progression and exacerbate issues of bias. In addressing the rise of teamwork, this paper further considers institutional innovations, especially those inspired by the hard sciences, that can help limit the costs teamwork imposes while realizing the benefits.

Large language models (LLM) have been a catalyst for the public interest in artificial intelligence (AI). These technologies perform some knowledge-based tasks better and faster than human beings. However, whether AIs can correctly assess social situations and devise socially appropriate behavior, is still unclear. We conducted an established Situational Judgment Test (SJT) with five different chatbots and compared their results with responses of human participants ( N  = 276). Claude, Copilot and you.com’s smart assistant performed significantly better than humans in proposing suitable behaviors in social situations. Moreover, their effectiveness rating of different behavior options aligned well with expert ratings. These results indicate that LLMs are capable of producing adept social judgments. While this constitutes an important requirement for the use as virtual social assistants, challenges and risks are still associated with their wide-spread use in social contexts.

How is credit for group work allocated when individual contributions are not observed? I use data on academics' publication records to test whether demographic traits like gender influence how credit is allocated under such uncertainty. While solo-authored papers send a clear signal about ability, coauthored papers are noisy, providing no specific information about each contributor's skills. I find that men are tenured at roughly the same rate regardless of coauthoring choices. Women, however, are less likely to receive tenure the more they coauthor. The result is much less pronounced among women who coauthor with other women.

Newcomers’ seamless onboarding is important for open collaboration communities, particularly those that leverage outsiders’ contributions to remain sustainable. Nevertheless, previous work shows that OSS newcomers often face several barriers to contribute, which lead them to lose motivation and even give up on contributing. A well-known way to help newcomers overcome initial contribution barriers is mentoring. This strategy has proven effective in offline and online communities, and to some extent has been employed in OSS projects. Studying mentors’ perspectives on the barriers that newcomers face play a vital role in improving onboarding processes; yet, OSS mentors face their own barriers, which hinder the effectiveness of the strategy. Since little is known about the barriers mentors face, in this paper, we investigate the barriers that affect mentors and their newcomer mentees. We interviewed mentors from OSS projects and qualitatively analyzed their answers. We found 44 barriers: 19 that affect mentors; and 34 that affect newcomers (9 affect both newcomers and mentors). Interestingly, most of the barriers we identified (66%) have a social nature. Additionally, we identified 10 strategies that mentors indicated to potentially alleviate some of the barriers. Since gender-related challenges emerged in our analysis, we conducted nine follow-up structured interviews to further explore this perspective. The contributions of this paper include: identifying the barriers mentors face; bringing the unique perspective of mentors on barriers faced by newcomers; unveiling strategies that can be used by mentors to support newcomers; and investigating gender-specific challenges in OSS mentorship. Mentors, newcomers, online communities, and educators can leverage this knowledge to foster new contributors to OSS projects.

We investigate learning at the workplace. To do so, we use German administrative data that contain information on the entire workforce of a sample of establishments. We document that having more-highly-paid coworkers is strongly associated with future wage growth, particularly if those workers earn more. Motivated by this fact, we propose a dynamic theory of a competitive labor market where firms produce using teams of heterogeneous workers that learn from each other. We develop a methodology to structurally estimate knowledge flows using the full-richness of the German employer-employee matched data. The methodology builds on the observation that a competitive labor market prices coworker learning. Our quantitative approach imposes minimal restrictions on firms’ production functions, can be implemented on a very short panel, and allows for potentially rich and flexible coworker learning functions. In line with our reduced-form results, learning from coworkers is significant, particularly from more knowledgeable coworkers. We show that between 4 and 9% of total worker compensation is in the form of learning and that inequality in total compensation is significantly lower than inequality in wages.

Sociomotor theory – an extension of ideomotor theory – suggests that actions can also be represented in terms of the effects they elicit from others. But what if those others violate one’s action effect anticipations? Here, we introduce a novel joint goal-setting paradigm to investigate effects of co-actors’ occasional and overall unreliability on an individual’s goal selection. In a first step, the participant moved a target halfway from the bottom center to the top left or right corner of the computer screen. In the second step, the co-actor moved the target to its final left or right position. In a learning block, the co-actor always continued the participant’s target movements. In the test block(s), the co-actor produced congruent action effects in 50% (unreliable) vs. 80% (reliable co-actor) of the trials. Experiment 1 consisted of one (between-participants), Experiment 2 and 3 of two (within-participants) test blocks; in Experiment 3, the co-actor changed between blocks. Results of Experiments 1 and 3 reveal that participants repeated their corner choice more often after incongruent trials, but only when the co-actor was generally reliable. Implications in terms of sociomotor action control and joint action are discussed.