scholarly journals Publons Peer Evaluation Metrics are not Reliable Measures of Quality or Impact

2019 ◽  
Vol 14 (3) ◽  
pp. 153-155
Author(s):  
Scott Goldstein
Keyword(s):  
Research Area ◽  
Research Quality ◽  
Peer Evaluation ◽  
Event Data ◽  
Medical Sciences ◽  
Data Set ◽  
Maximum Value ◽  
Subject Areas ◽  
The Relationship ◽  
Pearson Correlations

A Review of: Ortega, J. L. (2019). Exploratory analysis of Publons metrics and their relationship with bibliometric and altmetric impact. Aslib Journal of Information Management, 71(1), 124– 136. https://doi.org/10.1108/AJIM-06-2018-0153 Abstract Objective – To analyze the relationship between scholars’ qualitative opinion of publications using Publons metrics and bibliometric and altmetric impact measures. Design – Comparative, quantitative data set analysis. Setting – Maximally exhaustive set of research articles retrievable from Publons. Subjects – 45,819 articles retrieved from Publons in January 2018. Methods – Author extracted article data from Publons and joined them (using the DOI) with data from three altmetric providers: Altmetric.com, PlumX, and Crossref Event Data. When providers gave discrepant results for the same metric, the maximum value was used. Publons data are described, and correlations are calculated between Publons metrics and altmetric and bibliometric indicators. Main Results – In terms of coverage, Publons is biased in favour of life sciences and subject areas associated with health and medical sciences. Open access publishers are also over-represented. Articles reviewed in Publons overwhelmingly have one or two pre-publication reviews and only one post-publication review. Furthermore, the metrics of significance and quality (rated on a 1 to 10 scale) are almost identically distributed, suggesting that users may not distinguish between them. Pearson correlations between Publons metrics and bibliometric and altmetric indicators are very weak and not significant. Conclusion – The biases in Publons coverage with respect to discipline and publisher support earlier research and suggest that the willingness to publish one’s reviews differs according to research area. Publons metrics are problematic as research quality indicators. Most publications have only a single post-publication review, and the absence of any significant disparity between the scores of significance and quality suggest the constructs are being conflated when in fact they should be measuring different things. The correlation analysis indicates that peer evaluation in Publons is not a measure of a work’s quality and impact.

scholarly journals Dynamics of Political Protests

2018 ◽  
Vol 72 (2) ◽  
pp. 485-521 ◽  
Author(s):  
Graig R. Klein ◽  
Patrick M. Regan
Keyword(s):  
Collective Action ◽  
The State ◽  
Event Data ◽  
Data Set ◽  
Government Response ◽  
Political Protests ◽  
The Arab Spring ◽  
The Relationship ◽  
State Responses ◽  
Cross National

AbstractThe links between protests and state responses have taken on increased visibility in light of the Arab Spring movements. But we still have unanswered questions about the relationship between protest behaviors and responses by the state. We frame this in terms of concession and disruption costs. Costs are typically defined as government behaviors that impede dissidents’ capacity for collective action. We change this causal arrow and hypothesize how dissidents can generate costs that structure the government's response to a protest. By disaggregating costs along dimensions of concession and disruption we extend our understanding of protest behaviors and the conditions under which they are more (or less) effective. Utilizing a new cross-national protest-event data set, we test our theoretical expectations against protests from 1990 to 2014 and find that when protesters generate high concession costs, the state responds in a coercive manner. Conversely, high disruption costs encourage the state to accommodate demands. Our research provides substantial insights and inferences about the dynamics of government response to protest.

scholarly journals Burnout and Socio-demographic Characteristics of Nurses in Iran

2014 ◽  
Vol 3 (4) ◽  
pp. 232-7
Author(s):  
Vahid Rashedi ◽  
Mohammad Rezaei ◽  
Masoud Gharib
Keyword(s):  
Maslach Burnout Inventory ◽  
Demographic Characteristics ◽  
Personal Accomplishment ◽  
Medical Sciences ◽  
Cross Sectional ◽  
Demographic Questionnaire ◽  
Managerial Strategies ◽  
Integrative Process ◽  
The Relationship ◽  
Pearson Correlations

Background: Nursing is considered as a profession at risk for high levels of stress and burnout, and these levels may be increasing as the care they deliver becomes complex. The purpose of this study was to investigate the relationship between burnout and socio-demographic characteristics of nurses.Materials and Methods: A cross-sectional descriptive-analytical design was used. The sample consisted of 194 nurses working in five hospitals of Hamadan University of Medical Sciences in Iran, who completed the Maslach Burnout Inventory (MBI) as well as a socio-demographic questionnaire. The data were analyzed using descriptive statistics, Pearson correlations, independent t-test and ANOVA.Results: Results indicated moderate levels of emotional exhaustion, depersonalization and low levels of personal accomplishment. There was significant relationship between burnout and age, length of employment, and educational level.Conclusion: Identifying an integrative process of burnout among nurses is an essential step in developing effective managerial strategies in order to address the problem. To prevent burnout, further research is necessary to determine the factors associated with it so that recommendations can be made for future wellness interventions. [GMJ. 2014;3(4):232-7]

