The relationship between traditional metrics of research impact (e.g., number of citations) and alternative metrics (altmetrics) such as Twitter activity are of great interest, but remain imprecisely quantified. We used generalized linear mixed modeling to estimate the relative effects of Twitter activity, journal impact factor, and time since publication on Web of Science citation rates of 1,599 primary research articles from 20 ecology journals published from 2012-2014. We found a strong positive relationship between Twitter activity (i.e., the number of unique tweets about an article) and number of citations. Twitter activity was a more important predictor of citation rates than 5-year journal impact factor. Moreover, Twitter activity was not driven by journal impact factor; the ‘highest-impact’ journals were not necessarily the most discussed online. The effect of Twitter activity was only about a fifth as strong as time since publication; accounting for this confounding factor was critical for estimating the true effects of Twitter use. Articles in impactful journals can become heavily cited, but articles in journals with lower impact factors can generate considerable Twitter activity and also become heavily cited. Authors may benefit from establishing a strong social media presence, but should not expect research to become highly cited solely through social media promotion. Our research demonstrates that altmetrics and traditional metrics can be closely related, but not identical. We suggest that both altmetrics and traditional citation rates can be useful metrics of research impact.
Journal impact factors have become an important criterion to judge the quality of scientific publications over the years, influencing the evaluation of institutions and individual researchers worldwide. However, they are also subject to a number of criticisms. Here we point out that the calculation of a journal’s impact factor is mainly based on the date of publication of its articles in print form, despite the fact that most journals now make their articles available online before that date. We analyze 61 neuroscience journals and show that delays between online and print publication of articles increased steadily over the last decade. Importantly, such a practice varies widely among journals, as some of them have no delays, while for others this period is longer than a year. Using a modified impact factor based on online rather than print publication dates, we demonstrate that online-to-print delays can artificially raise a journal’s impact factor, and that this inflation is greater for longer publication lags. We also show that correcting the effect of publication delay on impact factors changes journal rankings based on this metric. We thus suggest that indexing of articles in citation databases and calculation of citation metrics should be based on the date of an article’s online appearance, rather than on that of its publication in print.
Understanding the relationship between scientific productivity and research group size is important for deciding how science should be funded. We have investigated the relationship between these variables in the life sciences in the United Kingdom using data from 398 principle investigators (PIs). We show that three measures of productivity, the number of publications, the impact factor of the journals in which papers are published and the number of citations, are all positively correlated to group size, although they all show a pattern of diminishing returns-doubling group size leads to less than a doubling in productivity. The relationships for the impact factor and the number of citations are extremely weak. Our analyses suggest that an increase in productivity will be achieved by funding more PIs with small research groups, unless the cost of employing post-docs and PhD students is less than 20% the cost of a PI. We also provide evidence that post-docs are more productive than PhD students both in terms of the number of papers they produce and where those papers are published.
ABSTRACT A review of the United States Office of Research Integrity annual reports identified 228 individuals who have committed misconduct, of which 94% involved fraud. Analysis of the data by career stage and gender revealed that misconduct occurred across the entire career spectrum from trainee to senior scientist and that two-thirds of the individuals found to have committed misconduct were male. This exceeds the overall proportion of males among life science trainees and faculty. These observations underscore the need for additional efforts to understand scientific misconduct and to ensure the responsible conduct of research. IMPORTANCE As many of humanity’s greatest problems require scientific solutions, it is critical for the scientific enterprise to function optimally. Misconduct threatens the scientific enterprise by undermining trust in the validity of scientific findings. We have examined specific demographic characteristics of individuals found to have committed research misconduct in the life sciences. Our finding that misconduct occurs across all stages of career development suggests that attention to ethical aspects of the conduct of science should not be limited to those in training. The observation that males are overrepresented among those who commit misconduct implies a gender difference that needs to be better understood in any effort to promote research integrity.
Here we show that constructal-law physics unifies the design of animate and inanimate movement by requiring that larger bodies move farther, and their movement on the landscape last longer. The life span of mammals must scale as the body mass (M) raised to the power ¼, and the distance traveled during the lifetime must increase with body size. The same size effect on life span and distance traveled holds for the other flows that move mass on earth: atmospheric and oceanic jets and plumes, river basins, animals and human operated vehicles. The physics is the same for all flow systems on the landscape: the scaling rules of “design” are expressions of the natural tendency of all flow systems to generate designs that facilitate flow access. This natural tendency is the constructal law of design and evolution in nature. Larger bodies are more efficient movers of mass on the landscape.
