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1. Women’s Participation in Open Source Software: A Survey of the Literature

   https://doi.org/10.1145/3510460  

   Trinkenreich, Bianca ; Wiese, Igor ; Sarma, Anita ; Gerosa, Marco ; Steinmacher, Igor ( April 2022 , ACM Transactions on Software Engineering and Methodology)

   Women are underrepresented in Open Source Software (OSS) projects, as a result of which, not only do women lose career and skill development opportunities, but the projects themselves suffer from a lack of diversity of perspectives. Practitioners and researchers need to understand more about the phenomenon; however, studies about women in open source are spread across multiple fields, including information systems, software engineering, and social science. This paper systematically maps, aggregates, and synthesizes the state-of-the-art on women’s participation in OSS. It focuses on women contributors’ representation and demographics, how they contribute, their motivations and challenges, and strategies employed by communities to attract and retain women. We identified 51 articles (published between 2000 and 2021) that investigated women’s participation in OSS. We found evidence in these papers about who are the women who contribute, what motivates them to contribute, what types of contributions they make, challenges they face, and strategies proposed to support their participation. According to these studies, only about 5% of projects were reported to have women as core developers, and women authored less than 5% of pull-requests, but had similar or even higher rates of pull request acceptances than men. Women make both code and non-code contributions and their motivations to contribute include, learning new skills, altruism, reciprocity, and kinship. Challenges that women face in OSS are mainly social, including lack of peer parity and non-inclusive communication from a toxic culture. We found ten strategies reported in the literature, which we mapped to the reported challenges. Based on these results, we provide guidelines for future research and practice. 

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2. Influence of social and technical factors for evaluating contribution in GitHub

   https://doi.org/10.1145/2568225.2568315  

   Tsay, Jason ; Dabbish, Laura ; Herbsleb, James ( January 2014 , International Conference on Software Engineering)

   Open source software is commonly portrayed as a meritocracy, where decisions are based solely on their technical merit. However, literature on open source suggests a complex social structure underlying the meritocracy. Social work environments such as GitHub make the relationships between users and between users and work artifacts transparent. This transparency enables developers to better use information such as technical value and social connections when making work decisions. We present a study on open source software contribution in GitHub that focuses on the task of evaluating pull requests, which are one of the primary methods for contributing code in GitHub. We analyzed the association of various technical and social measures with the likelihood of contribution acceptance. We found that project managers made use of information signaling both good technical contribution practices for a pull request and the strength of the social connection between the submitter and project manager when evaluating pull requests. Pull requests with many comments were much less likely to be accepted, moderated by the submitter's prior interaction in the project. Well-established projects were more conservative in accepting pull requests. These findings provide evidence that developers use both technical and social information when evaluating potential contributions to open source software projects 

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3. Let's talk about it: evaluating contributions through discussion in GitHub

   https://doi.org/10.1145/2635868.2635882  

   Tsay, Jason ; Dabbish, Laura ; Herbsleb, James ( January 2014 , ACM SIGSOFT International Symposium on Foundations of Software Engineering)

   Open source software projects often rely on code contributions from a wide variety of developers to extend the capabilities of their software. Project members evaluate these contributions and often engage in extended discussions to decide whether to integrate changes. These discussions have important implications for project management regarding new contributors and evolution of project requirements and direction. We present a study of how developers in open work environments evaluate and discuss pull requests, a primary method of contribution in GitHub, analyzing a sample of extended discussions around pull requests and interviews with GitHub developers. We found that developers raised issues around contributions over both the appropriateness of the problem that the submitter attempted to solve and the correctness of the implemented solution. Both core project members and third-party stakeholders discussed and sometimes implemented alternative solutions to address these issues. Different stakeholders also influenced the outcome of the evaluation by eliciting support from different communities such as dependent projects or even companies. We also found that evaluation outcomes may be more complex than simply acceptance or rejection. In some cases, although a submitter's contribution was rejected, the core team fulfilled the submitter's technical goals by implementing an alternative solution. We found that the level of a submitter's prior interaction on a project changed how politely developers discussed the contribution and the nature of proposed alternative solutions. 

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4. What We Can Learn from Jury Note Taking: A Content Analysis

   Denne, E. ( March 2020 , Annual Conference of the American Psychology-Law Society.)

