Logical Framework Research Articles

Analisis Kinerja Pembangunan Kabupaten Jeneponto Dengan Metode Logical Framework Analysis

This research aims to analyze the factors behind the low development performance in Jeneponto Regency. The analysis method used is the Logical Framework Analysis method. The results showed that the factors behind the low development performance in Jeneponto Regency, especially in the fields of education and health, are the low quality of education and the low level of public health. The low quality of education is characterized by the low average length of schooling of the community there which is caused by high dropout rates where the average cause of dropout rates is economic inability, socio-cultural factors some children choose to marry or be married off at school age, and the absence of motivation to go to school so that children choose to work. Meanwhile, the low level of public health is caused by the low life expectancy of the people of Jeneponto. The low life expectancy of the community is caused by the low achievement of optimal service standards (SPM) where the cause of the low achievement is due to inadequate facilities and infrastructure and health services that are not yet optimal.

Modal reduction principles: a parametric shift to graphs

Graph-based frames have been introduced as a logical framework which internalises an inherent boundary to knowability (referred to as ‘informational entropy’), due, e.g. to perceptual, evidential or linguistic limits. They also support the interpretation of lattice-based (modal) logics as hyper-constructive logics of evidential reasoning. Conceptually, the present paper proposes graph-based frames as a formal framework suitable for generalising Pawlak's rough set theory to a setting in which inherent limits to knowability exist and need to be considered. Technically, the present paper establishes systematic connections between the first-order correspondents of Sahlqvist modal reduction principles on Kripke frames, and on the more general relational environments of graph-based and polarity-based frames. This work is part of a research line aiming at: (a) comparing and inter-relating the various (first-order) conditions corresponding to a given (modal) axiom in different relational semantics; (b) recognising when first-order sentences in the frame-correspondence languages of different relational structures encode the same ‘modal content’; (c) meaningfully transferring relational properties across different semantic contexts. The present paper develops these results for the graph-based semantics, polarity-based semantics, and all Sahlqvist modal reduction principles. As an application, we study well known modal axioms in rough set theory (such as those corresponding to seriality, reflexivity, and transitivity) on graph-based frames and show that, although these axioms correspond to different first-order conditions on graph-based frames, their intuitive meaning is retained. This allows us to introduce the notion of hyperconstructivist approximation spaces as the subclass of graph-based frames defined by the first-order conditions corresponding to the same modal axioms defining classical generalised approximation spaces, and to transfer the properties and the intuitive understanding of different approximation spaces to the more general framework of graph-based frames. The approach presented in this paper provides a base for systematically comparing and connecting various formal frameworks in rough set theory, and for the transfer of insights across different frameworks.

How digital transformation enhances corporate innovation performance: The mediating roles of big data capabilities and organizational agility

Digital transformation has emerged as a key driver of high-quality enterprise development and an essential tool in forging an innovation-driven paradigm.Existing studies fail to delve into the specific mechanisms of their impact on firms' innovation performance, and views on their impact are divergent. Some studies suggest that digital transformation can enhance innovation performance, while others point out that it may have negative impacts, and cannot clearly answer how big data capabilities and organisational agility play a role in the digital transformation process. Therefore, based on dynamic capability theory and systems engineering theory, this study adopts the logical framework of "strategy-behaviour-performance" to systematically explore the process of digital transformation that enhances firms' innovation performance through the enhancement of big data capability and organisational agility. By empirically analysing the survey data of 476 manufacturing enterprises in China, the study reveals the chain-mediated effects of big data capability and organisational agility, and confirms the key roles of both in the transformation process. The findings suggest that digital transformation significantly improves firms' innovation performance, and that the dual mediating effects of big data capability and organisational agility are important links in its influencing mechanism. These findings not only provide empirical support for the theoretical model of digital transformation, but also provide practical guidance for enterprises to formulate strategies and optimise resource allocation in the digital era. We suggest that enterprises should strengthen the cultivation of big data capabilities and organisational agility while promoting digital transformation to better adapt to and lead market changes.