Under high-strain-rate compression (strain rate approximately 10(3) s(-1)), nacre (mother-of-pearl) exhibits surprisingly high fracture strength vis-à-vis under quasi-static loading (strain rate 10(-3) s(-1)). Nevertheless, the underlying mechanism responsible for such sharply different behaviors in these two loading modes remains completely unknown. Here we report a new deformation mechanism, adopted by nacre, the best-ever natural armor material, to protect itself against predatory penetrating impacts. It involves the emission of partial dislocations and the onset of deformation twinning that operate in a well-concerted manner to contribute to the increased high-strain-rate fracture strength of nacre. Our findings unveil that Mother Nature delicately uses an ingenious strain-rate-dependent stiffening mechanism with a purpose to fight against foreign attacks. These findings should serve as critical design guidelines for developing engineered body armor materials.
Objective To examine how poor reporting and inadequate methods for key methodological features in randomised controlled trials (RCTs) have changed over the past three decades.Design Mapping of trials included in Cochrane reviews.Data sources Data from RCTs included in all Cochrane reviews published between March 2011 and September 2014 reporting an evaluation of the Cochrane risk of bias items: sequence generation, allocation concealment, blinding, and incomplete outcome data.Data extraction For each RCT, we extracted consensus on risk of bias made by the review authors and identified the primary reference to extract publication year and journal. We matched journal names with Journal Citation Reports to get 2014 impact factors.Main outcomes measures We considered the proportions of trials rated by review authors at unclear and high risk of bias as surrogates for poor reporting and inadequate methods, respectively.Results We analysed 20 920 RCTs (from 2001 reviews) published in 3136 journals. The proportion of trials with unclear risk of bias was 48.7% for sequence generation and 57.5% for allocation concealment; the proportion of those with high risk of bias was 4.0% and 7.2%, respectively. For blinding and incomplete outcome data, 30.6% and 24.7% of trials were at unclear risk and 33.1% and 17.1% were at high risk, respectively. Higher journal impact factor was associated with a lower proportion of trials at unclear or high risk of bias. The proportion of trials at unclear risk of bias decreased over time, especially for sequence generation, which fell from 69.1% in 1986-1990 to 31.2% in 2011-14 and for allocation concealment (70.1% to 44.6%). After excluding trials at unclear risk of bias, use of inadequate methods also decreased over time: from 14.8% to 4.6% for sequence generation and from 32.7% to 11.6% for allocation concealment.Conclusions Poor reporting and inadequate methods have decreased over time, especially for sequence generation and allocation concealment. But more could be done, especially in lower impact factor journals.
Biologists have devoted much attention to assortative mating or homogamy, the tendency for sexual species to mate with similar others. In contrast, there has been little theoretical work on the broader phenomenon of homophily, the tendency for individuals to interact with similar others. Yet this behaviour is also widely observed in nature. Here, we model how natural selection can give rise to homophily when individuals engage in social interaction in a population with multiple observable phenotypes. Payoffs to interactions depend on whether or not individuals have the same or different phenotypes, and each individual has a preference that determines how likely they are to interact with others of their own phenotype (homophily) or of opposite phenotypes (heterophily). The results show that homophily tends to evolve under a wide variety of conditions, helping to explain its ubiquity in nature.
Satellite temperature measurements do not support the recent claim of a “leveling off of warming” over the past two decades. Tropospheric warming trends over recent 20-year periods are always significantly larger (at the 10% level or better) than model estimates of 20-year trends arising from natural internal variability. Over the full 38-year period of the satellite record, the separation between observed warming and internal variability estimates is even clearer. In two out of three recent satellite datasets, the tropospheric warming from 1979 to 2016 is unprecedented relative to internally generated temperature trends on the 38-year timescale.
BACKGROUND: Previous work has noted that science stands as an ideological force insofar as the answers it offers to a variety of fundamental questions and concerns; as such, those who pursue scientific inquiry have been shown to be concerned with the moral and social ramifications of their scientific endeavors. No studies to date have directly investigated the links between exposure to science and moral or prosocial behaviors. METHODOLOGYPRINCIPAL FINDINGS: Across four studies, both naturalistic measures of science exposure and experimental primes of science led to increased adherence to moral norms and more morally normative behaviors across domains. Study 1 (n = 36) tested the natural correlation between exposure to science and likelihood of enforcing moral norms. Studies 2 (n = 49), 3 (n = 52), and 4 (n = 43) manipulated thoughts about science and examined the causal impact of such thoughts on imagined and actual moral behavior. Across studies, thinking about science had a moralizing effect on a broad array of domains, including interpersonal violations (Studies 1, 2), prosocial intentions (Study 3), and economic exploitation (Study 4). CONCLUSIONSSIGNIFICANCE: These studies demonstrated the morally normative effects of lay notions of science. Thinking about science leads individuals to endorse more stringent moral norms and exhibit more morally normative behavior. These studies are the first of their kind to systematically and empirically test the relationship between science and morality. The present findings speak to this question and elucidate the value-laden outcomes of the notion of science.