   Abstract: Jury notetaking can be controversial despite evidence suggesting benefits for recall and understanding. Research on note taking has historically focused on the deliberation process. Yet, little research explores the notes themselves. We developed a 10-item coding guide to explore what jurors take notes on (e.g., simple vs. complex evidence) and how they take notes (e.g., gist vs. specific representation). In general, jurors made gist representations of simple and complex information in their notes. This finding is consistent with Fuzzy Trace Theory (Reyna & Brainerd, 1995) and suggests notes may serve as a general memory aid, rather than verbatim representation. Summary: The practice of jury notetaking in the courtroom is often contested. Some states allow it (e.g., Nebraska: State v. Kipf, 1990), while others forbid it (e.g., Louisiana: La. Code of Crim. Proc., Art. 793). Some argue notes may serve as a memory aid, increase juror confidence during deliberation, and help jurors engage in the trial (Hannaford & Munsterman, 2001; Heuer & Penrod, 1988, 1994). Others argue notetaking may distract jurors from listening to evidence, that juror notes may be given undue weight, and that those who took notes may dictate the deliberation process (Dann, Hans, & Kaye, 2005). While research has evaluated the efficacy of juror notes on evidence comprehension, little work has explored the specific content of juror notes. In a similar project on which we build, Dann, Hans, and Kaye (2005) found jurors took on average 270 words of notes each with 85% including references to jury instructions in their notes. In the present study we use a content analysis approach to examine how jurors take notes about simple and complex evidence. We were particularly interested in how jurors captured gist and specific (verbatim) information in their notes as they have different implications for information recall during deliberation. According to Fuzzy Trace Theory (Reyna & Brainerd, 1995), people extract “gist” or qualitative meaning from information, and also exact, verbatim representations. Although both are important for helping people make well-informed judgments, gist-based understandings are purported to be even more important than verbatim understanding (Reyna, 2008; Reyna & Brainer, 2007). As such, it could be useful to examine how laypeople represent information in their notes during deliberation of evidence. Methods Prior to watching a 45-minute mock bank robbery trial, jurors were given a pen and notepad and instructed they were permitted to take notes. The evidence included testimony from the defendant, witnesses, and expert witnesses from prosecution and defense. Expert testimony described complex mitochondrial DNA (mtDNA) evidence. The present analysis consists of pilot data representing 2,733 lines of notes from 52 randomly-selected jurors across 41 mock juries. Our final sample for presentation at AP-LS will consist of all 391 juror notes in our dataset. Based on previous research exploring jury note taking as well as our specific interest in gist vs. specific encoding of information, we developed a coding guide to quantify juror note-taking behaviors. Four researchers independently coded a subset of notes. Coders achieved acceptable interrater reliability [(Cronbach’s Alpha = .80-.92) on all variables across 20% of cases]. Prior to AP-LS, we will link juror notes with how they discuss scientific and non-scientific evidence during jury deliberation. Coding Note length. Before coding for content, coders counted lines of text. Each notepad line with at minimum one complete word was coded as a line of text. Gist information vs. Specific information. Any line referencing evidence was coded as gist or specific. We coded gist information as information that did not contain any specific details but summarized the meaning of the evidence (e.g., “bad, not many people excluded”). Specific information was coded as such if it contained a verbatim descriptive (e.g.,“<1 of people could be excluded”). We further coded whether this information was related to non-scientific evidence or related to the scientific DNA evidence. Mentions of DNA Evidence vs. Other Evidence. We were specifically interested in whether jurors mentioned the DNA evidence and how they captured complex evidence. When DNA evidence was mention we coded the content of the DNA reference. Mentions of the characteristics of mtDNA vs nDNA, the DNA match process or who could be excluded, heteroplasmy, references to database size, and other references were coded. Reliability. When referencing DNA evidence, we were interested in whether jurors mentioned the evidence reliability. Any specific mention of reliability of DNA evidence was noted (e.g., “MT DNA is not as powerful, more prone to error”). Expert Qualification. Finally, we were interested in whether jurors noted an expert’s qualifications. All references were coded (e.g., “Forensic analyst”). Results On average, jurors took 53 lines of notes (range: 3-137 lines). Most (83%) mentioned jury instructions before moving on to case specific information. The majority of references to evidence were gist references (54%) focusing on non-scientific evidence and scientific expert testimony equally (50%). When jurors encoded information using specific references (46%), they referenced non-scientific evidence and expert testimony equally as well (50%). Thirty-three percent of lines were devoted to expert testimony with every juror including at least one line. References to the DNA evidence were usually focused on who could be excluded from the FBIs database (43%), followed by references to differences between mtDNA vs nDNA (30%), and mentions of the size of the database (11%). Less frequently, references to DNA evidence focused on heteroplasmy (5%). Of those references that did not fit into a coding category (11%), most focused on the DNA extraction process, general information about DNA, and the uniqueness of DNA. We further coded references to DNA reliability (15%) as well as references to specific statistical information (14%). Finally, 40% of jurors made reference to an expert’s qualifications. Conclusion Jury note content analysis can reveal important information about how jurors capture trial information (e.g., gist vs verbatim), what evidence they consider important, and what they consider relevant and irrelevant. In our case, it appeared jurors largely created gist representations of information that focused equally on non-scientific evidence and scientific expert testimony. This finding suggests note taking may serve not only to represent information verbatim, but also and perhaps mostly as a general memory aid summarizing the meaning of evidence. Further, jurors’ references to evidence tended to be equally focused on the non-scientific evidence and the scientifically complex DNA evidence. This observation suggests jurors may attend just as much to non-scientific evidence as they to do complex scientific evidence in cases involving complicated evidence – an observation that might inform future work on understanding how jurors interpret evidence in cases with complex information. Learning objective: Participants will be able to describe emerging evidence about how jurors take notes during trial. 

