On the shoulders of students? The contribution of PhD students to the advancement of knowledge

Using the participation in peer reviewed publications of all doctoral students in Quebec over the 2000-2007 period this paper provides the first large scale analysis of their research effort. It shows that PhD students contribute to about a third of the publication output of the province, with doctoral students in the natural and medical sciences being present in a higher proportion of papers published than their colleagues of the social sciences and humanities. Collaboration is an important component of this socialization: disciplines in which student collaboration is higher are also those in which doctoral students are the most involved in peer-reviewed publications. In terms of scientific impact, papers co-signed by doctorate students obtain significantly lower citation rates than other Quebec papers, except in natural sciences and engineering. Finally, this paper shows that involving doctoral students in publications is positively linked with degree completion and ulterior career in research.Comment: 41 pages, 7 figures, forthcoming in Scientometric

On the relationship between interdisciplinarity and scientific impact

This paper analyzes the effect of interdisciplinarity on the scientific impact of individual papers. Using all the papers published in Web of Science in 2000, we define the degree of interdisciplinarity of a given paper as the percentage of its cited references made to journals of other disciplines. We show that, although for all disciplines combined there is no clear correlation between the level of interdisciplinarity of papers and their citation rates, there are nonetheless some disciplines in which a higher level of interdisciplinarity is related to a higher citation rates. For other disciplines, citations decline as interdisciplinarity grows. One characteristic is visible in all disciplines: highly disciplinary and highly interdisciplinary papers have a low scientific impact. This suggests that there might be an optimum of interdisciplinarity beyond which the research is too dispersed to find its niche and under which it is too mainstream to have high impact. Finally, the relationship between interdisciplinarity and scientific impact is highly determined by the citation characteristics of the disciplines involved: papers citing citation intensive disciplines are more likely to be cited by those disciplines and, hence, obtain higher citation scores than papers citing non citation intensive disciplines.Comment: 10 pages, 3 figures, 1 table. Forthcoming in JASIS

Controlling for the effects of information in a public goods discrete choice model

This paper develops a reduced form method of controlling for differences in information sets of subjects in public good discrete choice models, using stated preference data. The main contribution of our method comes from accounting for the effect of information provided during a survey on the mean and the variance of individual-specific scale parameters. In this way we incorporate both scale heterogeneity as well as observed and unobserved preference heterogeneity to investigate differences across and within information treatments. Our approach will also be useful to researchers who want to combine stated preference data sets while controlling for scale differences. We illustrate our approach using the data from a discrete choice experiment study of a biodiversity conservation program and find that the mean of individual-specific scale parameters and its variance in the sample is sensitive to the information set provided to the respondents

\u3ci\u3eHoplistoscelis Sordidus\u3c/i\u3e (Heteroptera: Nabidae) in Canada

Hoplistoscelis sordidus is recorded for the first time from Canada. The distribution of the species, its establishment in Canada, and its bionomics are discussed. Characters are given that distinguish Hoplistoscelis from all other eastern Canadian genera of Nabinae. The potential role of the genus as a biological control agent is also briefly outlined

The weakening relationship between the Impact Factor and papers' citations in the digital age

Historically, papers have been physically bound to the journal in which they were published but in the electronic age papers are available individually, no longer tied to their respective journals. Hence, papers now can be read and cited based on their own merits, independently of the journal's physical availability, reputation, or Impact Factor. We compare the strength of the relationship between journals' Impact Factors and the actual citations received by their respective papers from 1902 to 2009. Throughout most of the 20th century, papers' citation rates were increasingly linked to their respective journals' Impact Factors. However, since 1990, the advent of the digital age, the strength of the relation between Impact Factors and paper citations has been decreasing. This decrease began sooner in physics, a field that was quicker to make the transition into the electronic domain. Furthermore, since 1990, the proportion of highly cited papers coming from highly cited journals has been decreasing, and accordingly, the proportion of highly cited papers not coming from highly cited journals has also been increasing. Should this pattern continue, it might bring an end to the use of the Impact Factor as a way to evaluate the quality of journals, papers and researchers.Comment: 14 pages, 5 figure