A Review and evaluation of Machine Translation methods for Lumasaaba

2020 ◽  
pp. 3-17
Author(s):  
Peter Nabende
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Machine Translation ◽  
Language Processing ◽  
Research Area ◽  
Data Driven ◽  
East African ◽  
Data Set ◽  
African Languages ◽  
Translation Methods

Natural Language Processing for under-resourced languages is now a mainstream research area. However, there are limited studies on Natural Language Processing applications for many indigenous East African languages. As a contribution to covering the current gap of knowledge, this paper focuses on evaluating the application of well-established machine translation methods for one heavily under-resourced indigenous East African language called Lumasaaba. Specifically, we review the most common machine translation methods in the context of Lumasaaba including both rule-based and data-driven methods. Then we apply a state of the art data-driven machine translation method to learn models for automating translation between Lumasaaba and English using a very limited data set of parallel sentences. Automatic evaluation results show that a transformer-based Neural Machine Translation model architecture leads to consistently better BLEU scores than the recurrent neural network-based models. Moreover, the automatically generated translations can be comprehended to a reasonable extent and are usually associated with the source language input.

An Enhancement of Feature Selection Algorithm for EDM: A Review

2018 ◽  
Vol 8 (5) ◽  
pp. 29
Author(s):  
Manpreet Kaur ◽  
Chamkaur Singh
Keyword(s):  
Feature Selection ◽  
Educational Data Mining ◽  
Problem Formulation ◽  
Research Area ◽  
Education Quality ◽  
Educational Institutions ◽  
Selection Algorithm ◽  
Positive Role ◽  
Data Set ◽  
Selection Algorithms

Educational Data Mining (EDM) is an emerging research area help the educational institutions to improve the performance of their students. Feature Selection (FS) algorithms remove irrelevant data from the educational dataset and hence increases the performance of classifiers used in EDM techniques. This paper present an analysis of the performance of feature selection algorithms on student data set. .In this papers the different problems that are defined in problem formulation. All these problems are resolved in future. Furthermore the paper is an attempt of playing a positive role in the improvement of education quality, as well as guides new researchers in making academic intervention.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

Approximate Bayesian inference for joint linear and partially linear modeling of longitudinal zero-inflated count and time to event data

2021 ◽  
pp. 096228022110028
Author(s):  
T Baghfalaki ◽  
M Ganjali
Keyword(s):  
Linear Model ◽  
Joint Modeling ◽  
Partially Linear Model ◽  
Event Data ◽  
Time To Event ◽  
Data Set ◽  
Partially Linear ◽  
Time To Event Data ◽  
Count Response ◽  
Approximate Bayesian

Joint modeling of zero-inflated count and time-to-event data is usually performed by applying the shared random effect model. This kind of joint modeling can be considered as a latent Gaussian model. In this paper, the approach of integrated nested Laplace approximation (INLA) is used to perform approximate Bayesian approach for the joint modeling. We propose a zero-inflated hurdle model under Poisson or negative binomial distributional assumption as sub-model for count data. Also, a Weibull model is used as survival time sub-model. In addition to the usual joint linear model, a joint partially linear model is also considered to take into account the non-linear effect of time on the longitudinal count response. The performance of the method is investigated using some simulation studies and its achievement is compared with the usual approach via the Bayesian paradigm of Monte Carlo Markov Chain (MCMC). Also, we apply the proposed method to analyze two real data sets. The first one is the data about a longitudinal study of pregnancy and the second one is a data set obtained of a HIV study.

Railroad Integration and Uneven Development on the European Periphery, 1870–1910

2021 ◽  
Vol 45 (2) ◽  
pp. 261-289
Author(s):  
Eduard J. Alvarez-Palau ◽  
Alfonso Díez-Minguela ◽  
Jordi Martí-Henneberg
Keyword(s):  
Economic Development ◽  
Positive Impact ◽  
Data Set ◽  
Per Capita Gdp ◽  
Catching Up ◽  
Nation States ◽  
Railroad Network ◽  
Per Capita ◽  
European Periphery ◽  
The Relationship

AbstractThis study explores the relationship between railroad integration and regional development on the European periphery between 1870 and 1910, based on a regional data set including 291 spatial units. Railroad integration is proxied by railroad density, while per capita GDP is used as an indicator of economic development. The period under study is of particular relevance as it has been associated with the second wave of railroad construction in Europe and also coincides with the industrialization of most of the continent. Overall, we found that railroads had a significant and positive impact on the growth of per capita GDP across Europe. The magnitude of this relationship appears to be relatively modest, but the results obtained are robust with respect to a number of different specifications. From a geographical perspective, we found that railroads had a significantly greater influence on regions located in countries on the northern periphery of Europe than in other outlying areas. They also helped the economies of these areas to begin the process of catching up with the continent’s industrialized core. In contrast, the regions on the southern periphery showed lower levels of economic growth, with this exacerbating the preexisting divergence in economic development. The expansion of the railroad network in them was unable to homogenize the diffusion of economic development and tended to further benefit the regions that were already industrialized. In most of the cases, the capital effect was magnified, and this contributed to the consolidation of newly created nation-states.

