Hierarchy Of Knowledge Research Articles

Centring Race: Unpacking Informality Through the Lens of Black Tax

AbstractTaking a historical and contextual approach to racialization, this study seeks to unpack informality in the development of welfare regimes. By centring race as a conceptual lens, it elicits knowledge hierarchies that exist within the formulation of social policies; particularly concerning the classification of informal/formal practices. It thereby draws on Black Tax as a lived example of family and kinship support in Southern Africa, in the development discourse predominantly understood as informal social protection or informal safety nets. Black Tax, however, is a colloquial term that claims its non-Western origin and struggle to co-exist in a Westernized unequal society. It does so by stressing its racialized nature as a necessary practice in response to racial inequality but also as a form of alienation from its origin, being the African philosophy of Ubuntu. In showing consequences and internal conflicts that arise when living across dominant (Western) and subaltern (African) divides, it challenges colonial dichotomies that continue to dominate the development discourse. In highlighting what the informal/formal dichotomy overlooks, the study seeks to encourage a process of repositioning and expanding informality to better account for its political role in ‘thinking’ and ‘doing’ development.

9.P. Scientific session: National perspective on knowledge translation to bridge the gap between research and policy

Abstract National and international public health institutions play a crucial role in guiding public health policies. However, a key challenge in this process is to bridge the gap between the data collected and the insights required to guide decision-makers, commonly referred to as knowledge translation (KT). Various models have been proposed to facilitate the KT process in public health, and one of the widely recognized models is the Data-Information-Knowledge-Wisdom (DIKW) model, also known as the knowledge pyramid or information hierarchy. In this workshop, we provide insight into the Belgian perspective on the implementation of the DIKW pyramid, using the Belgian health status website as an example https://www.healthybelgium.be. The workshop will tackle the four distinct layers of KT, including data, information, knowledge, and wisdom. The first one involves the data collection process, and the importance of considering potential biases that may arise during this process. Information revolves around the data analysis and the translation of data into meaningful information. Knowledge builds on data-driven information by contextualizing public health analysis results. Finally, wisdom reflects the end-result of the DIKW model, highlighting the need to utilize knowledge for action and achieving results based on the analysis performed. The DIKW model provides a valuable platform by delineating the different layers required to move from raw data to knowledge and wisdom. This process is crucial in achieving an impact on public health, where the data analyzed by public health researchers informs the end-users, including policymakers and the public. Nonetheless, the DIKW model and its applicability to knowledge translation are the subjects of many debates. Within this workshop, the national perspective of the national public health institute in Belgium, Sciensano, on each level of the DIKW pyramid will offer participants concrete examples that might spark an initial step towards their nationwide implementation of the DIKW pyramid for KT. The workshop will offer a step-by-step presentation on the different KT layers, whereby the attendees will gain unique insights into the system implemented in Belgium. This presentation will foster a discussion for generating ideas and stimulating other countries to implement the DIKW pyramid. Key messages • The DIKW pyramid offers a valuable framework to guide knowledge translation in public health, which is a key task for public health institutes. • Attendees will receive an overview and a practical example of how the DIKW-model could be applied in a national context, including a discussion of the strengths and weaknesses of the pyramid.

Holy grail or convenient excuse? Stakeholder perspectives on the role of health system strengthening evaluation in global health resource allocation