Fuzzy logic framework for financial distress prediction: Enhancing corporate decision-making under uncertainty

This research aims to develop an enhanced Fuzzy Logic Framework for Financial Distress Prediction to improve corporate decision-making under uncertainty. The primary objective is to address limitations in traditional fuzzy logic models, such as static rule bases and lack of adaptability to dynamic financial conditions. To achieve this, a time-dependent fuzzy logic system is proposed, incorporating real-time financial data and adaptive learning mechanisms to improve predictive accuracy over time. The research design involves creating a dynamic fuzzy rule base, assigning weights to rules based on predictive performance, and optimizing membership functions and rule weights using real-time data. The methodology applies the proposed framework to financial indicators such as liquidity, profitability, and leverage, with a numerical example demonstrating the system's effectiveness in predicting financial distress. The results show that the model can accurately predict financial distress levels, with a predicted distress value of 0.588 compared to an actual value of 0.6. The model’s ability to update rule weights and optimize predictions over time represents a significant improvement over static fuzzy logic models. This research fills a critical gap in financial distress prediction by introducing a dynamic, adaptive fuzzy logic framework that evolves with real-time data. The model offers significant implications for both academics and industry, providing a tool for more accurate risk assessment in volatile financial environments. However, further research is needed to refine the model’s computational efficiency and test its long-term predictive capabilities across different industries

Investigating Public Perception and Understanding of Biochar from Rice Stubble in Punjab & Implications for SDGs

The issue of burning of rice stubble in Punjab releases many harmful pollutants and particulate matter into the air, including carbon dioxide, carbon monoxide, nitrogen oxides, Sulphur dioxide, and volatile organic compounds. This leads to the deterioration of air quality, posing serious health risks to the population, especially those with respiratory conditions. Additionally, the smoke and pollutants from stubble burning can travel long distances, affecting not only Punjab but also neighbouring regions. The high levels of air pollution caused by rice stubble burning have been a major concern for public health and environmental sustainability in the region. This study focuses on the issue of rice stubble burning in Punjab, which has been identified as a major environmental and health hazard. The objective of the study is to assess the knowledge and awareness among the public in Punjab regarding biochar and its benefits. The study aims to establish a connection between the Sustainable Development Goals (SDGs) and the benefits that can be achieved by reducing rice stubble through alternative methods like biochar production. To gather data, a survey was conducted among individuals in Punjab. The survey included a structured questionnaire covering topics such as biochar production, the current situation of stubble burning, and awareness of the associated benefits. The collected data was analysed using a logical framework analysis approach. The results of the study indicate that biochar derived from rice stubble has the potential to significantly contribute to sustainable development in Punjab. It can help address the challenges faced by farmers in managing agricultural waste, improve soil health, and increase crop productivity, aligning with the goals of the SDGs. Government actions and support, such as providing incentives and subsidies, play a crucial role in promoting biochar production and use to mitigate the adverse effects of stubble burning.

A Framework for Developing and Assessing Custom Case Definitions: A Demonstration Applied to Opioid Overdose in Maryland.

Public health epidemiologists monitor data sources for disease outbreaks and other events of public health concern, but manual review of records to identify cases of interest is slow and labor-intensive and may not reflect evolving data practices. To automatically identify cases from electronic data sources, epidemiologists must use "case definitions" or formal logic that captures the criteria used to identify a record as a case of interest. To establish a methodology for development and evaluation of case definitions. A logical evaluation framework to approach case definitions will allow jurisdictions the flexibility to implement a case definition tailored to their goals and available data. Case definition development is explained as a process with multiple logical components combining free-text and categorical data fields. The process is illustrated with the development of a case definition to identify emergency medical services (EMS) call records related to opioid overdoses in Maryland. The Maryland Department of Health (MDH) installation of the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE), which began capturing EMS call records in ESSENCE in 2019 to improve statewide coverage of all-hazards health issues. We describe a case definition evaluation framework and demonstrate its application through development of an opioid overdose case definition to be used in MDH ESSENCE. We show the iterative process of development, from defining how a case can be identified conceptually to examining each component of the conceptual definition and then exploring how to capture that component using available data. We present a framework for developing and qualitatively assessing case definitions and demonstrate an application of the framework to identifying opioid overdose incidents from MDH EMS data. We discuss guidelines to support jurisdictions in applying this framework to their own data and public health challenges to improve local surveillance capability.

Congressional Redistricting and Strategic Copartisans: Partisan Gerrymandering in Pennsylvania, 1800–1824

The group-centered theory of party development provides a new theoretical framework for understanding early party development. Specifically, it provides a logical framework to understand why early state legislators were motivated to engage in partisan gerrymandering during a period without national organizations. I use Pennsylvania as a case study to determine if partisanship influenced the creation of congressional district maps in 1802, 1812, and 1822. Using county-level congressional election returns and state legislative journals, I provide evidence of strategic partisan gerrymandering by the Democratic-Republicans during each apportionment year. I also show that the Federalist minority in Pennsylvania knew the national political impact of the process and attempted to influence congressional maps for their own partisan advantage. Lastly, I demonstrate how multi-member districts were the Democratic-Republicans’ weapon of choice to engage in partisan gerrymandering throughout the period. These results highlight the connection between state legislatures and congressional party politics during the first party era.

