Typologie des noms communs de personne et féminisation linguistique

Pour l’Académie française, le genre masculin, non-marqué, représenterait à lui seul les deux genres, alors que la marque du féminin serait privative et entraînerait une limitation dont le masculin est exempt, instituant chez les êtres animés une ségrégation. Par conséquent, pour assurer l’égalité, l’Académie recommande que les termes de métier non-consacrés par l’usage soient au masculin. Or, une telle position ne respecte pas les structures linguistiques du français parce que les dénominations professionnelles non seulement sont soumises, structuralement, aux variations morphologiques du genre, mais font partie de classes sémantiques déterminées qui exigent une telle variation et sont assujetties à certaines règles syntaxiques propres. La démonstration en sera faite à l’intérieur d’une étude qui englobe tous les noms communs de personne, offrant ainsi un tableau complet de la représentation humaine.According to the French Academy, the masculine gender, as the unmarked gender, can represent both genders, while the mark of the feminine would be privative and would bring about a limitation from which the masculine is free, thus creating segregation among animate beings. Consequently, in order to provide equality between women and men, the Academy recommends the masculine form for professional designations, except for the feminine forms already accepted. We believe that such a position fails to respect the structures of French because professional designations are submitted to the morphological variation of gender, belong to a specific semantic class, and obey syntactical rules proper to that class. This will be demonstrated in a study including all common nouns designating human beings as well, thus offering a full portrait of human representation

Doctoral students’ access to non-academic support for mental health

Increased doctoral student numbers has led to a growth in studies dedicated to doctoral experience. These studies have raised a range of mental health concerns around workload, supervision processes and student well-being. Despite these challenges being well documented, few studies have looked at doctoral student’s experiences of accessing non-academic support services. This article presents the findings of a mixed-method study to investigate doctoral experiences of non-academic support, conducted at one British university with a large postgraduate research population. Drawing on focus groups and a student survey, the article concludes that many doctoral students are not accessing institutional support when they could benefit from it, with many turning to external support mechanisms including family, personal doctor and online resources. Five institutional recommendations are proposed to develop improved dedicated doctoral student mental health support: clear signposting, online self-help, workshops, parity of support and supervisor training

Modeling a century of citation distributions

The prevalence of uncited papers or of highly cited papers, with respect to the bulk of publications, provides important clues as to the dynamics of scientific research. Using 25 million papers and 600 million references from the Web of Science over the 1900–2006 period, this paper proposes a simple model based on a random selection process to explain the “uncitedness” phenomenon and its decline over the years. We show that the proportion of cited papers is a function of (1) the number of articles available (the competing papers), (2) the number of citing papers and (3) the number of references they contain. Using uncitedness as a departure point, we demonstrate the utility of the stretched-exponential function and a form of the Tsallis q-exponential function to fit complete citation distributions over the 20th century. As opposed to simple power-law fits, for instance, both these approaches are shown to be empirically well-grounded and robust enough to better understand citation dynamics at the aggregate level. On the basis of these models, we provide quantitative evidence and provisional explanations for an important shift in citation practices around 1960. We also propose a revision of the “citation classic” category as a set of articles which is clearly distinguishable from the rest of the field

Ensembles of probability estimation trees for customer churn prediction

Customer churn prediction is one of the most, important elements tents of a company's Customer Relationship Management, (CRM) strategy In tins study, two strategies are investigated to increase the lift. performance of ensemble classification models, i.e (1) using probability estimation trees (PETs) instead of standard decision trees as base classifiers; and (n) implementing alternative fusion rules based on lift weights lot the combination of ensemble member's outputs Experiments ale conducted lot font popular ensemble strategics on five real-life chin n data sets In general, the results demonstrate how lift performance can be substantially improved by using alternative base classifiers and fusion tides However: the effect vanes lot the (Idol cut ensemble strategies lit particular, the results indicate an increase of lift performance of (1) Bagging by implementing C4 4 base classifiets. (n) the Random Subspace Method (RSM) by using lift-weighted fusion rules, and (in) AdaBoost, by implementing both

A small world of citations? The influence of collaboration networks on citation practices