BackgroundThe role of evaluation evidence in guiding health systems strengthening (HSS) investments at the global-level remains contested. A lack of rigorous impact evaluations is viewed by some as an obstacle to scaling resources. However, others suggest that power dynamics and knowledge hierarchies continue to shape perceptions of rigor and acceptability in HSS evaluations. This debate has had major implications on HSS resource allocation in global-level funding decisions. Yet, few studies have examined the relationship between HSS evaluation evidence and prioritization of HSS. In this paper, we explore the perspectives of key global health stakeholders, specifically around the nature of evidence sought regarding HSS and its potential impact on prioritization, the challenges in securing such evidence, and the drivers of intra- and inter-organizational divergences. We conducted a stakeholder analysis, drawing on 25 interviews with senior representatives of major global health organizations, and utilized inductive approaches to data analysis to develop themes.ResultsOur analysis suggests an intractable challenge at the heart of the relationship between HSS evaluations and prioritization. A lack of evidence was used as a reason for limited investments by some respondents, citing their belief that HSS was an unproven and potentially risky investment which is driven by the philosophy of HSS advocates rather than evidence. The same respondents also noted that the ‘holy grail’ of evaluation evidence that they sought would be rigorous studies that assess the impact of investments on health outcomes and financial accountability, and believed that methodological innovations to deliver this have not occurred. Conversely, others held HSS as a cross-cutting principle across global health investment decisions, and felt that the type of evidence sought by some funders is unachievable and not necessary – an ‘elusive quest’ – given methodological challenges in establishing causality and attribution. In their view, evidence would not change perspectives in favor of HSS investments, and evidence gaps were used as a ‘convenient excuse’. Respondents raised additional concerns regarding the design, dissemination and translation of HSS evaluation evidence.ConclusionsOngoing debates about the need for stronger evidence on HSS are often conducted at cross-purposes. Acknowledging and navigating these differing perspectives on HSS evaluation may help break the gridlock and find a more productive way forward.

Epistemic silences, subversive politics: post-disaster economic assessments as technologies of persistent coloniality and route to an emancipatory climate justice agenda in the Caribbean

ABSTRACT Economic analyses of losses and damages or post-disaster needs assessments (PDNAs) are silent about the longstanding reparatory claims related to the legacies of African enslavement, colonial violence and indigenous dispossession that compound uneven racialized geographies in the Caribbean. This paper unpacks these so-called ‘objective’ valuations drawing attention to their (neo)liberal framings, technocratic underpinnings, and historical origins in the Caribbean plantation economy. Using case studies of catastrophic hurricanes Matthew (2016), Irma (2017) and Dorian (2019) in Haiti, Antigua and Barbuda, and The Bahamas respectively, the paper exposes critical tensions, knowledge hierarchies, and contradictions embedded within empirical assessments that justify and prioritize preferred policies of powerful international development, financial and governance institutions. PDNAs under-value and neglect important community and local knowledge, solidarity practices, cultural institutions, and relational ethics in the face of climate disasters in these Caribbean islands. Taking a Black geographies and political economy approach, the paper addresses the limitations and risks associated with PDNAs, deemed political tools or technologies of climate disaster that reinforce oppression. To advance an emancipatory climate justice agenda to enable more radical reparative measures and possibilities, the paper suggests that analyses and political strategy must be grounded in people's history, cultural, ethical, and communal governance practices.

A contextual approach to decolonising IR: Interrogating knowledge production hierarchies

Abstract Although calls to decolonise International Relations (IR) have become more prominent, the endeavour becomes infinitely more complex when searching for concrete approaches to decolonise IR knowledge production. We posit that decolonising IR, a global counter-hegemonic political project to dismantle and transform dominant knowledge production practices, must be enacted according to context-specific particularities. Contexts shape practices of epistemological decolonisation, since knowledge hierarchies are enacted and experienced – and must be challenged and dismantled – differently in different sites. Yet although acknowledged as important, contexts are understudied and under-theorised. This raises several questions: how do contexts matter to IR knowledge production, in what ways, and with what effects? This article disaggregates six contexts in IR knowledge production – material, spatial, disciplinary, political, embodied, and temporal – and explores how they impact academic practices. We bring together hitherto-disparate insights into the role of contexts in knowledge production from Global IR, Political Sociology, Feminist Studies, Higher Education Studies, and Critical Geopolitics, illustrating them with empirical evidence from 30 interviews with IR scholars across a variety of countries and academic institutions. We argue that an interrogation of the inequalities produced through these contexts brings us closer towards developing concrete tools to dismantle entrenched hierarchies in IR knowledge production.