State Crime

The International Criminal Tribunal for Rwanda’s historic judgment in the Akayesu Judgment established that rape and other forms of sexual violence can be an actus reus of genocide as defined by the United Nations Convention on Genocide Article II. The Akayesu Judgment therefore provides a logical framework to analyze a hidden episode of extreme post-colonial state violence in the newly independent Zimbabwe, namely a state policy of mass atrocities in Matabeleland and parts of the Midlands, targeting the minority Ndebele ethnic group during Operation Gukurahundi. The specific foci of this study are the patterns of mass rape and sexual violence in the military operation between 1983 and 1984 in Matabeleland. Drawing on 36 in-depth interviews with survivors from throughout Matabeleland, this study provides a critical new lens on Operation Gukurahundi through its identification of uniform systematic patterns of rape and other forms of sexual violence across Matabeleland. The article concludes that the patterns of rape and other forms of sexual violence identified in this study are indicative of a state policy of systematic genocidal rape between 1983 and 1984, deployed with the intent and effect to destroy, in part, a specific ethnic group, namely the minority Ndebele of Zimbabwe, thereby fulfilling every condition of the Genocide Convention principles of genocide.

Operation Gukurahundi: A Policy of Genocidal Rape and Sexual Violence in Zimbabwe, 1983–1984

The International Criminal Tribunal for Rwanda’s historic judgment in the Akayesu Judgment established that rape and other forms of sexual violence can be an actus reus of genocide as defined by the United Nations Convention on Genocide Article II. The Akayesu Judgment therefore provides a logical framework to analyze a hidden episode of extreme post-colonial state violence in the newly independent Zimbabwe, namely a state policy of mass atrocities in Matabeleland and parts of the Midlands, targeting the minority Ndebele ethnic group during Operation Gukurahundi. The specific foci of this study are the patterns of mass rape and sexual violence in the military operation between 1983 and 1984 in Matabeleland. Drawing on 36 in-depth interviews with survivors from throughout Matabeleland, this study provides a critical new lens on Operation Gukurahundi through its identification of uniform systematic patterns of rape and other forms of sexual violence across Matabeleland. The article concludes that the patterns of rape and other forms of sexual violence identified in this study are indicative of a state policy of systematic genocidal rape between 1983 and 1984, deployed with the intent and effect to destroy, in part, a specific ethnic group, namely the minority Ndebele of Zimbabwe, thereby fulfilling every condition of the Genocide Convention principles of genocide.

Review of Ethiopia’s Foreign Policy Responsiveness Capacity to Red Sea Militarization between 1991-2018

Abstract This article aims to assess responsiveness capacity of Ethiopian foreign policy on political and militarization dynamics in the Red Sea region from 1991 to 2018. Primarily, the evaluation employs the Effectiveness and Adequacy policy measurement criteria to assess the foreign policy's responsiveness. The review employed explanatory and argumentative approaches to examine different sources. The study also designed a logical framework of analysis by incorporating relevant IR theories like Hegemonic Stability Theory (HST) and Realism. The analysis then divided foreign policy objectives into General objectives and specific objectives which include Eritrea, Somalia, Egypt, and the Arabian Peninsula. Consequently, Adequacy and effectiveness policy evaluation criteria are used as to examine whether or not Ethiopian foreign policy assumptions are aligning with the Red Sea political dynamics and effectively achieve the stated objectives. The study shows shortcomings in responsiveness of both adequacy and effectiveness criteria. This is due to change in prior policy assumptions caused by rapid global and regional power dynamics. nevertheless, country specific findings are different. In country such as Eritrea and the Arabian Peninsula the policy is found to be is ineffective and inadequate; where as in Somalia it’s both effective and adequate. on the other hand, policy towards Egypt bound to have adequate assumptions but not effective. Therefore, revision and adoption of a holistic policy towards Red Sea region recommended.

Univalence and Ontic Structuralism

The persistent challenge of formulating ontic structuralism in a rigorous manner, which prioritizes structures over the entities they contain, calls for a transformation of traditional logical frameworks. I argue that Univalent Foundations (UF), which feature the axiom that all isomorphic structures are identical, offer such a foundation and are more attractive than other proposed structuralist frameworks. Furthermore, I delve into the significance in the case of the hole argument and, very briefly, the nature of symmetries.

