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. "

The criterion validity of a general factor of personality (GFP) extracted from personality scales of various lengths was explored in relation to organizational behavior and subjective well‐being with 288 employed students. Results indicated that GFPs extracted from as few as 10 items were significantly related to organizational outcomes. The relationship between GFP scores and outcomes generally increased with the length of the underlying scales, but these differences were reduced when correcting for reliability. Additionally, in over 60% of the analyses the GFPs exhibited higher correlations with specific outcomes compared to specific Big Five scores; this was true of 100% of the analyses using a broad, composite criterion. These results highlight the potential utility of the GFP as a screening tool when extracted from Big Five inventories from 10 to 100 items.

Purpose Estimates of the effects of faking on personality scores typically represent the difference from one sample mean to another sample mean in terms of standard deviations. While this is technically accurate, it does put faking effects into the context of the individuals actually engaging in faking behavior. The purpose of this paper is to address this deficiency. Design/methodology/approach This paper provides a mathematical proof and a computational simulation manipulating faking effect size, prevalence of faking, and the size of the applicant pool. Findings The paper illustrates that reported effects of faking are underestimates of the amount of faking that individual test takers are engaging in. Results provide researchers and practitioners with more accurate estimates of how to interpret faking effects sizes. Practical implications To understand the impact of faking on personality testing, it is important to consider both faking effect sizes as well as the prevalence of faking. Originality/value Researchers and practitioners do not often consider the real implications of faking effect sizes. The current paper presents those results in a new light.

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