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5. Study on U.S. Parents' Divisions of Labor During COVID-19, Waves 1-2

   https://doi.org/10.3886/E183142V2  

   Carlson, Daniel L. ; Petts, Richard J. ( January 2022 , ICPSR - Interuniversity Consortium for Political and Social Research)

   The COVID-19 pandemic has dramatically altered family life in the United States. Over the long duration of the pandemic, parents had to adapt to shifting work conditions, virtual schooling, the closure of daycare facilities, and the stress of not only managing households without domestic and care supports but also worrying that family members may contract the novel coronavirus. Reports early in the pandemic suggest that these burdens have fallen disproportionately on mothers, creating concerns about the long-term implications of the pandemic for gender inequality and mothers’ well-being. Nevertheless, less is known about how parents’ engagement in domestic labor and paid work has changed throughout the pandemic, what factors may be driving these changes, and what the long-term consequences of the pandemic may be for the gendered division of labor and gender inequality more generally.
   
   The Study on U.S. Parents’ Divisions of Labor During COVID-19 (SPDLC) collects longitudinal survey data from partnered U.S. parents that can be used to assess changes in parents’ divisions of domestic labor, divisions of paid labor, and well-being throughout and after the COVID-19 pandemic. The goal of SPDLC is to understand both the short- and long-term impacts of the pandemic for the gendered division of labor, work-family issues, and broader patterns of gender inequality.
   
   Survey data for this study is collected using Prolifc (www.prolific.co), an opt-in online platform designed to facilitate scientific research. The sample is comprised U.S. adults who were residing with a romantic partner and at least one biological child (at the time of entry into the study). In each survey, parents answer questions about both themselves and their partners. Wave 1 of SPDLC was conducted in April 2020, and parents who participated in Wave 1 were asked about their division of labor both prior to (i.e., early March 2020) and one month after the pandemic began. Wave 2 of SPDLC was collected in November 2020. Parents who participated in Wave 1 were invited to participate again in Wave 2, and a new cohort of parents was also recruited to participate in the Wave 2 survey. Wave 3 of SPDLC was collected in October 2021. Parents who participated in either of the first two waves were invited to participate again in Wave 3, and another new cohort of parents was also recruited to participate in the Wave 3 survey. This research design (follow-up survey of panelists and new cross-section of parents at each wave) will continue through 2024, culminating in six waves of data spanning the period from March 2020 through October 2024. An estimated total of approximately 6,500 parents will be surveyed at least once throughout the duration of the study.
   
