Accountability Bargains in Pakistan

Poor and marginalised citizens rarely engage directly with the state to solve their governance issues in fragile, conflict and violence-affected settings, as these settings are characterised by the confrontational nature of state–citizen relations. Instead, citizens engage with, and make claims to, intermediaries some of them public authorities in their own right. What are these intermediaries’ roles, and which strategies and practices do they use to broker state–citizen engagement? We argue that in Pakistan intermediaries make themselves essential by: (1) being able to speak the language of public authorities; (2) constantly creating and sustaining networks outside their communities; and (3) building collectivising power by maintaining reciprocity relations with their communities. In doing so, households and intermediaries engage in what we are calling ‘accountability bargains’: strategies and practices intermediaries and poor and marginalised households employ in order to gain a greater degree of security and autonomy within the bounds of class, religious, and ethnic oppression.Foreign, Commonwealth & Development Offic

Design and Implementation of Real-Time Kitchen Monitoring and Automation System Based on Internet of Things

Automation can now be found in nearly every industry. However, home automation has yet to reach Pakistan. This paper presents an Internet of Things smart kitchen project that includes automation and monitoring. In this project, a system was developed that automatically detects the kitchen temperature. It also monitors the humidity level in the kitchen. This system includes built-in gas detection sensors that detect any gas leaks in the kitchen and notify the user if the gas pressure in the kitchen exceeds a certain level. This system also allows the user to remotely control appliances such as freezers, ovens, and air conditioners using a mobile phone. The user can control gas levels using their phone with this system. In this paper, the ESP32, DHT11 Sensor, 5 V Relay X 8, and MQ-135 gas sensors create a smart kitchen by controlling the temperature, managing humidity, and detecting gas leakage. The system was built on an Arduino board that is connected to the Internet. The hardware was integrated and programmed using an Arduino, and a user Android application was developed. The project’s goal is to allow any Android smartphone to remotely control devices. This method is commonly used in homes, businesses, and grocery stores. Users will be able to control all of their instruments from anywhere, including switches, fans, and lights. Furthermore, simulation was performed using Matlab2016b on multiple houses. In the simulation, not only was the kitchen considered, but also two, four, and six houses. Each house has two bedrooms, one living room, one guest room, two bathrooms, and one kitchen. The results revealed that using this system will have a scientifically significant impact on electricity consumption and cost. In the case of the houses, the cost was USD 33.32, 32.64, 22.32, and 19.54 for unscheduled, two, four, and six houses, respectively. Thus, it was observed that the cost and power are directly proportional to each other. The results reveal that the proposed solution efficiently reduces the cost as compared to that of unscheduled houses.publishedVersio

Understanding Governance from the Margins: What Does It Mean In Practice?

What does governance look like ‘from below’ – from the perspectives of poor and marginalised households? How do patterns of conflict affect that? These were the questions at the heart of the Governance at the Margins research project. Over three years from 2017-2020 we worked to explore this through in-depth study in conflict-affected areas of Mozambique, Myanmar, and Pakistan. Our research teams interviewed the same people regularly over that time, finding out how they resolved problems and interacted with authorities. In this paper we connect what we found to the realities and complexities of development practice, drawing on the input of 20 experienced practitioners working in bilateral and multilateral development agencies and international NGOs, who generously gave their time to help us think through the practical implications of our wealth of findings

Estimation and Interpretation of Machine Learning Models with Customized Surrogate Model

Machine learning has the potential to predict unseen data and thus improve the productivity and processes of daily life activities. Notwithstanding its adaptiveness, several sensitive applications based on such technology cannot compromise our trust in them; thus, highly accurate machine learning models require reason. Such models are black boxes for end-users. Therefore, the concept of interpretability plays the role if assisting users in a couple of ways. Interpretable models are models that possess the quality of explaining predictions. Different strategies have been proposed for the aforementioned concept but some of these require an excessive amount of effort, lack generalization, are not agnostic and are computationally expensive. Thus, in this work, we propose a strategy that can tackle the aforementioned issues. A surrogate model assisted us in building interpretable models. Moreover, it helped us achieve results with accuracy close to that of the black box model but with less processing time. Thus, the proposed technique is computationally cheaper than traditional methods. The significance of such a novel technique is that data science developers will not have to perform strenuous hands-on activities to undertake feature engineering tasks and end-users will have the graphical-based explanation of complex models in a comprehensive way—consequently building trust in a machine

Estimation and Interpretation of Machine Learning Models with Customized Surrogate Model

Machine learning has the potential to predict unseen data and thus improve the productivity and processes of daily life activities. Notwithstanding its adaptiveness, several sensitive applications based on such technology cannot compromise our trust in them; thus, highly accurate machine learning models require reason. Such models are black boxes for end-users. Therefore, the concept of interpretability plays the role if assisting users in a couple of ways. Interpretable models are models that possess the quality of explaining predictions. Different strategies have been proposed for the aforementioned concept but some of these require an excessive amount of effort, lack generalization, are not agnostic and are computationally expensive. Thus, in this work, we propose a strategy that can tackle the aforementioned issues. A surrogate model assisted us in building interpretable models. Moreover, it helped us achieve results with accuracy close to that of the black box model but with less processing time. Thus, the proposed technique is computationally cheaper than traditional methods. The significance of such a novel technique is that data science developers will not have to perform strenuous hands-on activities to undertake feature engineering tasks and end-users will have the graphical-based explanation of complex models in a comprehensive way—consequently building trust in a machine

Everyday Governance in Areas of Contested Power: Insights from Mozambique, Myanmar and Pakistan

How do poor and marginalized people solve problems and claim rights and entitlements in places affected by conflict and where state authority is contested? Understanding such processes is important as the numbers of poor people living in difficult settings grows, yet existing research on governance in conflict largely misses a “citizen’s eye” view of these processes. The article focuses on “everyday governance” from a citizen’s perspective. What do engagements with the multiple state and non-state actors that prevail in such settings look like? We present insights from longitudinal research in conflict-affected areas in Mozambique, Myanmar and Pakistan. Research was undertaken in two phases over the period 2017–2021. Researchers developed an innovative method, “governance diaries,” in which we interviewed the same set of poor and marginalized households over a period of a year, capturing an unfolding citizen’s eye view of governance. We subsequently used the same method to include key intermediaries to whom households went with problems. We find that in most instances poor and marginalized households did not rely on the state or other formal or external authorities to resolve problems. Mostly, they simply “lived with” those problems, or resolved them through “self-provision” — mutual aid, and community action. When they did go to authorities, they used “governance intermediaries”—actors that connect people with authorities or mediate between households. These intermediaries played a central role in local governance, using their networks and deploying a range of strategies with a focus on local resolution of problems. These findings challenge some core assumptions of contemporary development practice. First, development programmes tend to focus on improving state-run services, rather than engaging with the diversity of how public goods are governed on the ground. Second, policies assume that people can go directly to authorities with their problems, and do not take into account the role that intermediaries play. Finally, the highly diverse networks of governance actors that matter to specific places challenges the common focus on formal systems rather than informal practices