This paper examines the proximity of authors to those they cite using degrees of separation in a co-author network, essentially using collaboration networks to expand on the notion of self-citations. While the proportion of direct self-citations (including co-authors of both citing and cited papers) is relatively constant in time and across specialties in the natural sciences (10% of citations) and the social sciences (20%), the same cannot be said for citations to authors who are members of the co-author network. Differences between fields and trends over time lie not only in the degree of co-authorship which defines the large-scale topology of the collaboration network, but also in the referencing practices within a given discipline, computed by defining a propensity to cite at a given distance within the collaboration network. Overall, there is little tendency to cite those nearby in the collaboration network, excluding direct self-citations. By analyzing these social references, we characterize the social capital of local collaboration networks in terms of the knowledge production within scientific fields. These results have implications for the long-standing debate over biases common to most types of citation analysis, and for understanding citation practices across scientific disciplines over the past 50 years. In addition, our findings have important practical implications for the availability of 'arm's length' expert reviewers of grant applications and manuscripts

The use of bibliometrics for assessing research : possibilities, limitations and adverse effects

Researchers are used to being evaluated: publications, hiring, tenure and funding decisions are all based on the evaluation of research. Traditionally, this evaluation relied on judgement of peers but, in the light of limited resources and increased bureaucratization of science, peer review is getting more and more replaced or complemented with bibliometric methods. Central to the introduction of bibliometrics in research evaluation was the creation of the Science Citation Index (SCI)in the 1960s, a citation database initially developed for the retrieval of scientific information. Embedded in this database was the Impact Factor, first used as a tool for the selection of journals to cover in the SCI, which then became a synonym for journal quality and academic prestige. Over the last 10 years, this indicator became powerful enough to influence researchers’ publication patterns in so far as it became one of the most important criteria to select a publication venue. Regardless of its many flaws as a journal metric and its inadequacy as a predictor of citations on the paper level, it became the go-to indicator of research quality and was used and misused by authors, editors, publishers and research policy makers alike. The h-index, introduced as an indicator of both output and impact combined in one simple number, has experienced a similar fate, mainly due to simplicity and availability. Despite their massive use, these measures are too simple to capture the complexity and multiple dimensions of research output and impact. This chapter provides an overview of bibliometric methods, from the development of citation indexing as a tool for information retrieval to its application in research evaluation, and discusses their misuse and effects on researchers’ scholarly communication behavior

Large publishing consortia produce higher citation impact research but co-author contributions are hard to evaluate

This paper introduces a simple agglomerative clustering method to identify large publishing consortia with at least 20 authors and 80% shared authorship between articles. Based on Scopus journal articles 1996-2018, under these criteria, nearly all (88%) of the large consortia published research with citation impact above the world average, with the exceptions being mainly the newer consortia for which average citation counts are unreliable. On average, consortium research had almost double (1.95) the world average citation impact on the log scale used (Mean Normalised Log Citation Score). At least partial alphabetical author ordering was the norm in most consortia. The 250 largest consortia were for nuclear physics and astronomy around expensive equipment, and for predominantly health-related issues in genomics, medicine, public health, microbiology and neuropsychology. For the health-related issues, except for the first and last few authors, authorship seem to primary indicate contributions to the shared project infrastructure necessary to gather the raw data. It is impossible for research evaluators to identify the contributions of individual authors in the huge alphabetical consortia of physics and astronomy, and problematic for the middle and end authors of health-related consortia. For small scale evaluations, authorship contribution statements could be used, when available

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

Reviewing, indicating, and counting books for modern research evaluation systems

In this chapter, we focus on the specialists who have helped to improve the conditions for book assessments in research evaluation exercises, with empirically based data and insights supporting their greater integration. Our review highlights the research carried out by four types of expert communities, referred to as the monitors, the subject classifiers, the indexers and the indicator constructionists. Many challenges lie ahead for scholars affiliated with these communities, particularly the latter three. By acknowledging their unique, yet interrelated roles, we show where the greatest potential is for both quantitative and qualitative indicator advancements in book-inclusive evaluation systems.Comment: Forthcoming in Glanzel, W., Moed, H.F., Schmoch U., Thelwall, M. (2018). Springer Handbook of Science and Technology Indicators. Springer Some corrections made in subsection 'Publisher prestige or quality