   SPDLC data will be released to the public two years after data is collected; Waves 1 and 2 are currently publicly available. Wave 3 will be publicly available in October 2023, with subsequent waves becoming available yearly. Data will be available to download in both SPSS (.sav) and Stata (.dta) formats, and the following data files will be available: (1) a data file for each individual wave, which contains responses from all participants in that wave of data collection, (2) a longitudinal panel data file, which contains longitudinal follow-up data from all available waves, and (3) a repeated cross-section data file, which contains the repeated cross-section data (from new respondents at each wave) from all available waves. Codebooks for each survey wave and a detailed user guide describing the data are also available. Response Rates: Of the 1,157 parents who participated in Wave 1, 828 (72%) also participated in the Wave 2 study. Presence of Common Scales: The following established scales are included in the survey:
   

   • Self-Efficacy, adapted from Pearlin's mastery scale (Pearlin et al., 1981) and the Rosenberg self-esteem scale (Rosenberg, 2015) and taken from the American Changing Lives Survey
   • Communication with Partner, taken from the Marriage and Relationship Survey (Lichter & Carmalt, 2009)
     
   • Gender Attitudes, taken from the National Survey of Families and Households (Sweet & Bumpass, 1996)
     
   • Depressive Symptoms (CES-D-10)
   • Stress, measured using Cohen's Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983)
     

   Full details about these scales and all other items included in the survey can be found in the user guide and codebook
   The second wave of the SPDLC was fielded in November 2020 in two stages. In the first stage, all parents who participated in W1 of the SPDLC and who continued to reside in the United States were re-contacted and asked to participate in a follow-up survey. The W2 survey was posted on Prolific, and messages were sent via Prolific’s messaging system to all previous participants. Multiple follow-up messages were sent in an attempt to increase response rates to the follow-up survey. Of the 1,157 respondents who completed the W1 survey, 873 at least started the W2 survey. Data quality checks were employed in line with best practices for online surveys (e.g., removing respondents who did not complete most of the survey or who did not pass the attention filters). After data quality checks, 5.2% of respondents were removed from the sample, resulting in a final sample size of 828 parents (a response rate of 72%).
   
   In the second stage, a new sample of parents was recruited. New parents had to meet the same sampling criteria as in W1 (be at least 18 years old, reside in the United States, reside with a romantic partner, and be a parent living with at least one biological child). Also similar to the W1 procedures, we oversampled men, Black individuals, individuals who did not complete college, and individuals who identified as politically conservative to increase sample diversity. A total of 1,207 parents participated in the W2 survey. Data quality checks led to the removal of 5.7% of the respondents, resulting in a final sample size of new respondents at Wave 2 of 1,138 parents.
   
   In both stages, participants were informed that the survey would take approximately 20 minutes to complete. All panelists were provided monetary compensation in line with Prolific’s compensation guidelines, which require that all participants earn above minimum wage for their time participating in studies.
   To be included in SPDLC, respondents had to meet the following sampling criteria at the time they enter the study: (a) be at least 18 years old, (b) reside in the United States, (c) reside with a romantic partner (i.e., be married or cohabiting), and (d) be a parent living with at least one biological child. Follow-up respondents must be at least 18 years old and reside in the United States, but may experience changes in relationship and resident parent statuses. Smallest Geographic Unit: U.S. State

   This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. In accordance with this license, all users of these data must give appropriate credit to the authors in any papers, presentations, books, or other works that use the data. A suggested citation to provide attribution for these data is included below:            
   
   Carlson, Daniel L. and Richard J. Petts. 2022. Study on U.S. Parents’ Divisions of Labor During COVID-19 User Guide: Waves 1-2.  

   To help provide estimates that are more representative of U.S. partnered parents, the SPDLC includes sampling weights. Weights can be included in statistical analyses to make estimates from the SPDLC sample representative of U.S. parents who reside with a romantic partner (married or cohabiting) and a child aged 18 or younger based on age, race/ethnicity, and gender. National estimates for the age, racial/ethnic, and gender profile of U.S. partnered parents were obtained using data from the 2020 Current Population Survey (CPS). Weights were calculated using an iterative raking method, such that the full sample in each data file matches the nationally representative CPS data in regard to the gender, age, and racial/ethnic distributions within the data. This variable is labeled CPSweightW2 in the Wave 2 dataset, and CPSweightLW2 in the longitudinal dataset (which includes Waves 1 and 2). There is not a weight variable included in the W1-W2 repeated cross-section data file.
    

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