Journal article publishing in the social sciences and humanities: A comparison of Web of Science coverage for five European countries.

This study compares publication pattern dynamics in the social sciences and humanities in five European countries. Three are Central and Eastern European countries that share a similar cultural and political heritage (the Czech Republic, Slovakia, and Poland). The other two are Flanders (Belgium) and Norway, representing Western Europe and the Nordics, respectively. We analysed 449,409 publications from 2013-2016 and found that, despite persisting differences between the two groups of countries across all disciplines, publication patterns in the Central and Eastern European countries are becoming more similar to those in their Western and Nordic counterparts. Articles from the Central and Eastern European countries are increasingly published in journals indexed in Web of Science and also in journals with the highest citation impacts. There are, however, clear differences between social science and humanities disciplines, which need to be considered in research evaluation and science policy.

Publication rates from biomedical and behavioral and social science R01s funded by the National Institutes of Health.

Prior research has shown a serious lack of research transparency resulting from the failure to publish study results in a timely manner. The National Institutes of Health (NIH) has increased its use of publication rate and time to publication as metrics for grant productivity. In this study, we analyze the publications associated with all R01 and U01 grants funded from 2008 through 2014, providing sufficient time for these grants to publish their findings, and identify predictors of time to publication based on a number of variables, including if a grant was coded as a behavioral and social sciences research (BSSR) grant or not. Overall, 2.4% of the 27,016 R01 and U01 grants did not have a publication associated with the grant within 60 months of the project start date, and this rate of zero publications was higher for BSSR grants (4.6%) than for non-BSSR grants (1.9%). Mean time in months to first publication was 15.2 months, longer for BSSR grants (22.4 months) than non-BSSR grants (13.6 months). Survival curves showed a more rapid reduction of risk to publish from non-BSSR vs BSSR grants. Cox regression models showed that human research (vs. animal, neither, or both) and clinical trials research (vs. not) are the strongest predictors of time to publication and failure to publish, but even after accounting for these and other predictors, BSSR grants continued to show longer times to first publication and greater risk of no publications than non-BSSR grants. These findings indicate that even with liberal criteria for publication (any publication associated with a grant), a small percentage of R01 and U01 grantees fail to publish in a timely manner, and that a number of factors, including human research, clinical trial research, child research, not being an early stage investigator, and conducting behavioral and social sciences research increase the risk of time to first publication.

Has Covid-19 Gone Viral? An Overview of Research by Subject Area.

When a pandemic outbreak occurs, it seems logical that related scientific production should increase substantially; however, it is important to recognize its interdisciplinary usefulness to find a solution to the problem. The main aim of this research is to analyse the main keywords of the scientific research about COVID-19, by subject area. To discover the influence of certain terms and their transferability, synergies, and future trends, a cluster analysis of the keywords was performed. The results show that Health Sciences dominate the publications with 88.23% of the total volume. As expected, the largest volume of research was dedicated to medical aspects of the disease, like experimental treatments, its physiopathology, or its respiratory syndrome. However, other fields, like Social Sciences (6.07%), Technology (2.68%), Physical Sciences (1.95%), and Arts and Humanities (1.08%), also played an important role in research on COVID-19.

Use and users of a social science research data archive.

This study focuses on the use and users of Finnish social science research data archive. Study is based on enriched user data of the archive from years 2015-2018. Study investigates the number and type of downloaded datasets, the number of citations for data, the demographics of data downloaders and the purposes data are downloaded for. Datasets were downloaded from the archive 10346 times. Majority of the downloaded datasets are quantitative. Quantitative datasets are also more often cited, but the number of citations vary and does not always correlate with the number of downloads. Use of the archive varies by user's country, organization, and discipline. Datasets from the archive were downloaded most often for study work, bachelor's and master's theses, and research purposes. It is likely that reusing research data will increase in the near future as more data will become available, scholars are more informed about research data management, and data citation practices are established.

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

The impact of penalties for wrong answers on the gender gap in test scores.

Multiple-choice examinations play a critical role in university admissions across the world. A key question is whether imposing penalties for wrong answers on these examinations deters guessing from women more than men, disadvantaging female test-takers. We consider data from a large-scale, high-stakes policy change that removed penalties for wrong answers on the national college entry examination in Chile. The policy change reduced a large gender gap in questions skipped. It also narrowed gender gaps in performance, primarily among high-performing test-takers, and in the fields of math, social science, and chemistry.

