Counseling Trainees’ Advocacy: Investigating the Role of Race, Gender Beliefs, Exposure to Injustice, and Diversity Experiences

Although some efforts have been made to understand counseling trainees’ characteristics and environmental factors that are associated with trainees’ social justice advocacy beliefs and behaviors, little research has explored the combined effect of counseling trainees’ demographic characteristics, their beliefs, experiences of oppression, and their participation in diversity activities on their advocacy behaviors. Applying the Resource Model of Political Participation (Brady, Verba, & Schlozman, 1995), the present study aimed to extend the emerging research on counselor trainees’ advocacy by examining trainees’ race and gender differences in advocacy among 281 graduate counselor trainees. Although no racial and gender differences were found in regard to trainees’ social justice advocacy, the study found significant race and gender differences in trainees’ levels of awareness of modern racism and sexism. Moreover, Structural Equation Modeling revealed that trainees’ exposure to racist and sexist events, as well as participation in formal diversity experiences had significant links to trainees’ social justice advocacy behaviors. Additionally, trainees’ experiences and witnessing of racist events, their participation in formal diversity experiences, and having close interracial friendship were found to have negative association with trainees’ color-blind racial attitudes. Trainees’ experiences and witnessing of sexist events were negatively linked to trainees’ modern sexist beliefs. Implications for theory, training programs, and research are addressed

Person-Context Influences on Educational Involvement in Rural Cambodian Schools

Based on Bronfenbrenner’s Process-Person-Context-Time model, this study explored the attitudes and potential factors affecting children’s educational participation in two non-governmental organization-sponsored rural schools in Siem Reap, Cambodia. Focus groups and individual interviews were conducted with students (female and male), teachers, principals, and parents. A discovery-oriented qualitative analytical approach revealed that at the individual level, truancy and student respect for school regulations impacted school participation. At the family level, parental support and family difficulties influenced school participation. At the school level, teacher ability, teacher-parent interactions, and adequate resources either facilitated or hindered student success. At the socio-cultural level, socioeconomic conditions, communal supports, and traditional gendered expectations created gender disparities in school involvement. Policy implications include a nation-wide comprehensive professional development program targeting teacher training (structural level), a strong teacher-counselor partnership to facilitate the development of literacy campaigns (community level), and increasing female mentors and counselors to increase gender parity (cultural level)

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Attribution of typhoon-induced torrential precipitation in Central Vietnam, October 2020

International audienceIn October 2020, Central Vietnam was struck by heavy rain resulting from a sequence of 5 tropical depressions and typhoons. The immense amount of water led to extensive flooding and landslides that killed more than 200 people, injured more than 500 people, and caused direct damages valued at approximately 1.2 billion USD. Here, we quantify how the intensity of the precipitation leading to such exceptional impacts is attributable to anthropogenic climate change. First, we define the event as the regional maximum of annual maximum 15-day average rainfall (Rx15day). We then analyse the trend in Rx15day over Central Vietnam from the observations and simulations in the PRIMAVERA and CORDEX-CORE ensembles, which pass our evaluation tests, by applying the generalised extreme value (GEV) distribution in which location and scale parameters exponentially covary with increasing global temperatures. Combining these observations and model results, we find that the 2020 event, occurring about once every 80 years (at least 17 years), has not changed in either probability of occurrence (a factor 1.0, ranging from 0.4 to 2.4) or intensity (0%, ranging from −8 to +8%) in the present climate in comparison with early-industrial climate. This implies that the effect of human-induced climate change contributing to this persistent extreme rainfall event is small compared to natural variability. However, given the scale of damage of this hazard, our results underline that more investment in disaster risk reduction for this type of rainfall-induced flood hazard is of importance, even independent of the effect of anthropogenic climate change. Moreover, as both observations and model simulations will be extended with the passage of time, we encourage more climate change impact investigations on the extreme in the future that help adaptation and mitigation plans and raise awareness in the country

Mass Reproducibility and Replicability: A New Hope

This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators' experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes