scholarly journals Plasma Plus Iron Therapy in Congenital Hypotransferrinemia in the Second Decade: a Dynamic Approach to Maintain Hematological Stability

Author(s):  
Deniz Aslan
1972 ◽  
Vol 17 (2) ◽  
pp. 79-79
Author(s):  
JAMES BIERI
Keyword(s):  

PsycCRITIQUES ◽  
2006 ◽  
Vol 51 (22) ◽  
Author(s):  
Francine Conway ◽  
Nina Finkel
Keyword(s):  

2013 ◽  
Author(s):  
Ashraf Soliman ◽  
Mohamed Yassin ◽  
Osman Abdelrahmanm ◽  
Vincenzo Desanctis ◽  
Ahmed Elawwa

2008 ◽  
Vol 12 (1) ◽  
pp. 1-26
Author(s):  
So-Woo Chung
Keyword(s):  

2019 ◽  
pp. 94-102
Author(s):  
A.A. Kochkarov ◽  
◽  
N.V. Kalashnikov ◽  
R.A. Kochkarov ◽  
◽  
...  

2020 ◽  
Author(s):  
Claudia Mazzuca ◽  
Matteo Santarelli

The concept of gender has been the battleground of scientific and political speculations for a long time. On the one hand, some accounts contended that gender is a biological feature, while on the other hand some scholars maintained that gender is a socio-cultural construct (e.g., Butler, 1990; Risman, 2004). Some of the questions that animated the debate on gender over history are: how many genders are there? Is gender rooted in our biological asset? Are gender and sex the same thing? All of these questions entwine one more crucial, and often overlooked interrogative. How is it possible for a concept to be the purview of so many disagreements and conceptual redefinitions? The question that this paper addresses is therefore not which specific account of gender is preferable. Rather, the main question we will address is how and why is even possible to disagree on how gender should be considered. To provide partial answers to these questions, we suggest that gender/sex (van Anders, 2015; Fausto-Sterling, 2019) is an illustrative example of politicized concepts. We show that no concepts are political in themselves; instead, some concepts are subjected to a process involving a progressive detachment from their supposed concrete referent (i.e., abstractness), a tension to generalizability (i.e., abstraction), a partial indeterminacy (i.e., vagueness), and the possibility of being contested (i.e., contestability). All of these features differentially contribute to what we call the politicization of a concept. In short, we will claim that in order to politicize a concept, a possible strategy is to evidence its more abstract facets, without denying its more embodied and perceptual components (Borghi et al., 2019). So, we will first outline how gender has been treated in psychological and philosophical discussions, to evidence its essentially contestable character thereby showing how it became a politicized concept. Then we will review some of the most influential accounts of political concepts, arguing that currently they need to be integrated with more sophisticated distinctions (e.g., Koselleck, 2004). The notions gained from the analyses of some of the most important accounts of political concepts in social sciences and philosophy will allow us to implement a more dynamic approach to political concepts. Specifically, when translated into the cognitive science framework, these reflections will help us clarifying some crucial aspects of the nature of politicized concepts. Bridging together social and cognitive sciences, we will show how politicized concepts are abstract concepts, or better abstract conceptualizations.


2020 ◽  
Author(s):  
Kun Sun

Expectations or predictions about upcoming content play an important role during language comprehension and processing. One important aspect of recent studies of language comprehension and processing concerns the estimation of the upcoming words in a sentence or discourse. Many studies have used eye-tracking data to explore computational and cognitive models for contextual word predictions and word processing. Eye-tracking data has previously been widely explored with a view to investigating the factors that influence word prediction. However, these studies are problematic on several levels, including the stimuli, corpora, statistical tools they applied. Although various computational models have been proposed for simulating contextual word predictions, past studies usually preferred to use a single computational model. The disadvantage of this is that it often cannot give an adequate account of cognitive processing in language comprehension. To avoid these problems, this study draws upon a massive natural and coherent discourse as stimuli in collecting the data on reading time. This study trains two state-of-art computational models (surprisal and semantic (dis)similarity from word vectors by linear discriminative learning (LDL)), measuring knowledge of both the syntagmatic and paradigmatic structure of language. We develop a `dynamic approach' to compute semantic (dis)similarity. It is the first time that these two computational models have been merged. Models are evaluated using advanced statistical methods. Meanwhile, in order to test the efficiency of our approach, one recently developed cosine method of computing semantic (dis)similarity based on word vectors data adopted is used to compare with our `dynamic' approach. The two computational and fixed-effect statistical models can be used to cross-verify the findings, thus ensuring that the result is reliable. All results support that surprisal and semantic similarity are opposed in the prediction of the reading time of words although both can make good predictions. Additionally, our `dynamic' approach performs better than the popular cosine method. The findings of this study are therefore of significance with regard to acquiring a better understanding how humans process words in a real-world context and how they make predictions in language cognition and processing.


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