Social scientists' testimony before Congress in the United States between 1946-2016, trends from a new dataset.

Congressional hearings are a venue in which social scientists present their views and analyses before lawmakers in the United States, however quantitative data on their representation has been lacking. We present new, publicly available, data on the rates at which anthropologists, economists, political scientists, psychologists, and sociologists appeared before United States congressional hearings from 1946 through 2016. We show that social scientists were present at some 10,347 hearings and testified 15,506 times. Economists testify before the US Congress far more often than other social scientists, and constitute a larger proportion of the social scientists testifying in industry and government positions. We find that social scientists' testimony is increasingly on behalf of think tanks; political scientists, in particular, have gained much more representation through think tanks. Sociology, and psychology's representation before Congress has declined considerably beginning in the 1980s. Anthropologists were the least represented. These findings show that academics are representing a more diverse set of organizations, but economists continue to be far more represented than other disciplines before the US Congress.

Specification issues in nonlinear sem: the moderation that wasn't / Problemas de especificación en SEM no lineal: la moderación que no lo era

BACKGROUND: Analysis of interaction or moderation effects between latent variables is a common requirement in the social sciences. However, when predictors are correlated, interaction and quadratic effects become more alike, making them difficult to distinguish. As a result, when data are drawn from a quadratic population model and the analysis model specifies interactions only, misleading results may be obtained. METHOD: This article addresses the consequences of different types of specification error in nonlinear structural equation models using a Monte Carlo study. RESULTS: Results show that fitting a model with interactions when quadratic effects are present in the population will almost certainly lead to erroneous detection of moderation effects, and that the same is true in the opposite scenario. Simultaneous estimation of interactions and quadratic effects yields correct results. CONCLUSIONS: Simultaneous estimation of interaction and quadratic effects prevents detection of spurious or misleading nonlinear effects. Results are discussed and recommendations are offered to applied researchers

ANTECEDENTES: el análisis de efectos de interacción o moderación entre variables latentes es común en ciencias sociales. Sin embargo, cuando los predictores están correlacionados, los efectos de interacción y cuadráticos se vuelven parecidos, haciendo difícil su distinción. Así, cuando los datos provienen de un modelo de cuadrático a nivel poblacional y el modelo de análisis solo especifica interacciones, se pueden obtener resultados engañosos. MÉTODO: este artículo aborda las consecuencias de diferentes tipos de errores de especificación en modelos de ecuaciones estructurales no lineales utilizando un estudio de Monte Carlo. RESULTADOS: los resultados muestran que estimar un modelo con interacciones cuando en la población hay efectos cuadráticos conducirá a una detección equivocada de efectos de moderación con casi plena seguridad, y lo mismo ocurrirá en el escenario opuesto. La estimación simultánea de interacciones y efectos cuadráticos en el modelo conduce a resultados correctos. CONCLUSIONES: la estimación simultánea de efectos de interacción y cuadráticos permite evitar detectar efectos no lineales espurios o engañosos. Los resultados se discuten para ofrecer recomendaciones a los investigadores aplicados

Specification issues in nonlinear SEM: The moderation that wasn't.

BACKGROUND: Analysis of interaction or moderation effects between latent variables is a common requirement in the social sciences. However, when predictors are correlated, interaction and quadratic effects become more alike, making them difficult to distinguish. As a result, when data are drawn from a quadratic population model and the analysis model specifies interactions only, misleading results may be obtained. METHOD: This article addresses the consequences of different types of specification error in nonlinear structural equation models using a Monte Carlo study. RESULTS: Results show that fitting a model with interactions when quadratic effects are present in the population will almost certainly lead to erroneous detection of moderation effects, and that the same is true in the opposite scenario. Simultaneous estimation of interactions and quadratic effects yields correct results. CONCLUSIONS: Simultaneous estimation of interaction and quadratic effects prevents detection of spurious or misleading nonlinear effects. Results are discussed and recommendations are offered to applied researchers.