Perbandingan Konsep Integrasi Sains dan Agama Menurut Imam Prayogo dan M. Amin Abdullah

This research aims to find out the thoughts of Imam Prayogo and Amin Abdullah regarding the tree of knowledge and spider web models, to find out the differences in the thoughts of the two figures. By using data collection techniques in the form of studying and collecting data through reading materials sourced from primary books and secondary books related to the two figures discussed. This research uses a qualitative descriptive approach, and the type of research used is library research, namely collecting data or scientific writing aimed at the object of research or library data collection. From the research results, it was concluded that Imam Prayogo placed greater emphasis on the hierarchy and structure of knowledge rooted in revelation as the main foundation, with a focus on modernization and renewal of Islamic thought. Amin Abdullah, meanwhile, highlights the deep integration between Islamic and secular sciences in dealing with the complexities of contemporary life, placing the Qur'an and Sunnah at the center of his scientific framework.

Analyzing convolutional neural networks and linear regression models for wind speed forecasting in sustainable energy provision

Wind energy's significance lies in its contribution to electricity production. Accurate wind speed prediction is crucial for precisely forecasting electricity generation, enhancing its overall importance. For the wind speed prediction two methods are developed in this paper that are the Linear Regression Method and Convolutional Neural Networks (CNNs). Linear regression makes a linear relation between input and output which are used to predict continuous outcomes. The second proposed leverage hierarchical feature extraction through convolutional layers, enabling them to excel at tasks like pattern recognition by capturing spatial patterns and hierarchies of information. Hyperparameter tuning is applied on both the models to minimize the errors. Then both the model’s performances are compared under different error matrices including MAE, RMSE, MSE and MAPE. The observations indicate that both the Linear Regression Model and CNN models are capable of forecasting wind speed However, the Linear Regression Model after Hyperparameter tuning performs better in terms of the calculated errors.

DNA Identities: Narrative and Authority in Genetic Ancestry Performance on YouTube

Abstract The rise of direct-to-consumer genetic ancestry testing and social media technologies have converged to create a particular genre of vernacular identity performance: the genetic ancestry “reveal” on YouTube. This article seeks to understand these performances in relation to the authority that performers grant test results to inform racial and/or ethnic identities, how performers establish hierarchies of knowledge when family folklore and genetic test results collide, and what these performances reveal about conceptions of genetic determinism today.

NAVIGATING BUSINESS INTELLIGENCE TOOLS: STRATEGIES TO DRIVE BUSINESS GROWTH

This study explores the evolution and current state of business intelligence (BI) tools and their strategic role in driving business growth. The research utilizes a combination of market analysis, industry case studies, and theoretical frameworks, including the DIKW hierarchy and Resource-Based View, to examine BI adoption trends. The results highlight the importance of data quality, cross-functional collaboration, and user adoption in maximizing BI effectiveness. Key findings indicate that cloud-based and self-service BI tools significantly improve data-driven decision-making, while challenges remain in data governance and integration. To address these challenges, organizations must implement robust data policies and empower users through training and self-service capabilities. The study concludes that integrating BI tools into digital transformation initiatives provides a competitive edge, enabling strategic planning, operational efficiency, and innovation. This research offers new insights into how organizations can leverage BI tools for sustained growth and enhanced decision-makingl.

Cross‐Domain Information Integration in Government: Hierarchies and Responsibilities

ABSTRACTCross‐domain integration of information is increasingly identified as a priority across public sector contexts because (in theory) it enables the use of more information, including information from groups and communities historically excluded from public sector decision making. In this paper, we reject the tendency to take ‘integration’ for granted, arguing the need to position cross‐domain integration as an information practice, and conducting mixed methods thematic analysis of government strategic documents to validate the utility of this approach. We find that depending on the type of information proposed to be integrated — digital data versus the knowledge of peoples and communities — our sample of Canadian government institutions treats cross‐domain integration with differing levels of procedural rigour and detail. Reflecting ASIS&T 2024 themes of prioritizing responsibility and reflexivity in information practice, and of cultivating community partnerships through practice, not merely in name, we discuss the information hierarchies that emerge in the cross‐domain information integration in government and the associated impacts on stakeholder communities.