Estimating Open Access Mandate Effectiveness: The MELIBEA Score

MELIBEA is a Spanish database that uses a composite formula with eight weighted conditions to estimate the effectiveness of Open Access mandates (registered in ROARMAP). We analyzed 68 mandated institutions for publication years 2011-2013 to determine how well the MELIBEA score and its individual conditions predict what percentage of published articles indexed by Web of Knowledge is deposited in each institution's OA repository, and when. We found a small but significant positive correlation (0.18) between MELIBEA score and deposit percentage. We also found that for three of the eight MELIBEA conditions (deposit timing, internal use, and opt-outs), one value of each was strongly associated with deposit percentage or deposit latency (immediate deposit required, deposit required for performance evaluation, unconditional opt-out allowed for the OA requirement but no opt-out for deposit requirement). When we updated the initial values and weights of the MELIBEA formula for mandate effectiveness to reflect the empirical association we had found, the score's predictive power doubled (.36). There are not yet enough OA mandates to test further mandate conditions that might contribute to mandate effectiveness, but these findings already suggest that it would be useful for future mandates to adopt these three conditions so as to maximize their effectiveness, and thereby the growth of OA.Comment: 27 pages, 13 figures, 3 tables, 40 references, 7761 word

Testing the Finch Hypothesis on Green OA Mandate Ineffectiveness

We have now tested the Finch Committee's Hypothesis that Green Open Access Mandates are ineffective in generating deposits in institutional repositories. With data from ROARMAP on institutional Green OA mandates and data from ROAR on institutional repositories, we show that deposit number and rate is significantly correlated with mandate strength (classified as 1-12): The stronger the mandate, the more the deposits. The strongest mandates generate deposit rates of 70%+ within 2 years of adoption, compared to the un-mandated deposit rate of 20%. The effect is already detectable at the national level, where the UK, which has the largest proportion of Green OA mandates, has a national OA rate of 35%, compared to the global baseline of 25%. The conclusion is that, contrary to the Finch Hypothesis, Green Open Access Mandates do have a major effect, and the stronger the mandate, the stronger the effect (the Liege ID/OA mandate, linked to research performance evaluation, being the strongest mandate model). RCUK (as well as all universities, research institutions and research funders worldwide) would be well advised to adopt the strongest Green OA mandates and to integrate institutional and funder mandates.Comment: 6 pages, 1 table, 4 figure

Imputation of truncated p-values for meta-analysis methods and its genomic application

Microarray analysis to monitor expression activities in thousands of genes simultaneously has become routine in biomedical research during the past decade. A tremendous amount of expression profiles are generated and stored in the public domain and information integration by meta-analysis to detect differentially expressed (DE) genes has become popular to obtain increased statistical power and validated findings. Methods that aggregate transformed $p$-value evidence have been widely used in genomic settings, among which Fisher's and Stouffer's methods are the most popular ones. In practice, raw data and $p$-values of DE evidence are often not available in genomic studies that are to be combined. Instead, only the detected DE gene lists under a certain $p$-value threshold (e.g., DE genes with $p$-value${}<0.001$) are reported in journal publications. The truncated $p$-value information makes the aforementioned meta-analysis methods inapplicable and researchers are forced to apply a less efficient vote counting method or na\"{i}vely drop the studies with incomplete information. The purpose of this paper is to develop effective meta-analysis methods for such situations with partially censored $p$-values. We developed and compared three imputation methods - mean imputation, single random imputation and multiple imputation - for a general class of evidence aggregation methods of which Fisher's and Stouffer's methods are special examples. The null distribution of each method was analytically derived and subsequent inference and genomic analysis frameworks were established. Simulations were performed to investigate the type I error, power and the control of false discovery rate (FDR) for (correlated) gene expression data. The proposed methods were applied to several genomic applications in colorectal cancer, pain and liquid association analysis of major depressive disorder (MDD). The results showed that imputation methods outperformed existing na\"{i}ve approaches. Mean imputation and multiple imputation methods performed the best and are recommended for future applications.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS747 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org