Los emerging sources citation index y la internacionalización de las revistas científicas españolas, con especial mención a las de psicología / The Emerging Sources Citation Index and the internationalization of Spanish scientific journals, with special reference to Psychology journals

ANTECEDENTES: España está entre los países que más revistas ha ingresado en Emerging Sources Citation Index, el nuevo producto de Web of Science. El objetivo de este trabajo es analizar sus implicaciones y cuantificar sus efectos en los Factores de Impacto. MÉTODO: la presencia española se cuantificó utilizando los listados de Master Journal List, volcados a una hoja de cálculo para su tratamiento. Las implicaciones se observaron mediante análisis de los criterios de los "Journal Selection Process". La repercusión en los impactos se analizó mediante estudio de caso de revistas españolas de Psicología incluidas en Journal Citation Reports (JCR). RESULTADOS: hasta el año 2015 España significa el 1,13% de la Colección Central. Con las 568 revistas de Emerging ha incrementado su presencia hasta el 3,37%. Las áreas más beneficiadas son las Ciencias Sociales y Humanidades. Como efecto general, la citación en revistas de Psicología se ha incrementado un 13,18%. CONCLUSIONES: la situación propiciada por Emerging mejorará de forma significativa a corto plazo el número y posición de revistas españolas con Factor de Impacto. De momento, las citas que emiten ya tienen una influencia significativa en el incremento de los impactos de las revistas españolas ya establecidas en los JCR

BACKGROUND: Spain is among the countries that have added more scientific journals into the Emerging Sources Citation Index (ESCI), a new product from the Central Collection of Web of Science. The aim of this paper is to analyze the implications of this and quantify the effects on Impact Factors. METHOD: The Spanish presence was quantified using the Master Journal List, converted to a spreadsheet for data processing. The implications were determined by analyzing the criteria "Journal Selection Process". The effect on impact factors was analyzed through a case study of Spanish JCR journals of Psychology. RESULTS: Until 2015, Spain represented 1.13% of the Central Collection. With the 568 journals included in the ESCI, that presence has increased to 3.37%. The areas benefitting most were Social Sciences and Humanities. As a general effect, citation in Psychology journals has increased by an average of 13.18%. CONCLUSIONS: The situation fostered by the ESCI will significantly improve the number and position of Spanish journals with impact factors in the short and medium term. Currently, their citations have already significantly influenced an increase of the impact of Spanish journals included in the Journal Citation Reports

[The Emerging Sources Citation Index and the internationalization of Spanish scientific journals, with special reference to Psychology journals].

The Emerging Sources Citation Index and the internationalization of Spanish scientific journals, with special reference to Psychology journals. BACKGROUND: Spain is among the countries that have added more scientific journals into the Emerging Sources Citation Index (ESCI), a new product from the Central Collection of Web of Science. The aim of this paper is to analyze the implications of this and quantify the effects on Impact Factors. METHOD: The Spanish presence was quantified using the Master Journal List, converted to a spreadsheet for data processing. The implications were determined by analyzing the criteria "Journal Selection Process". The effect on impact factors was analyzed through a case study of Spanish JCR journals of Psychology. RESULTS: Until 2015, Spain represented 1.13% of the Central Collection. With the 568 journals included in the ESCI, that presence has increased to 3.37%. The areas benefitting most were Social Sciences and Humanities. As a general effect, citation in Psychology journals has increased by an average of 13.18%. CONCLUSIONS: The situation fostered by the ESCI will significantly improve the number and position of Spanish journals with impact factors in the short and medium term. Currently, their citations have already significantly influenced an increase of the impact of Spanish journals included in the Journal Citation Reports.

Breast cancer risk by occupation and industry in women and men: Results from the Occupational Disease Surveillance System (ODSS).

BACKGROUND: The recently established Occupational Disease Surveillance System (ODSS) was used to examine breast cancer risk in women and men by occupation and industry. METHODS: Ontario workers in the ODSS cohort (1983-2016) were followed up for breast cancer diagnosis through the Ontario Cancer Registry. Cox-proportional hazard models were used to calculate age-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: A total of 17 865 and 492 cases were identified in working women (W) and men (M), respectively. Elevated risks were observed in management (W: HR = 1.54, 95% CI = 1.40-1.70; M: HR = 2.79, 95% CI = 1.44-5.39), administrative/clerical (W: HR = 1.16, 95% CI = 1.11-1.21; M: HR = 1.45, 95% CI = 1.06-1.99), and teaching (W: HR = 1.54, 95% CI = 1.44-1.63; M: HR = 3.00, 95% CI = 1.49-6.03). Other elevated risks were observed in nursing/health, social sciences, and janitor/cleaning services for both genders. CONCLUSIONS: Common occupational associations in both genders warrant investigation into job-related risk factors, such as sedentary behavior, shift work, ionizing radiation, and chemical exposures.

A default prior for regression coefficients.