“It’s an Old White Boys’ Club:” Faculty of Color’s Perceptions of Policy Engagement

Scholars of color remain underrepresented in policymaking contexts, and the absence of their expertise in policy processes can have significant consequences for society. In this study, we examine motivations for and perceived barriers to engagement in public policymaking among faculty of color. Using an institutional logics framework and interviews with 20 tenure-stream faculty of color at 20 research universities, we identify three main themes that elucidate their perceptions of public policy engagement: (1) the network-driven, racialized nature of public policymaking spaces; (2) communal motivations and perceived benefits of public policy engagement; and (3) the double-edged sword of engaging with public policymaking.

Social support as a coping resource for psychosocial conditions in postpartum period: a systematic review and logic framework

PurposeThis review seeks to examine the current state of postpartum social support and psychosocial conditions among women around the world, as well as explore the relationship between these factors. Additionally, it aims to propose a logical framework for enhancing postpartum social support and psychosocial conditions in this population.MethodsFollowing the development of a search strategy, two databases, PubMed and Science Direct, were searched for studies published between January 2019 and May 2023. The search was conducted throughout the entire month of May 2023. The risk of bias in the included cross-sectional studies was assessed using the Newcastle–Ottawa Quality Assessment Scale, which was adapted for this specific study design. To determine if the main objective of the cross-sectional studies was to investigate the relationship between social support and postpartum psychosocial conditions, a review was conducted based on the AMSTAR checklist, PRISMA checklist and PRISMA flow diagram. Data extraction was performed with the consensus of two authors, and a narrative synthesis approach was chosen for data synthesis, following the guidelines provided by the Centre for Reviews and Dissemination (CRD).ResultsEleven cross-sectional studies were included in the final analysis. Our findings revealed that all reviewed studies provided evidence of a positive association between social support and healthy psychosocial conditions in postpartum period. However, due to the absence of standardized measurement indicators to identify and compare the outcomes of various studies, there was a need to develop a conceptual framework that could enhance our understanding of the postpartum psychosocial condition including anxiety, depression, unfavorable quality of life and social support status up to 24 month after child birth. This framework aimed to incorporate childbirth and motherhood as "stressful events," while considering social support as a crucial "coping resource." Furthermore, it acknowledged empowerment, help-seeking behavior, and peer support as important "coping actions," alongside implementing client-centered interventions. Lastly, it recognized postpartum mental health and optimal quality of life as significant "effects" of these factors.ConclusionsThe proposed conceptual framework could define postpartum women’s health as “the ability to adapt and self-manage.”

A First Approach to Quantum Logical Shape Classification Framework

Quantum logic is a well-structured theory, which has recently received some attention because of its fundamental relation to quantum computing. However, the complex foundation of quantum logic borrowing concepts from different branches of mathematics as well as its peculiar settings have made it a non-trivial task to devise suitable applications. This article aims to propose for the first time an approach using quantum logic in image processing for shape classification. We show how to make use of the principal component analysis to realize quantum logical propositions. In this way, we are able to assign a concrete meaning to the rather abstract quantum logical concepts, and we are able to compute a probability measure from the principal components. For shape classification, we consider encrypting given point clouds of different objects by making use of specific distance histograms. This enables us to initiate the principal component analysis. Through experiments, we explore the possibility of distinguishing between different geometrical objects and discuss the results in terms of quantum logical interpretation.

A visual defrosting control method for air source heat pump system based on machine vision

Frosting on the coil of the air source heat pump (ASHP) significantly affects its performance. An accurate defrosting control method is essential for the ASHP unit. Here, a novel visual defrosting control method based on machine vision is proposed. The frosting degree of the unit is accurately obtained by frosting image analysis with digital image processing to achieve on-demand defrosting. Fractal dimension, frosting degree coefficient, and single-circuit frosting evenness value are introduced to evaluate the frosting degree of coil images. The image acquisition point is determined with confusion matrix. Based on this, the logical framework of the proposed method is constructed, in which the defrosting starting and termination conditions are set as the moment when the frosting degree coefficient is equal to 0.9 and 0, respectively. A multi-variable model of fractal dimension is fitted, which improves the generalization of the proposed method. Finally, comparative experiments are conducted between the proposed method and the traditional temperature-time (T-T) method in typical cases. The results indicate that the COP and total heating capacity increase by 11.8 %, 10.6 % and 7.4 %, 6.6 %, respectively, and the defrosting frequency is reduced by 75 %, which demonstrates dominant advantages of the proposed method in accuracy, energy-saving, and indoor thermal comfort management.

