Journal of Public Policy Practitioners

Addressing Fisheries Policies in Pakistan by Using Deep Learning

Hinna Hafeez — 2024-11-04

Pakistan has been facing an acute decline in the aquamarine population, especially fisheries, over the last few years. Therefore, the current study attempted to facilitate policymakers in identifying and addressing fish shortage using Artificial Intelligence (AI), particularly deep learning (DL). Policymakers can achieve this objective with the help of biologists and experts working in the field of AI. Presently, manual identification methods are still utilized in fish breeding, however, aquaculture is the only sector where the use of DL is increasing rapidly. For this, marine biologists and ichthyologists must have a precise taxonomy of fish species, if they intend to understand fish behavior deeply. Most current algorithms are designed to recognize fish in dry environments due to various challenges, such as background noise, picture distortion, the existence of other water bodies in images, low image quality, and occlusion. Due to the rapid growth of DL, the use of computer vision in agriculture and farming to generate agricultural intelligence has become a current hotspot in the field of research. Automatic classification of fish is severely limited by the inability to reliably distinguish between different fish species and taxonomic groups. Once the data is split into a "train" and "test" set, the former's features may be retrieved. Layer-specific feature extraction was performed for the current study. Subsequently, the model was trained using AlexNet and several machine-learning classification methods were compared to improve the classification accuracy. To demonstrate the use of DL in order to address the extinction of fisheries in Pakistan, a dataset of different types of fish was used, taken from Kaggle which measured 541MB. After choosing the dataset, AlexNet was used for the classification and to split the data into test (70%) and train data (30%). Afterwards, the features of train data were extracted on layers and AlexNet was used to train the model. Later, different machine learning classification algorithms were used to find the best classification accuracy, which may help to identify the fish breeds that are facing the threat of extinction. Moreover, policymakers may use the results to formulate policies in order to address the problem.

Analysis of the Education Policies of Pakistan: Identifying Factors Behind its Shortcomings and Failure to Achieve Goals

Zerish Tasleem — 2024-06-27

Education is critical for personal and national development, influencing economic growth, social progress, and cultural preservation. Since gaining independence in 1947, Pakistan has worked to establish an effective education system, yet literacy rates remain low. Early efforts, such as the 1947 National Education Conference, were hampered by the challenges of post-partition circumstances. Currently, Pakistan's education system confronts a number of issues, including limited finance, poor educational quality, socio-cultural hurdles, and major urban-rural inequities. Understanding these concerns is vital for understanding the continued struggles to meet educational needs. Data for this study was collected from secondary sources. It concluded that significant obstacles to educational policy include socio-cultural barriers, poor quality of education, inadequate funding, and inconsistent policy implementation. The findings underscore the need for evidence-based strategies and comprehensive reforms to address these issues effectively. This research contributes to the broader discourse on educational policy by highlighting actionable recommendations and proposing a framework for successful policy development and implementation, ultimately aiming to enhance the quality and equity of education in Pakistan.

Improving Leadership Decision-Making (LDM) through Knowledge Management (KM) in Public Sector (PS) of Pakistan

Muhammad Abdus Salam — 2024-06-27

The current study aimed to identify the existing leadership decision-making (LDM) in the public sector (PS) of Pakistan along with its role, barriers, constraints, and issues. Thereafter, the study attempted to examine the application of knowledge management (KM) principles and techniques for the augmentation of LDM to enhance the overall efficacy of PS. The study was qualitative in nature and comprised rigorous literature review and examination of archival records of PS in Pakistan. Additionally, it also analyzed the personal insights and reflections from the PS of Pakistan. The findings revealed that the field is in embryonic stage and requires extensive research in qualitative as well as quantitative domain. There is even a lack of basic awareness pertaining to KM and its subfields encompassing tacit knowledge, explicit knowledge, and phronesis. However, the growth of private sector and the role of key decisions taken by the leadership in shaping their sustainable success is a prime lesson to be learnt by the PS in terms of adoption of KM for better decision-making (DM). Moreover, the study also focused on the development of a model by modifying an existing DM organizational model presented in 2017. However, generalizability could be an issue, since this study was conducted based on the personal reflections of the researcher. Additionally, empirical validation, quantitative, longitudinal, cross-sectional, and case study researches may b conducted to evaluate the implications of the study. PS is considered as a non-profit organizational setup. There is a wide gap between public and private sector due to the difference in the role played by both. However, a number of practices can be adopted interchangeably to improve and enhance the existing capabilities which in case of PS include governance, compliance, and citizen satisfaction. The current study provided theoretical insights into how KM models, themes, and practices can be applied for the improvement of DM in the PS. The model presented was novel and an addition to the existing body of knowledge.

Strategic Communication in Pakistan: Synergizing a Policy Framework for National Security

Zainab Ahmed — 2024-06-28

Cyclic communications, engagements, feedbacks, and rectifications ensure the accomplishment of a policy. Power projection in International Relations (IR) has transformed to include soft and smart dimensions which eventually bring evolution in public relations and public diplomacy. Strategic communication is the tool of soft power engaging targeted audience in circular communication along with incorporating implementation. Pakistan’s National Security Policy (NSP) (2022-2026) is the first in its history at a critical juncture of global, regional, and national political landscape. Therefore, many geopolitical and geo-economic fault lines cross through what lies at Pakistan’s core national interests. A comprehensive strategic communication framework introduced in the current study aimed to overhaul the crises of narrative building, adequate communication, and continuous engagement.

Financial Devolution and Local Government: Citizen's Perception in Azad Jammu and Kashmir

Zopash Khan — 2024-11-04

This study aims to analyse the perception of citizens regarding accountability, competency, effectiveness, and challenges related to local government system. Respondent’s income, gender, age, familiarity with roles and responsibilities of local government members, and engagement in political discussions are important factors affecting their perception. Data has been collected through stratified random sampling. Citizens revealed that accountability and effectiveness of government will improve after financial devolution. Moreover, voters mostly preferred to cast their votes on the basis of personal affiliation. Education remains top expectation of citizens from the Local Government (LG). This study also provides policy tools for the local government policy makers.

Role of Collaborative Governance towards Crisis Management: A Case Study of Provincial Disaster Management Authority (PDMA)

Zahra Shahid — 2024-11-04

The current study examines how the Provincial Disaster Management Authority (PDMA) used collaborative governance to manage crises. It also aims to identify the elements of cooperative governance, fundamental tactics, and challenges encountered during crisis management. For data collection, semi-structured interviews were used. Twelve interviews with the PDMA top management were conducted and data was transcribed through thematic analysis. It has been determined that collaborative governance and fundamental and complementary conditions impact crisis management, particularly when building collaborative processes. It has also been discovered that the key prerequisites for developing the collaborative process are leadership activities and face-to-face negotiation. Contrarily, supportive settings entail an initial understanding, trust, and commitment that enhance the collaborative process without endangering crisis management. However, the research findings connect well with existing theories especially in governance frameworks on the importance of interactive dynamics. These perceptions can enlighten future study and pursue the practices in crisis management, mostly in how collaborative governance can influence to improve awareness and resilience in disaster management struggle.