The Impact of Right to Carry Laws and the NRC Report: The Latest Lessons for the Empirical Evaluation of Law and Policy

2012 ◽  
Author(s):  
John J. Donohue ◽  
Abhay Aneja ◽  
Alexandria Zhang
Keyword(s):  
Empirical Evaluation ◽  
Law And Policy ◽  
Right To Carry Laws ◽  
The Impact

scholarly journals Impact of Dataset Size on Classification Performance: An Empirical Evaluation in the Medical Domain

2021 ◽  
Vol 11 (2) ◽  
pp. 796
Author(s):  
Alhanoof Althnian ◽  
Duaa AlSaeed ◽  
Heyam Al-Baity ◽  
Amani Samha ◽  
Alanoud Bin Dris ◽  
...  
Keyword(s):  
Empirical Evaluation ◽  
Classification Performance ◽  
Support Vector ◽  
Robust Model ◽  
Original Distribution ◽  
C4.5 Decision Tree ◽  
Dataset Size ◽  
Overall Performance ◽  
Medical Domain ◽  
The Impact

Dataset size is considered a major concern in the medical domain, where lack of data is a common occurrence. This study aims to investigate the impact of dataset size on the overall performance of supervised classification models. We examined the performance of six widely-used models in the medical field, including support vector machine (SVM), neural networks (NN), C4.5 decision tree (DT), random forest (RF), adaboost (AB), and naïve Bayes (NB) on eighteen small medical UCI datasets. We further implemented three dataset size reduction scenarios on two large datasets and analyze the performance of the models when trained on each resulting dataset with respect to accuracy, precision, recall, f-score, specificity, and area under the ROC curve (AUC). Our results indicated that the overall performance of classifiers depend on how much a dataset represents the original distribution rather than its size. Moreover, we found that the most robust model for limited medical data is AB and NB, followed by SVM, and then RF and NN, while the least robust model is DT. Furthermore, an interesting observation is that a robust machine learning model to limited dataset does not necessary imply that it provides the best performance compared to other models.

scholarly journals Economic and non-economic values and objectives in the EU’s international trade: Normative tensions, actors and processes

2019 ◽  
Author(s):  
Urszula Jaremba ◽  
Machiko Kanetake ◽  
Ingrid Koning
Keyword(s):  
Sustainable Development ◽  
Human Rights ◽  
New Technologies ◽  
Economic Values ◽  
Trade Relations ◽  
Trade Law ◽  
Law And Policy ◽  
Recent Developments ◽  
The One ◽  
The Impact

This Europe and the World: A law review special issue comprises selected papers presented at a RENFORCE workshop on the theme of tensions between the EU’s trade and non-economic values, held at Utrecht University in November 2017. The symposium addresses normative dilemmas underlying the EU’s trade law and policy. Normative dilemmas subsist between, on the one hand, the EU’s basic pursuit of its commercial interests and trade liberalization, and, on the other hand, the EU’s mandate to promote and safeguard a number of non-economic values, including human rights and sustainable development. The journal symposium aims to unveil normative tensions existing in the EU’s trade and investment policy, and understand some of the key actors and processes through which normative tensions are created and also mitigated. While the tensions between economic and non-economic values in the EU’s trade law and policy have been extensively discussed in literature, the present symposium highlights some of the recent developments in the EU’s trade relations, analyses not only human rights but also sustainable development, and examines the impact of new technologies.

scholarly journals A Multi-Objective Approach to Mitigate Negative Side Effects

2020 ◽  
Author(s):  
Sandhya Saisubramanian ◽  
Ece Kamar ◽  
Shlomo Zilberstein
Keyword(s):  
Side Effects ◽  
Empirical Evaluation ◽  
Primary Objective ◽  
Maximum Deviation ◽  
Negative Side ◽  
Multi Objective ◽  
Markov Decision ◽  
Secondary Objective ◽  
Negative Side Effects ◽  
The Impact

Agents operating in unstructured environments often create negative side effects (NSE) that may not be easy to identify at design time. We examine how various forms of human feedback or autonomous exploration can be used to learn a penalty function associated with NSE during system deployment. We formulate the problem of mitigating the impact of NSE as a multi-objective Markov decision process with lexicographic reward preferences and slack. The slack denotes the maximum deviation from an optimal policy with respect to the agent's primary objective allowed in order to mitigate NSE as a secondary objective. Empirical evaluation of our approach shows that the proposed framework can successfully mitigate NSE and that different feedback mechanisms introduce different biases, which influence the identification of NSE.

Empirical evaluation of structure-conduct-performance paradigm as applied to the Iranian Islamic banking system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdi Ghaemi Asl ◽  
Muhammad Mahdi Rashidi ◽  
Alireza Ghorbani
Keyword(s):  
Market Structure ◽  
Market Share ◽  
Balance Sheet ◽  
Empirical Evaluation ◽  
Banking System ◽  
Islamic Banking ◽  
Islamic Banks ◽  
Content Type ◽  
Simple Regression Model ◽  
The Impact

Purpose This paper aims to investigate the impact of market structure and market share on the performance of the Islamic banks operating in the Iranian banking system based on the structure-conduct-performance (SCP) paradigm. Design/methodology/approach The Iranian Islamic banking system’s market structure is evaluated by using the econometrics method to test the validity of the traditional SCP paradigm. For this purpose, the authors estimate a simple regression model that is consisted of several independent variables, such as the market share, bank size, real gross domestic product, liquidity and Herfindahl-Hirschman index as a proxy variable for concentration and one dependent variable, namely, the profit as a proxy for performance. The panel data includes a data sample of 22 Islamic banks operating from 2006 to 2019. Data are extracted from the balance sheet of Islamic banks and the time-series database of the Central Bank of Iran and World Bank. Findings The study’s findings indicate that both concentration and market share have a positive impact on the performance of banks in the Iranian Islamic banking system. This result is contradicted with both traditional SCP and efficient structure hypotheses; however, it confirms the existence of oligopoly or cartel in the Iranian Islamic banking system that few banks try to gain the highest share of profit and maintain their market share by colluding with each other. This result is in contradiction with other research studies about the market structure in the Iranian banking system that claimed that banks in Iran operate under monopolistic competition. In addition, it shows that the privatization of some banks in Iran does not improve and help competition in the Iranian banking system. Originality/value This paper is a pioneer empirical study analyzing the market structure, concentration and collusion based on the SCP paradigm in Iranian Islamic banking. The results of the study support the existence of collusive behavior among the Islamic bank in Iran that is not aligned with Sharia. This study clearly shows the difference between ideal Islamic banking and Islamic banking in practice in Islamic countries. This clearly indicates that only prohibiting some operations like receiving interest, gambling and bearing excessive risk is not enough. In fact, the Islamic banking system should be based on the Sharia rule in all aspects and much more modification and study have to be done to achieve an appropriate Islamic banking system. These possible modifications to overcome the issues of cartel-like market structure and collusive behavior in the Iranian Islamic banking system include making the Iranian banking system more transparent, letting foreign banks enter the Iranian banking system and minimizing the government intervention in the Iranian banking system.

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