Understanding the complexities of omnichannel retailing through a service-dominant logic framework: exploring the role of digitalization in the retail ecosystem

ABSTRACT Retailing’s digital transformation continues to exert pressure on marketers to effectively design and manage consumers’ shopping experiences. A multi-method research approach was adopted to thoroughly examine the current state of consumer experiences in an omnichannel retailing context. Specifically, a bibliometric analysis of 561 omnichannel retailing articles in the Web of Science database was conducted, revealing a lack of research focused on the service-dominant logic perspective. Therefore, the proposed conceptual framework utilized a service-dominant logic perspective, emphasizing the interconnected roles of various actors in shaping consumers’ experiences and their assessments of value-in-use within complex omnichannel retailing. To the best of the authors’ knowledge, this research is the first comprehensive framework for understanding consumer value-in-use in omnichannel retailing, linking antecedents, consumers’ value-in-use experiences, and consequences for consumers and retailers. In summary, this paper conceptualizes how consumers perceive value co-creation within an omnichannel retail ecosystem, contributing to the development of omnichannel strategies that optimize consumers’ value-in-use across the retail landscape.

US-China global competition and dilemma for Vietnam's strategic choices in the South China Sea conflict

The South China Sea (SCS) conflict has become a critical factor for regional peace and development with growing geopolitical competition between China and the USA. To face the rising threat of China, the study argues that the balance of power theory is relevant to explain why Vietnam attempts to strengthen strategic alliances with the USA, Russia, EU, and India to balance against the rising threat of China in SCS. However, this theory is not able to explain why Vietnam has a bandwagoning policy toward China at the same time. To fill the gap of the previous studies, this study endeavors to put forward the point that as geopolitical rivalry between the two superpowers, the United States and China, intensifies, Vietnam is put in a predicament of balancing the economic and the political choices against the choices of taking a neutral stand against the assertiveness of China in the SCS. Further, the alternative traditional balance options with ASEAN, and Russia are not sufficiently effective for Vietnam to balance against China since the position of both ASEAN and Russia is much weaker than China. This study also suggests that the support of the USA, EU, and its alliance for Vietnam’s position creates unbearable costs for China’s aggressive behaviors in SCS. By using the mathematical and logical framework, the study suggests that Vietnam tends to adopt a mixed strategy (balancing, bandwagoning, neutrality) in dealing with China’s threats.

Citizens’ conscious engagement in digital platforms: advancing public service delivery within the public service logic framework

ABSTRACT Public service logic (PSL) acknowledges the pivotal role of citizen participation in value creation, yet the effect of citizens’ conscious engagement on public service delivery and co-creation of value with public service organizations (PSOs) remains underexplored. This study addresses this issue through empirical research on the interactional text data between users and PSOs on an online responsive service platform in Beijing, China. The study contributes by unveiling evidence of users’ conscious engagement and input and examines its influence on PSOs’ responsiveness and service outcomes. Furthermore, it extends the research on value co-creation within digital platforms.

Simplification errors in predictive models

AbstractOrganizational and political responses to strategic surprises such as the credit crunch in 2008 and the pandemic in 2020 are increasingly reliant on scientific insights. As a result, the accuracy of scientific models has become more critical, and models have become more complex to capture the real‐world phenomena as best as they can. So much, so that appeals for simplification are beginning to surface. But unfortunately, simplification has its issues. Too simple models are so generic that they no longer accurately describe or predict real‐world cause‐effect relationships. On the other hand, too complex models are hard to generalize. Somewhere on the continuum between too simple and too complex lies the optimal model. In this article, the authors contribute to the ongoing discussion on model complexity by presenting a logical and systematic framework of simplification issues that may occur during the conceptualization and operationalization of variables, relationships, and model contexts. The framework was developed with the help of two cases, one from foresight, a relatively young discipline, and the other from the established discipline of innovation diffusion. Both disciplines have a widely accepted foundational predictive model that could use another look. The shared errors informed the simplification framework. The framework can help social scientists to detect possible oversimplification issues in literature reviews and inform their choices for either in‐ or decreases in model complexity.

Responding to economic abuse: An institutional logics analysis of feminist activism

AbstractEconomic abuse (EA)—intimate partners' efforts to control women's economic resources—still suffers from ambiguous legal recognition. Even in countries with legal recognition, state allocation of resources for support remains meager. We suggest that Israeli state welfare organizations (SWOs) employees have developed their professional response to EA along two distinct value sets—a dominant institutional logic in their respective organizations and a more covert feminist institutional logic encountered in collaborations with feminist Non Governmental Organizations. Using a framework of multiple institutional logics, in interviews with 48 SWO employees, we map the multiple institutional logics that cultivate responses to EA survivors and show that elements of feminist understanding and practices on EA permeate SWOs' practices. The existence of a feminist institutional logic creates a path for exploring whether the feminist impact is significant in enabling committed responses to EA even while no institutional change is achieved.