When the sample size is not too small, M-estimators of regression coefficients are approximately normal and unbiased. This leads to the familiar frequentist inference in terms of normality-based confidence intervals and p-values. From a Bayesian perspective, use of the (improper) uniform prior yields matching results in the sense that posterior quantiles agree with one-sided confidence bounds. For this, and various other reasons, the uniform prior is often considered objective or non-informative. In spite of this, we argue that the uniform prior is not suitable as a default prior for inference about a regression coefficient in the context of the bio-medical and social sciences. We propose that a more suitable default choice is the normal distribution with mean zero and standard deviation equal to the standard error of the M-estimator. We base this recommendation on two arguments. First, we show that this prior is non-informative for inference about the sign of the regression coefficient. Second, we show that this prior agrees well with a meta-analysis of 50 articles from the MEDLINE database.

Health Sciences cultural safety education in Australia, Canada, New Zealand, and the United States: a literature review.

OBJECTIVES: To review the research literature on cultural safety education within post-secondary health science programs. METHODS: We conducted health and social science database searches from 1996-2016, using combined keywords: cultural competence or safety; teaching or curriculum; universities, polytechnics or professional programs; and Aboriginal or Indigenous. In dyads, authors selected, and reviewed studies independently followed by discussion and consensus to identify thematic linkages of major findings. RESULTS: A total of 1583 abstracts and 122 full-text articles were reviewed with 40 selected for final inclusion. Publications from Australia, Canada, New Zealand and the United States described curriculum development and delivery. A variety of evaluation approaches were used including anecdotal reports, focus groups, interviews, course evaluations, reflective journals, pre-post surveys, critical reflective papers, and exam questions. Duration and depth of curricular exposure ranged from one day to integration across a six-year program.  Changes in student knowledge, attitude, self-confidence, and behaviour when working with Indigenous populations were reported. Cultural safety education and application to practice were shown to be linked to improved relationships, healthier outcomes, and increased number of Indigenous people entering health education programs and graduates interested in working in diverse communities. CONCLUSIONS: This review provides a summary of multidisciplinary didactic and experiential instructional approaches to cultural safety education and the impact on students, educators and Indigenous people.  Institutional support, strategic planning and cultural safety curriculum policy within post-secondary settings and community engagement are imperative for positive student experiences, advocacy, and actions toward health equity and improved health for Indigenous people and communities.

Caveat emptor, computational social science: Large-scale missing data in a widely-published Reddit corpus.

As researchers use computational methods to study complex social behaviors at scale, the validity of this computational social science depends on the integrity of the data. On July 2, 2015, Jason Baumgartner published a dataset advertised to include "every publicly available Reddit comment" which was quickly shared on Bittorrent and the Internet Archive. This data quickly became the basis of many academic papers on topics including machine learning, social behavior, politics, breaking news, and hate speech. We have discovered substantial gaps and limitations in this dataset which may contribute to bias in the findings of that research. In this paper, we document the dataset, substantial missing observations in the dataset, and the risks to research validity from those gaps. In summary, we identify strong risks to research that considers user histories or network analysis, moderate risks to research that compares counts of participation, and lesser risk to machine learning research that avoids making representative claims about behavior and participation on Reddit.

Detecting the contagion effect in mass killings; a constructive example of the statistical advantages of unbinned likelihood methods.

BACKGROUND: When attempting to statistically distinguish between a null and an alternative hypothesis, many researchers in the life and social sciences turn to binned statistical analysis methods, or methods that are simply based on the moments of a distribution (such as the mean, and variance). These methods have the advantage of simplicity of implementation, and simplicity of explanation. However, when null and alternative hypotheses manifest themselves in subtle differences in patterns in the data, binned analysis methods may be insensitive to these differences, and researchers may erroneously fail to reject the null hypothesis when in fact more sensitive statistical analysis methods might produce a different result when the null hypothesis is actually false. Here, with a focus on two recent conflicting studies of contagion in mass killings as instructive examples, we discuss how the use of unbinned likelihood methods makes optimal use of the information in the data; a fact that has been long known in statistical theory, but perhaps is not as widely appreciated amongst general researchers in the life and social sciences. METHODS: In 2015, Towers et al published a paper that quantified the long-suspected contagion effect in mass killings. However, in 2017, Lankford & Tomek subsequently published a paper, based upon the same data, that claimed to contradict the results of the earlier study. The former used unbinned likelihood methods, and the latter used binned methods, and comparison of distribution moments. Using these analyses, we also discuss how visualization of the data can aid in determination of the most appropriate statistical analysis methods to distinguish between a null and alternate hypothesis. We also discuss the importance of assessment of the robustness of analysis results to methodological assumptions made (for example, arbitrary choices of number of bins and bin widths when using binned methods); an issue that is widely overlooked in the literature, but is critical to analysis reproducibility and robustness. CONCLUSIONS: When an analysis cannot distinguish between a null and alternate hypothesis, care must be taken to ensure that the analysis methodology itself maximizes the use of information in the data that can distinguish between the two hypotheses. The use of binned methods by Lankford & Tomek (2017), that examined how many mass killings fell within a 14 day window from a previous mass killing, substantially reduced the sensitivity of their analysis to contagion effects. The unbinned likelihood methods used by Towers et al (2015) did not suffer from this problem. While a binned analysis might be favorable for simplicity and clarity of presentation, unbinned likelihood methods are preferable when effects might be somewhat subtle.

