1,720,977 research outputs found
K-Alpha Calculator–Krippendorff’s Alpha Calculator: A user-friendly tool for computing Krippendorff’s Alpha inter-rater reliability coefficient
Full text linkKrippendorff’s Alpha is a measure for assessing inter-rater reliability, facilitating triangulated evaluations among multiple raters. Indeed, Krippendorff’s Alpha is key in validating the depend- ability of human assessments, thereby reinforcing the robustness of human-based choices in con- texts where interpretive variability could otherwise undermine the research outcomes. Despite its versatility across various data types, the procedure for computing this coefficient might limit its applicability for researchers unfamiliar with specialised statistical software. Addressing this issue, this paper introduces the “K-Alpha Calculator ”—Krippendorff’s Alpha Calculator —a freely accessible, user-friendly, web application available at https://www.k-alpha.org designed for easy computation of Krippendorff’s Alpha. By offering a web interface without any software depen- dency, the K-Alpha Calculator seeks to promote the broader integration of such a reliability metric in research processes. We envisage that the tool’s contribution could support researchers in enhancing methodological rigour, fostering conclusions are rooted in triangulated interpretations and assessments. The K-Alpha Calculator is both a computational tool and an educational re- source, encouraging more researchers to include reliability measures in their studies
SKraken: Fast and sensitive classification of short metagenomic reads based on filtering uninformative k-mers
Full text linkThe study of microbial communities is an emerging field that is revolutionizing many disciplines from ecology to medicine. The major problem when analyzing a metagenomic sample is to taxonomic annotate its reads in order to identify the species in the sample and their relative abundance. Many tools have been developed in the recent years, however the performance in terms of precision and speed are not always adequate for these very large datasets. In this work we present SKraken an efficient approach to accurately classify metagenomic reads against a set of reference genomes, e.g. the NCBI/RefSeq database. SKraken is based on k-mers statistics combined with the taxonomic tree. Given a set of target genomes SKraken is able to detect the most representative k-mers for each species, filtering out uninformative k-mers. The classification performance on several synthetic and real metagenomics datasets shows that SKraken achieves in most cases the best performances in terms of precision and ..
Hierarchical decision-making produces persistent differences in learning performance
Full text linkHuman organizations are commonly characterized by a hierarchical chain of command that facilitates division of labor and integration of effort. Higher-level employees set the strategic frame that constrains lower-level employees who carry out the detailed operations serving to implement the strategy. Typically, strategy and operational decisions are carried out by different individuals that act over different timescales and rely on different kinds of information. We hypothesize that when such decision processes are hierarchically distributed among different individuals, they produce highly heterogeneous and strongly path-dependent joint learning dynamics. To investigate this, we design laboratory experiments of human dyads facing repeated joint tasks, in which one individual is assigned the role of carrying out strategy decisions and the other operational ones. The experimental behavior generates a puzzling bimodal performance distribution-some pairs learn, some fail to learn after a few periods. We also develop a computational model that mirrors the experimental settings and predicts the heterogeneity of performance by human dyads. Comparison of experimental and simulation data suggests that self-reinforcing dynamics arising from initial choices are sufficient to explain the performance heterogeneity observed experimentally
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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