52% Yes, a signiicant crisis 3% No, there is no crisis 7% Don't know 38% Yes, a slight crisis 38% Yes, a slight crisis 1,576 RESEARCHERS SURVEYED M ore than 70% of researchers have tried and failed to reproduce another scientist's experiments, and more than half have failed to reproduce their own experiments. Those are some of the telling figures that emerged from Nature's survey of 1,576 researchers who took a brief online questionnaire on reproducibility in research. The data reveal sometimes-contradictory attitudes towards reproduc-ibility. Although 52% of those surveyed agree that there is a significant 'crisis' of reproducibility, less than 31% think that failure to reproduce published results means that the result is probably wrong, and most say that they still trust the published literature. Data on how much of the scientific literature is reproducible are rare and generally bleak. The best-known analyses, from psychology 1 and cancer biology 2 , found rates of around 40% and 10%, respectively. Our survey respondents were more optimistic: 73% said that they think that at least half of the papers in their field can be trusted, with physicists and chemists generally showing the most confidence. The results capture a confusing snapshot of attitudes around these issues, says Arturo Casadevall, a microbiologist at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland. "At the current time there is no consensus on what reproducibility is or should be. " But just recognizing that is a step forward, he says. "The next step may be identifying what is the problem and to get a consensus. "

Effect size information is essential for the scientific enterprise and plays an increasingly central role in the scientific process. We extracted 147,328 correlations and developed a hierarchical taxonomy of variables reported in Journal of Applied Psychology and Personnel Psychology from 1980 to 2010 to produce empirical effect size benchmarks at the omnibus level, for 20 common research domains, and for an even finer grained level of generality. Results indicate that the usual interpretation and classification of effect sizes as small, medium, and large bear almost no resemblance to findings in the field, because distributions of effect sizes exhibit tertile partitions at values approximately one-half to one-third those intuited by Cohen (1988). Our results offer information that can be used for research planning and design purposes, such as producing better informed non-nil hypotheses and estimating statistical power and planning sample size accordingly. We also offer information useful for understanding the relative importance of the effect sizes found in a particular study in relationship to others and which research domains have advanced more or less, given that larger effect sizes indicate a better understanding of a phenomenon. Also, our study offers information about research domains for which the investigation of moderating effects may be more fruitful and provide information that is likely to facilitate the implementation of Bayesian analysis. Finally, our study offers information that practitioners can use to evaluate the relative effectiveness of various types of interventions.

Previous research has primarily revealed a negative relationship between collective employee turnover and organizational performance. However, this research also suggests underlying complexity in the relationship. To clarify the nature of this relationship, the authors conduct a meta-analytic review in which they test and provide support for a portion of Hausknecht and Trevor’s model of collective turnover. The authors’ meta-analysis includes 48 independent samples reporting 157 effect size estimates (N = 24,943), tests six hypothesized moderator variables, and provides path analyses to test alternative conceptualizations of the turnover–organizational performance relationship. Results indicate that the mean corrected correlation between turnover and organizational performance is −.03, but this relationship is moderated by several important variables. For example, the relationship is stronger in manufacturing and transportation industries (−.07), for managerial employees (−.08), in midsize organizations (−.07), in samples from labor market economies (−.05), and when organizational performance is operationalized in terms of customer service (−.10) or quality and safety (−.12) metrics. In addition, proximal performance outcomes mediate relationships with financial performance. The authors discuss implications of their results for theory and practice and provide directions for future research.

The authors content analyzed 196 meta-analyses including 5,581 effect-size estimates published in Academy of Management Journal, Journal of Applied Psychology, Journal of Management, Personnel Psychology, and Strategic Management Journal from January 1982 through August 2009 to assess the presumed effects of each of 21 methodological choices and judgment calls on substantive conclusions. Results indicate that, overall, the various meta-analytic methodological choices available and judgment calls involved in the conduct of a meta-analysis have little impact on the resulting magnitude of the meta-analytically derived effect sizes. Thus, the present study, based on actual meta-analyses, casts doubt on previous warnings, primarily based on selective case studies, that judgment calls have an important impact on substantive conclusions. The authors also tested the fit of a multivariate model that includes relationships among theory-building and theory-testing goals, obtained effect sizes, year of publication of the meta-analysis, and scholarly impact (i.e., citations per year). Results indicate that the more a meta-analysis attempts to test an existing theory, the larger the number of citations, whereas the more a meta-analysis attempts to build new theory, the lower the number of citations. Also, in support of scientific particularism, as opposed to scientific universalism, the magnitude of the derived effects is not related to the extent to which a meta-analysis is cited. Taken together, the results provide a comprehensive data-based understanding of how meta-analytic reviews are conducted and the implications of these practices for theory building and testing, obtained effect sizes, and scholarly impact.

Do cultural values enhance financial and subjective well-being (SWB)? Taking a multidisciplinary approach, we meta-analytically reviewed the field, found it thinly covered, and focused on individualism. In counter, we collected a broad array of individual-level data, specifically an Internet sample of 8,438 adult respondents. Individual SWB was most strongly associated with cultural values that foster relationships and social capital, which typically accounted for more unique variance in life satisfaction than an individual’s salary. At a national level, we used mean-based meta-analysis to construct a comprehensive cultural and SWB database. Results show some reversals from the individual level, particularly masculinity’s facet of achievement orientation. In all, the happy nation has low power distance and low uncertainty avoidance, but is high in femininity and individualism, and these effects are interrelated but still partially independent from political and economic institutions. In short, culture matters for individual and national well-being.