‘I think my body knew what it was before I did’: Affirming women’s embodied experiences as a conduit to knowing

This paper focuses on ignorance within the phenomenon of women who experience female ejaculation. Based on ethnographic research, I show how the experience of the phenomenon in the absence of propositional knowledge about it results in what I term ‘experiential ignorance.’ This type of ignorance is caused by the cultural positioning of propositional knowledge as the most valid and reliable form of knowledge about the body. Experiential ignorance can be manifested in many different ways, such as an inability to categorize and validate subjective bodily experiences, resulting in feelings of doubt, shame, and can even lead to somatic effects. Nevertheless, some women challenge this knowledge hierarchy by valuing their bodily sensations as legitimate sources of information. The paper concludes that reconceptualizing ignorance to include experiential dimensions reveals the power dynamics inherent in knowledge production and provides opportunities for women to reclaim authority over their bodies and pleasurable experiences. This framework has broader implications for understanding embodied knowledge and ignorance across diverse sociocultural contexts.

Academics’ dilemmas in addressing challenging societal issues in today’s higher education landscape

ABSTRACT The critical role of universities in addressing societal issues is considered particularly important nowadays, when our futures are being threatened by various forces. Given this context, this study aimed to gain an understanding of academics’ perceptions of their role in engaging with ongoing societal challenges. Semi-structured interviews were conducted with 26 academics, 14 female and 12 males, from three universities in Iceland. The findings revealed that academics see the university as a critical player in responding to societal challenges, yet their reflections underscore the complexities and tensions that this role entails. These include persistent tensions related to knowledge hierarchies and criticality, as well as complexities related to competition and the marketisation of research.

Co-design, neighbourhood sharing, and commoning through urban living labs

ABSTRACT This paper examines the role of co-design methods in catalysing neighbourhood sharing and commoning in European cities. Through the comparative analysis of two design-mediated Urban Living Labs (ULLs) in Bagneux/Paris and Poplar/London, the paper explores how neighbourhood sharing of goods, spaces, and experiences are sustained in two different contexts. The paper then presents a co-design framework which was implemented in both cities, catalysing new sharing projects and relations in support of urban commons. We conclude that nesting co-design practices within ‘civic-organic’ ULLs can help to foster productive long-term relations between communities and academic partners based on mutual trust and help to initiate new sharing practices in the neighbourhoods of study. We argue that co-design methods are generative in this space, flattening knowledge hierarchies, supporting action on the ground, and developing situated responses to local needs.

Mitigation measures for addressing gender bias in artificial intelligence within healthcare settings: a critical area of sociological inquiry

AbstractArtificial intelligence (AI) is often described as crucial for making healthcare safer and more efficient. However, some studies point in the opposite direction, demonstrating how biases in AI cause inequalities and discrimination. As a result, a growing body of research suggests mitigation measures to avoid gender bias. Typically, mitigation measures address various stakeholders such as the industry, academia, and policy-makers. To the author’s knowledge, these have not undergone sociological analysis. The article fills this gap and explores five examples of mitigation measures designed to counteract gender bias in AI within the healthcare sector. The rapid development of AI in healthcare plays a crucial role globally and must refrain from creating or reinforcing inequality and discrimination. In this effort, mitigation measures to avoid gender bias in AI in healthcare are central tools and, therefore, essential to explore from a social science perspective, including sociology. Sociologists have made valuable contributions to studying inequalities and disparities in AI. However, research has pointed out that more engagement is needed, specifically regarding bias in AI. While acknowledging the importance of these measures, the article suggests that they lack accountable agents for implementation and overlook potential implementation barriers such as resistance, power relations, and knowledge hierarchies. Recognizing the conditions where the mitigation measures are to be implemented is essential for understanding the potential challenges that may arise. Consequently, more studies are needed to explore the practical implementation of mitigation measures from a social science perspective and a systematic review of mitigation measures.