scholarly journals RESTING HEART RATE MODERATES THE RELATIONSHIP BETWEEN NEUROPSYCHIATRIC SYMPTOMS, MCI, AND ALZHEIMER’S DISEASE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S641-S641
Author(s):  
Shanna L Burke
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Heart Rate ◽  
Relative Risk ◽  
Neuropsychiatric Symptoms ◽  
Cognitive Status ◽  
Resting Heart Rate ◽  
Data Set ◽  
Increased Risk ◽  
The Relationship

Abstract Little is known about how resting heart rate moderates the relationship between neuropsychiatric symptoms and cognitive status. This study examined the relative risk of NPS on increasingly severe cognitive statuses and examined the extent to which resting heart rate moderates this relationship. A secondary analysis of the National Alzheimer’s Coordinating Center Uniform Data Set was undertaken, using observations from participants with normal cognition at baseline (13,470). The relative risk of diagnosis with a more severe cognitive status at a future visit was examined using log-binomial regression for each neuropsychiatric symptom. The moderating effect of resting heart rate among those who are later diagnosed with mild cognitive impairment (MCI) or Alzheimer’s disease (AD) was assessed. Delusions, hallucinations, agitation, depression, anxiety, elation, apathy, disinhibition, irritability, motor disturbance, nighttime behaviors, and appetite disturbance were all significantly associated (p<.001) with an increased risk of AD, and a reduced risk of MCI. Resting heart rate increased the risk of AD but reduced the relative risk of MCI. Depression significantly interacted with resting heart rate to increase the relative risk of MCI (RR: 1.07 (95% CI: 1.00-1.01), p<.001), but not AD. Neuropsychiatric symptoms increase the relative risk of AD but not MCI, which may mean that the deleterious effect of NPS is delayed until later and more severe stages of the disease course. Resting heart rate increases the relative risk of MCI among those with depression. Practitioners considering early intervention in neuropsychiatric symptomology may consider the downstream benefits of treatment considering the long-term effects of NPS.

scholarly journals Spatial pattern and genetic diversity estimates are linked in stochastic models of population differentiation

2000 ◽  
Vol 23 (3) ◽  
pp. 541-544 ◽  
Author(s):  
José Alexandre Felizola Diniz-Filho ◽  
Mariana Pires de Campos Telles
Keyword(s):  
Genetic Diversity ◽  
Spatial Pattern ◽  
Stochastic Models ◽  
Population Differentiation ◽  
Real Data ◽  
Population Heterogeneity ◽  
Data Set ◽  
Mantel’S Test ◽  
The Relationship ◽  
Diversity Estimates

In the present study, we used both simulations and real data set analyses to show that, under stochastic processes of population differentiation, the concepts of spatial heterogeneity and spatial pattern overlap. In these processes, the proportion of variation among and within a population (measured by G ST and 1 - G ST, respectively) is correlated with the slope and intercept of a Mantel's test relating genetic and geographic distances. Beyond the conceptual interest, the inspection of the relationship between population heterogeneity and spatial pattern can be used to test departures from stochasticity in the study of population differentiation.

Metric for Disassembly and Reuse Decisions: Formulation and Validation

2008 ◽  
Author(s):  
Vijitashwa Pandey ◽  
Deborah Thurston
Keyword(s):  
Maximum Likelihood ◽  
Value Function ◽  
Choice Theory ◽  
Decision Makers ◽  
Maximum Likelihood Estimates ◽  
Likelihood Method ◽  
Maximum Value ◽  
Long Range Planning ◽  
The Relationship ◽  
The Value Function

Design for disassembly and reuse focuses on developing methods to minimize difficulty in disassembly for maintenance or reuse. These methods can gain substantially if the relationship between component attributes (material mix, ease of disassembly etc.) and their likelihood of reuse or disposal is understood. For products already in the marketplace, a feedback approach that evaluates willingness of manufacturers or customers (decision makers) to reuse a component can reveal how attributes of a component affect reuse decisions. This paper introduces some metrics and combines them with ones proposed in literature into a measure that captures the overall value of a decision made by the decision makers. The premise is that the decision makers would choose a decision that has the maximum value. Four decisions are considered regarding a component’s fate after recovery ranging from direct reuse to disposal. A method on the lines of discrete choice theory is utilized that uses maximum likelihood estimates to determine the parameters that define the value function. The maximum likelihood method can take inputs from actual decisions made by the decision makers to assess the value function. This function can be used to determine the likelihood that the component takes a certain path (one of the four decisions), taking as input its attributes, which can facilitate long range planning and also help determine ways reuse decisions can be influenced.

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