Which bills are lobbied? Predicting and interpreting lobbying activity in the US

Using lobbying data from OpenSecrets.org, we offer several experiments applying machine learning techniques to predict if a piece of legislation (US bill) has been subjected to lobbying activities or not. We also investigate the influence of the intensity of the lobbying activity on how discernible a lobbied bill is from one that was not subject to lobbying. We compare the performance of a number of different models (logistic regression, random forest, CNN and LSTM) and text embedding representations (BOW, TF-IDF, GloVe, Law2Vec). We report results of above 0.85\% ROC AUC scores, and 78\% accuracy. Model performance significantly improves (95\% ROC AUC, and 88\% accuracy) when bills with higher lobbying intensity are looked at. We also propose a method that could be used for unlabelled data. Through this we show that there is a considerably large number of previously unlabelled US bills where our predictions suggest that some lobbying activity took place. We believe our method could potentially contribute to the enforcement of the US Lobbying Disclosure Act (LDA) by indicating the bills that were likely to have been affected by lobbying but were not filed as such

Metrics to evaluate research performance in academic institutions: A critique of ERA 2010 as applied in forestry and the indirect H2 index as a possible alternative

Excellence for Research in Australia (ERA) is an attempt by the Australian Research Council to rate Australian universities on a 5-point scale within 180 Fields of Research using metrics and peer evaluation by an evaluation committee. Some of the bibliometric data contributing to this ranking suffer statistical issues associated with skewed distributions. Other data are standardised year-by-year, placing undue emphasis on the most recent publications which may not yet have reliable citation patterns. The bibliometric data offered to the evaluation committees is extensive, but lacks effective syntheses such as the h-index and its variants. The indirect H2 index is objective, can be computed automatically and efficiently, is resistant to manipulation, and a good indicator of impact to assist the ERA evaluation committees and to similar evaluations internationally.Comment: 19 pages, 6 figures, 7 tables, appendice

The intellectual influence of economic journals: quality versus quantity

The evaluation of scientific output has a key role in the allocation of research funds and academic positions. Decisions are often based on quality indicators for academic journals, and over the years, a handful of scoring methods have been proposed for this purpose. Discussing the most prominent methods (de facto standards) we show that they do not distinguish quality from quantity at article level. The systematic bias we find is analytically tractable and implies that the methods are manipulable. We introduce modified methods that correct for this bias, and use them to provide rankings of economic journals. Our methodology is transparent; our results are replicable

Examining the Moderating Role of Rational-Versus Emotional-Focused Websites: The Case of Boutique Hotels

This article examines whether emotional or rational advertising appeals are more effective for website hospitality services. Specifically, it considers how attitudes towards websites, service expectations and attitudes towards boutique hotels may influence the two different types of advertising appeals and purchase intention. Results show that websites using emotional appeals tend to show a positive relationship between attitude towards hotels and attitude towards websites and purchase intention. It also indicates that emotional advertisements are better at gaining and retaining interest and attention, and as such can be highly beneficial for small boutique hotels. This article provides several marketing and business policy implications to aid practitioners and strategists in making better decisions

Bowling Together: Scientific Collaboration Networks of Demographers at European Population Conferences

Studies of collaborative networks of demographers are relatively scarce. Similar studies in other social sciences provide insight into scholarly trends of both the fields and characteristics of their successful scientists. Exploiting a unique database of metadata for papers presented at six European Population Conferences, this report explores factors explaining research collaboration among demographers. We find that (1) collaboration among demographers has increased over the past 10 years, however, among co-authored papers, collaboration across institutions remains relatively unchanged over the period, (2) papers based on core demographic subfields such as fertility, mortality, migration and data and methods are more likely to involve multiple authors and (3) multiple author teams that are all female are less likely to co-author with colleagues in different institutions. Potential explanations for these results are discussed alongside comparisons with similar studies of collaboration networks in other related social sciences

Impact Factor: outdated artefact or stepping-stone to journal certification?

A review of Garfield's journal impact factor and its specific implementation as the Thomson Reuters Impact Factor reveals several weaknesses in this commonly-used indicator of journal standing. Key limitations include the mismatch between citing and cited documents, the deceptive display of three decimals that belies the real precision, and the absence of confidence intervals. These are minor issues that are easily amended and should be corrected, but more substantive improvements are needed. There are indications that the scientific community seeks and needs better certification of journal procedures to improve the quality of published science. Comprehensive certification of editorial and review procedures could help ensure adequate procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table

Do Author-Suggested Reviewers Rate Submissions More Favorably than Editor-Suggested Reviewers? A Study on Atmospheric Chemistry and Physics

Background: Ratings in journal peer review can be affected by sources of bias. The bias variable investigated here was the information on whether authors had suggested a possible reviewer for their manuscript, and whether the editor had taken up that suggestion or had chosen a reviewer that had not been suggested by the authors. Studies have shown that authorsuggested reviewers rate manuscripts more favorably than editor-suggested reviewers do. Methodology/Principal Findings: Reviewers ’ ratings on three evaluation criteria and the reviewers ’ final publication recommendations were available for 552 manuscripts (in total 1145 reviews) that were submitted to Atmospheric Chemistry and Physics, an interactive open access journal using public peer review (authors ’ and reviewers ’ comments are publicly exchanged). Public peer review is supposed to bring a new openness to the reviewing process that will enhance its objectivity. In the statistical analysis the quality of a manuscript was controlled for to prevent favorable reviewers ’ ratings from being attributable to quality instead of to the bias variable. Conclusions/Significance: Our results agree with those from other studies that editor-suggested reviewers rated manuscripts between 30 % and 42 % less favorably than author-suggested reviewers. Against this backdrop journal editors should consider either doing without the use of author-suggested reviewers or, if they are used, bringing in more than one editor-suggested reviewer for the review process (so that the review by author-suggested reviewers can be put i