Knowledge hierarchy-based dynamic multi-objective optimization method for AUV path planning in cooperative search missions

This study focuses on path planning for Autonomous Underwater Vehicles (AUVs) in underwater cooperative search missions. The complexities of the ocean environment, the uncertainty of target movements, and limited communication capabilities render underwater cooperative search missions dynamic multi-objective optimization challenges. Studies focusing on communication-constrained search strategies still lack reliable metrics for assessing underwater communication quality and do not consider communication dead zones. Addressing these deficiencies, this paper introduces a novel communication optimization strategy utilizing packet error rate as a metric for assessing communication efficacy, complemented by a potential field-based method for navigating out of communication dead zones. To tackle the inherently dynamic nature of cooperative search missions for mobile underwater targets, we propose a dynamic multi-objective optimization algorithm that employs a knowledge hierarchy strategy. This method enhances the NSGA-II algorithm's efficiency by extracting effective gene segments from historical Pareto solution set and generating a new initial population through recombination, hierarchy, and prediction. Distinct from other advanced dynamic multi-objective optimization approaches that are limited to theoretical problems, our approach is directly applicable to practical scenarios. The effectiveness and practicality of the proposed method are validated through a series of simulation experiments considering the impact of underwater acoustic communication. These results demonstrate that this research is not only innovative in theory but also holds significant engineering value and practical prospects in real-world applications.

The promises and pitfalls of cryptocurrencies and blockchain for marginalized communities

ABSTRACT Cryptocurrencies, and the blockchain technology that underlies them, have attracted much attention over the last decade from scholars, tech communities, financial institutions, states and more. The extreme volatility of the cryptocurrency market has made some people very rich and cost others almost everything. Importantly, there are many indications that marginalized communities are especially attracted to this new technology while being more vulnerable to issues such as fraud and exploitation in this field. This paper reviews academic research – predominantly social scientific – on cryptocurrencies and financial blockchain to determine the extent to which they engage with the experiences, agencies, and knowledges of marginalized communities. Overall, the findings show that, bar a few important exceptions that take seriously marginalized communities, academic research has largely focused on traditionally dominant actors such as crypto evangelists, fintech developers, states, and banks. Furthermore, the knowledges of marginalized communities are almost entirely absent while research privileges already dominant theories and research methodologies. Such trends in academic research on cryptocurrencies and blockchain technology reproduce existing knowledge hierarchies and lead to the further material marginalization of already vulnerable communities. In light of these findings, we conclude with some recommendations for further research that can challenge these problematic dynamics.

Polycentric governance, epistocracy and the limits of policing knowledge in preparing for the climate crisis

ABSTRACT The last two decades have seen an increase in the intensity and frequency of extreme weather events, placing complex demands on police and emergency services in the UK. Despite the growing recognition of the cascading and multidimensional threats, there is limited understanding of how policing and local governance actors are preparing for the climate crisis. In this paper, we argue that polycentric governance approaches, such as the Local Resilience Forums (LRFs), provide an essential focal point for emergency planning and disaster response activity that is rooted in localised contexts. However, while the LRFs are designed to benefit from the inclusion of a broad range of actors, dominant mentalities, knowledge hierarchies and powerful actors may limit their epistemic potential. We propose that a pathway towards a resilient and adaptive policing agenda for the Anthropocene necessitates acknowledging the limits of policing knowledge, expertise and traditional command-and-control mentalities. We draw on the notion of epistocracy to propose a policy and research agenda for police and partner agencies to harness the epistemic potential of LRFs. By adopting approaches to leverage pluralised forms of knowledge and identifying strategies for co-opting community-based actors in emergency planning and response activities, police and partner agencies can strengthen local capacity-building and better promote local resilience and adaptation efforts.

