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The paper aims to relocate discussions on police stops and police interactions from the Anglophone world to the particularistic context of the post-colonial state of India. The paper further frames the everyday policing practices in a theoretical dialog between questions of legitimacy, accountability and tolerated illegalities. For that purpose, the author contextualizes the discussion in the post-colonial state of India, in the jurisdictions of two police stations (PSs), in the National Capital Territory of Delhi and the State of Kerala.

The author conducted ethnographic studies in one station each in Kerala and Delhi, India, from February to July 2019 and July 2019 to January 2020, respectively. The study mapped everyday power relations as the relations manifested within the site and jurisdiction of the PSs.

Through the research, the author found that to fully understand everyday practices of policing, especially police interactions and police stops, one must contextualize the police force within the administrative power-sharing relations, police force's accountability structures, legal procedures and class dynamics, which mark the terrain in which personnel function. In that terrain, the author found that the dialog between particularistic legitimacy, accountability and tolerated illegalities offered an important framework to interpret the everyday policing practices.

Through the paper, the author seeks to expand the analysis of ethnographic descriptions of policing by contextualizing them in the political economy of the state. In doing so, the author aims to provide a framework through which police interactions in post-colonial India could be understood

Progress accomplished by the disabled entrepreneurs on the fronts of profits, turnover, return on investment (ROI), employees engaged, capital employed and diversification shall be studied and prevalence of gender differences in such progress shall be assessed.

The proposed research is descriptive in nature, based on primary data, collected by personally administering a well-structured interview schedule to 201 disabled entrepreneurs in Puducherry selected using a snowball sampling technique. Data collected has been analyzed using SPSS 21, using the tools of mean, one-way ANOVA, factorial ANOVA and chi-square (χ²) analysis.

The prevalence rate of entrepreneurship among female disabled is very low. Female disabled entrepreneurs manage higher turnover than their male counterparts and manage insignificantly higher progress in terms of capital employed, while male disabled entrepreneurs have managed insignificantly higher progress in terms of profits, diversification and ROI. Illiterate disabled, both men and women, struggle to manage decent turnover while the better educated manage better turnover.

This paper has highlighted the low prevalence rate of entrepreneurship among women disabled though the fewer women disabled entrepreneurs are performing better than their male counterparts in operating their business.

The findings of this paper may be taken as base for formulation of effective government policies in empowering disabled persons in general and women disabled in particular.

This work presents a novel approach by considering teaching learning based optimization (TLBO) and radial basis function neural networks (RBFNs) for building a classifier for the databases with missing values and irrelevant features. The least square estimator and relief algorithm have been used for imputing the database and evaluating the relevance of features, respectively. The preprocessed dataset is used for developing a classifier based on TLBO trained RBFNs for generating a concise and meaningful description for each class that can be used to classify subsequent instances with no known class label. The method is evaluated extensively through a few bench-mark datasets obtained from UCI repository. The experimental results confirm that our approach can be a promising tool towards constructing a classifier from the databases with missing values and irrelevant attributes.

The purpose of this study is to determine the impact of community-based and driven approaches during the lockdowns and early periods of the pandemic. The study examines the impact and perceptions of the state-led intervention. This would help to discover a better approach for postpandemic interventions and policy responses.

This article used the inductive method and gathered its data from surveys. In search of global opinions on COVID-19 responses received in communities, two countries in each continent with high COVID-19 infection per 100,000 during the peak period were chosen for study. In total, 13 community workers, leaders and members per continent were sampled. The simple percentile method was chosen for analysis. The simple interpretation was used to discuss the results.

The study showed that poor publicity of community-based interventions affected awareness and fame as most were mistaken for government interventions. The study found that most respondents preferred state interventions but preferred many communities or local assessments of projects and interventions while the projects were ongoing to adjust the project and intervention as they progressed. However, many preferred community-based and driven interventions.

State secrecy and perceived opposition oppression limited data sourcing for this study in countries where state interventions are performed in secret and oppression of perceived opposition voices limited data collection in some countries. Thus, last-minute changes were made to gather data from countries on the same continent. An intercontinental study requires data from more countries, which would require more time and resources. This study was affected by access to locals in remote areas where raw data would have benefited the study.

The absence of data from the two most populous countries due to government censorship limits access to over a third of the global population, as they make up 2.8 out of 7 billion.

The choice of two countries in each continent is representational enough, yet the absence of data from the two most populous countries creates a social identity gap.

The survey collected unique and genuine data and presents novel results. Thus, this study provides an important contribution to the literature on the subject. There is a need for maximum support for community-based interventions and projects as well as global data collection on community-based or driven interventions and projects.

The economic development of Bangladesh is heavily reliant on the banking industry, yet it faces numerous hurdles, including liquidity issues, capital shortages, non-performing loans, inefficiencies and so on. Therefore, this study investigated the performance and efficiency of scheduled banks (state-owned, private commercial, foreign commercial and specialized banks) operating in Bangladesh.

The research was conducted using secondary data from annual reports of banks. The CAMELS rating system and Data Envelopment Analysis (DEA) methods were employed to measure the performance and efficiency of banks, respectively.

In the overall bank rankings, results revealed that foreign commercial Standard Chartered Bank and state-owned Sonali Bank Limited came in first and last position, respectively. Among the four categories of banks, foreign commercial banks were the best performer, while state-owned banks were the worst. Only two banks, i.e. Citibank NA and HSBC Bank, were scale efficient while the remaining banks were inefficient. In terms of performance and efficiency, state-owned and specialized banks were deemed wanting.

This study proposes recommendations to the policymakers that could lead to more effective tactics for improving the banking industry's performance and efficiency.

As far as the authors are concerned, this study presents empirical evidence on the performance and efficiency of different types of banks and explores comparisons among them, which has never been done to this extent in the country before.