Classification and causal mechanisms: a deflationary approach to the classification problem

Author(s):  
Derek Bolton
Author(s):  
Anita NEUBERG

In this paper I will take a look at how one can facilitate the change in consumption through social innovation, based on the subject of art and design in Norwegian general education. This paper will give a presentation of books, featured relevant articles and formal documents put into context to identify different causal mechanisms around our consumption. The discussion will be anchored around the resources and condition that must be provided to achieve and identify opportunities for action under the subject of Art and craft, a subject in Norwegian general education with designing at the core of the subject, ages 6–16. The question that this paper points toward is: "How can we, based on the subject of Art and craft in primary schools, facilitate the change in consumption through social innovation?”


Author(s):  
Sunitha .T ◽  
Shyamala .J ◽  
Annie Jesus Suganthi Rani.A

Data mining suggest an innovative way of prognostication stereotype of Patients health risks. Large amount of Electronic Health Records (EHRs) collected over the years have provided a rich base for risk analysis and prediction. An EHR contains digitally stored healthcare information about an individual, such as observations, laboratory tests, diagnostic reports, medications, procedures, patient identifying information and allergies. A special type of EHR is the Health Examination Records (HER) from annual general health check-ups. Identifying participants at risk based on their current and past HERs is important for early warning and preventive intervention. By “risk”, we mean unwanted outcomes such as mortality and morbidity. This approach is limited due to the classification problem and consequently it is not informative about the specific disease area in which a personal is at risk. Limited amount of data extracted from the health record is not feasible for providing the accurate risk prediction. The main motive of this project is for risk prediction to classify progressively developing situation with the majority of the data unlabeled.


Vestnik MEI ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. 132-139
Author(s):  
Ivan E. Kurilenko ◽  
◽  
Igor E. Nikonov ◽  

A method for solving the problem of classifying short-text messages in the form of sentences of customers uttered in talking via the telephone line of organizations is considered. To solve this problem, a classifier was developed, which is based on using a combination of two methods: a description of the subject area in the form of a hierarchy of entities and plausible reasoning based on the case-based reasoning approach, which is actively used in artificial intelligence systems. In solving various problems of artificial intelligence-based analysis of data, these methods have shown a high degree of efficiency, scalability, and independence from data structure. As part of using the case-based reasoning approach in the classifier, it is proposed to modify the TF-IDF (Term Frequency - Inverse Document Frequency) measure of assessing the text content taking into account known information about the distribution of documents by topics. The proposed modification makes it possible to improve the classification quality in comparison with classical measures, since it takes into account the information about the distribution of words not only in a separate document or topic, but in the entire database of cases. Experimental results are presented that confirm the effectiveness of the proposed metric and the developed classifier as applied to classification of customer sentences and providing them with the necessary information depending on the classification result. The developed text classification service prototype is used as part of the voice interaction module with the user in the objective of robotizing the telephone call routing system and making a shift from interaction between the user and system by means of buttons to their interaction through voice.


2020 ◽  
Author(s):  
Tom Joseph Barry ◽  
David John Hallford ◽  
Keisuke Takano

Decades of research has examined the difficulty that people with psychiatric diagnoses, such as Major Depressive Disorder, Schizophrenia Spectrum Disorders, and Posttraumatic Stress Disorder, have in recalling specific autobiographical memories from events that lasted less than a day. Instead, they seem to retrieve general events that have occurred many times or which occurred over longer periods of time, termed overgeneral memory. We present the first transdiagnostic meta-analysis of memory specificity/overgenerality, and the first meta-regression of proposed causal mechanisms. A keyword search of Embase, PsycARTICLES and PsycINFO databases yielded 74 studies that compared people with and without psychiatric diagnoses on the retrieval of specific (k = 85) or general memories (k = 56). Multi-level meta-analysis confirmed that people with psychiatric diagnoses typically recall fewer specific (g = -0.864, 95% CI[-1.030, -0.698]) and more general (g = .712, 95% CI[0.524, 0.900]) memories than diagnoses-free people. The size of these effects did not differ between diagnostic groups. There were no consistent moderators; effect sizes were not explained by methodological factors such as cue valence, or demographic variables such as participants’ age. There was also no support for the contribution of underlying processes that are thought to be involved in specific/general memory retrieval (e.g., rumination). Our findings confirm that deficits in autobiographical memory retrieval are a transdiagnostic factor associated with a broad range of psychiatric problems, but future research should explore novel causal mechanisms such as encoding deficits and the social processes involved in memory sharing and rehearsal.


Author(s):  
Paul D. Kenny

Case studies of Indonesia and Japan illustrate that party-system stability in patronage democracies is deeply affected by the relative autonomy of political brokers. Over the course of a decade, a series of decentralizing reforms in Indonesia weakened patronage-based parties hold on power, with the 2014 election ultimately being a contest between two rival populists: Joko Widodo and Subianto Prabowo. Although Japan was a patronage democracy throughout the twentieth century, the ruling Liberal Democratic Party (LDP) remained robust to outsider appeals even in the context of economic and corruption crises. However, reforms in the 1990s weakened the hold of central factional leaders over individual members of the LDP and their patronage machines. This was instrumental to populist Junichiro Koizumi’s winning of the presidency of the LDP and ultimately the prime ministership of Japan. This chapter also reexamines canonical cases of populism in Latin America.


Author(s):  
Michael Zürn

This chapter summarizes the argument of the book. It recapitulates the global governance as a political system founded on normative principles and reflexive authorities in order to identify the legitimation problems built into it; it points to the explanation of the rise of societal politicization and counter-institutionalization via causal mechanisms highlighting the endogenous dynamics of that global governance system; and, it sums up the conditions under which the subsequent processes of legitimation and delegitimation lead to the system’s decline or to a deepening of it. In addition, the conclusion submits that the arguments put forward in this book are in line with a newly emerging paradigm in International Relations. A “global politics paradigm” is increasingly complementing the “cooperation under anarchy paradigm” which has been dominant for around five decades. The chapter finishes with suggestions of areas for further research.


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