How indigenous spiritual beliefs shape health-related consumption rituals: shipibo health rituals to tackle covid-19

PurposeIn marketing and consumer research, the study of Indigenous ideas and rituals remains limited. The authors present an Indigenous-informed study of consumption rituals co-produced with members of the Shipibo–Konibo Indigenous group of the Peruvian Amazon. Specifically, the authors worked with the Comando Matico, a group of Shipibos from Pucallpa, Peru. This study aims to investigate how Indigenous spiritual beliefs shape health-related consumption rituals by focusing on the experience of the Shipibos and their response to COVID-19.Design/methodology/approachDrawing upon the principles of Indigenous research, the authors co-produced this study with the Comando Matico. The authors collaboratively discussed the research project’s design, analysed and interpreted data and co-authored this study with members of the Comando Matico. This study uses discourse analyses. The corpus of discourse is speech and text produced by the Comando Matico in webinars and online interviews during the COVID-19 pandemic. The full and active participation of the Comando Matico informed the discourse analysis by ensuring Indigenous knowledge, and worldviews were infused throughout the process.FindingsThe authors foreground how Indigenous spiritual beliefs act as a force that imbues the knowledge and practice of health, wellbeing and illness, and this process shapes the performance of rituals. In Indigenous contexts, multiple spirits coexist with consumers, who adhere to specific rituals to respond to and relate to these spirits. Indigenous consumption rituals involve the participation of non-human beings (called rao, ibo, yoshin and chaikoni by the Shipibos) and this aspect challenges the traditional notion of rituals and ritual elements in marketing.Originality/valueThe authors demonstrate how Indigenous spiritual beliefs shape consumption rituals in the context of health and draw attention to how the acknowledgement of alternative ontologies and epistemologies can help address dominant hierarchies of knowledge in marketing theory.

Tc-llama 2: fine-tuning LLM for technology and commercialization applications

This paper introduces TC-Llama 2, a novel application of large language models (LLMs) in the technology-commercialization field. Traditional methods in this field, reliant on statistical learning and expert knowledge, often face challenges in processing the complex and diverse nature of technology-commercialization data. TC-Llama 2 addresses these limitations by utilizing the advanced generalization capabilities of LLMs, specifically adapting them to this intricate domain. Our model, based on the open-source LLM framework, Llama 2, is customized through instruction tuning using bilingual Korean-English datasets. Our approach involves transforming technology-commercialization data into formats compatible with LLMs, enabling the model to learn detailed technological knowledge and product hierarchies effectively. We introduce a unique model evaluation strategy, leveraging new matching and generation tasks to verify the alignment of the technology-commercialization relationship in TC-Llama 2. Our results, derived from refining task-specific instructions for inference, provide valuable insights into customizing language models for specific sectors, potentially leading to new applications in technology categorization, utilization, and predictive product development.

Designing visual hierarchies for the communication of health data.

Visual hierarchy underlies all visual design decisions related to information presentation. This manuscript describes the experience of a multidisciplinary health data visualization and software design team in using visual hierarchy to redesign a hereditary colorectal cancer lab report. A series of interviews with representative users were conducted to identify target user groups and determine information hierarchy for each user type. Visual elements (eg, size, color, contrast, etc.) were then assigned to mirror the information hierarchy and workflow for each user type. User research identified 2 distinct user groups as consumers of the redesigned lab report. An interactive design employing a 2-level page hierarchy was developed, which stratified the content to support the needs of each user type. The challenges related to displaying the complex nature of digital and personal health data can be addressed by applying foundational design methods such as visual hierarchy. Visual hierarchy, a foundational design principle, can be used by visualization teams to clearly and efficiently present complex datasets associated with healthcare.