Disciplinary differences of the impact of altmetric.

The main objective of this work was to group altmetric indicators according to their relationships and detect disciplinary differences with regard to altmetric impact in a set of 3793 research articles published in 2013. Three of the most representative altmetric providers (Altmetric, PlumX and Crossref Event Data) and Scopus were used to extract information about these publications and their metrics. Principal component analysis was used to summarize the information on these metrics and detect groups of indicators. The results show that these metrics can be grouped into three components: social media, gathering metrics from social networks and online media; usage, including metrics on downloads and views; and citations and saves, grouping metrics related to research impact and saves in bookmarking sites. With regard to disciplinary differences, articles in the General category attract more attention from social media, Social Sciences articles have higher usage than Physical Sciences, and General articles are more cited and saved than Health Sciences and Social Sciences articles.

Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015.

Being able to replicate scientific findings is crucial for scientific progress1-15. We replicate 21 systematically selected experimental studies in the social sciences published in Nature and Science between 2010 and 201516-36. The replications follow analysis plans reviewed by the original authors and pre-registered prior to the replications. The replications are high powered, with sample sizes on average about five times higher than in the original studies. We find a significant effect in the same direction as the original study for 13 (62%) studies, and the effect size of the replications is on average about 50% of the original effect size. Replicability varies between 12 (57%) and 14 (67%) studies for complementary replicability indicators. Consistent with these results, the estimated true-positive rate is 67% in a Bayesian analysis. The relative effect size of true positives is estimated to be 71%, suggesting that both false positives and inflated effect sizes of true positives contribute to imperfect reproducibility. Furthermore, we find that peer beliefs of replicability are strongly related to replicability, suggesting that the research community could predict which results would replicate and that failures to replicate were not the result of chance alone.

The first nationwide survey of MD-PhDs in the social sciences and humanities: training patterns and career choices.

BACKGROUND: While several articles on MD-PhD trainees in the basic sciences have been published in the past several years, very little research exists on physician-investigators in the social sciences and humanities. However, the numbers of MD-PhDs training in these fields and the number of programs offering training in these fields are increasing, particularly within the US. In addition, accountability for the public funding for MD-PhD programs requires knowledge about this growing population of trainees and their career trajectories. The aim of this paper is to describe the first cohorts of MD-PhDs in the social sciences and humanities, to characterize their training and career paths, and to better understand their experiences of training and subsequent research and practice. METHODS: This paper utilizes a multi-pronged recruitment method and novel survey instrument to examine an understudied population of MD-PhD trainees in the social sciences and humanities, many of whom completed both degrees without formal programmatic support. The survey instrument was designed to collect demographic, training and career trajectory data, as well as experiences of and perspectives on training and career. It describes their routes to professional development, characterizes obstacles to and predictors of success, and explores career trends. RESULTS: The average length of time to complete both degrees was 9 years. The vast majority (90%) completed a clinical residency, almost all (98%) were engaged in research, the vast majority (88%) were employed in academic institutions, and several others (9%) held leadership positions in national and international health organizations. Very few (4%) went into private practice. The survey responses supply recommendations for supporting current trainees as well as areas for future research. CONCLUSIONS: In general, MD-PhDs in the social sciences and humanities have careers that fit the goals of agencies providing public funding for training physician-investigators: they are involved in mutually-informative medical research, clinical practice, and teaching - working to improve our responses to the social, cultural, and political determinants of health and health care. These findings provide strong evidence for continued and improved funding and programmatic support for MD-PhD trainees in the social sciences and humanities.