Search Results (112)

This paper addresses the definitional ambiguity surrounding the term “green fintech” and its distinction from related concepts such as green finance and sustainable finance. We argue that the lack of clarity impedes accountability and facilitates greenwashing. To resolve this, we develop a conceptual framework grounded in a six-step “litmus test” that specifies the necessary conditions for an initiative to qualify as green fintech. These include demonstrable environmental objectives, the application of innovative financial technologies, and regulatory alignment. The test functions as a diagnostic tool, enhancing verifiability and reducing the risk of misrepresentation. We illustrate its practical use and integrate the Dynamic Integrated Model of Climate and the Economy (DICE) to support the analysis. Green fintech is defined as the implementation of green climate objectives through the medium of financial technology. This contribution provides both definitional precision and a means to assess the credibility of green fintech initiatives, offering clarity in an increasingly complex and contested area of sustainable finance. Full article

Reliable remote sensing-based Land Use and Land Cover (LULC) information is crucial for assessing Earth’s surface activities. Brazil’s agricultural dynamics, including year-round cropping, multiple cropping, and regional climate variability, make LULC monitoring a highly challenging task. The country has thirteen remote sensing-based LULC products specifically tailored for this purpose. However, the differences and the results of these products have not yet been synthesized to provide coherent guidance in assessing their spatio-temporal agricultural dynamics and identifying promising approaches and issues that affect LULC analysis. This review represents the first comprehensive assessment of the advantages, challenges, and limitations, highlighting the main issues when dealing with contrasting LULC maps. These challenges include incompatibility, a lack of updates, non-systematic classification ontologies, and insufficient data to monitor Brazilian LULC information. The consequences include impacts on intercropping estimation, diminished representation or misrepresentation of croplands; temporal discontinuity; an insufficient number of classes for subannual cropping evaluation; and reduced compatibility, comparability, and spectral separability. The study provides insights into the use of these products as primary input data for remote sensing-based applications. Moreover, it provides prospects for enhancing existing mapping efforts or developing new national-level initiatives to represent the spatio-temporal variation of Brazilian agriculture. Full article

The study of underrepresented ethnic groups in the social sciences is often hindered by structural and epistemic barriers that limit access to culturally embedded knowledge. This article examines the potential of the GPT-4 version of the ChatGPT language model as a complementary research tool used to generate insights into the Merchera ethnic group, whose presence in the academic literature remains minimal and often characterised by misrepresentation. Through a comparative analysis considering ChatGPT responses and the scarce number of existing sources, this study explores the model’s reliability, depth, and limitations. The findings reveal that while ChatGPT offers a coherent synthesis of available knowledge, it tends to reproduce the prevailing biases and informational gaps found in the existing academic discourse. The paper concludes that generative AI may serve as a provisional support for research on marginalised communities, but its outputs must be interpreted with caution and situated within a framework of critical inquiry and ethical responsibility. Full article

Regional planning agencies increasingly rely on Spatial Economic Models (SEMs) to evaluate the impact of various policies. However, traditional SEMs often employ homogeneous technical coefficients (TCs) to represent technology patterns used by activities located in very different areas of a region, leading to misrepresentations of production and consumption behaviors, and consequently, inaccurate modeling results. To this end, we propose a Differential Spatial Economic Modeling (DSEM) framework that incorporates region-specific TCs for activities within Independent Planning Units (IPUs), such as provinces or cities, each characterized by unique economic, demographic, and technological features. The DSEM framework comprises three core components: (1) a regional economy model that forecasts activity totals for each IPU using economic and demographic forecasting model, supplemented by statistical analyses like the Gini index and K-means clustering to group activities from different IPUs into homogeneous ‘technology’ clusters based on their TCs; (2) a land use model that allocates IPU activity totals to corresponding traffic analysis zones (e.g., counties or districts) using the Differential Spatial Activity Allocation (DSAA) method. This determines the spatial distribution of commodities (such as goods, services, floor space, and labor) across exchange zones, balancing supply and demand to achieve spatial equilibrium in both quantity and price; and (3) a transport model that performs modal split and network assignment, distributing commodity trip origin–destination matrices across a multimodal transportation supernetwork (highways, railways, and waterways) using a probit-based stochastic user equilibrium assignment model. The proposed method is applied to a case study of the Yangtze River Economic Belt, China. The results demonstrate that the proposed DSEM yields better goodness-of-fit (R²) values between observed and estimated flows compared to the traditional aggregate SEM. This indicates a more precise and objective representation of spatial economic activities and technological patterns, thus resulting in improved estimates of freight flows for individual transportation modes and specific links. Full article

There has been recent proliferation of entrepreneurship theorizing involving the true uncertainty of a system—most often labeled as Knightian. This has been noted in both individual papers and in the main partial theories that attempt to explain entrepreneurial activity more holistically. We detect a danger in this work involving such true uncertainty—defined by the condition that decisions plagued by it are non-optimizable by every interested party. It is that all the recent theorizing misinterprets that uncertainty in one of two ways: with a logical contradiction (i.e., that the non-optimizable is actually optimizable); or with a misrepresentation (i.e., that an uncertainty consisting of a knowable unknown that can be made known through known means by the time the decision must be made is true). Our concern is that such misinterpretations create unnecessary costs to academics and practitioners who are struggling to define the system they are managing. We explain this concern and its costs, detail the underlying premises, illustrate it with several examples, and then offer various specific directions to improve the theorizing over such uncertainty in entrepreneurship. Full article

Recycled building materials offer an effective economic solution to the environmental issues caused by construction and demolition waste (CDW). However, they also create opportunities for information misrepresentation by remanufacturers. Despite the significance of this issue, existing research has largely overlooked the impact of such misrepresentation on the pricing decisions for recycled building materials. The study aims to reveal how information misrepresentation influences pricing in the context of recycled building materials. This paper develops a supply chain model for the resource utilization of construction waste, consisting of both a remanufacturer of recycled building materials and a traditional building material manufacturer. The model evaluates the effects of information misrepresentation by the remanufacturer on pricing decisions. The main findings are as follows: (1) The impact of misrepresentation of information on manufacturers depends on government subsidies and the remanufacturing process misrepresentation factor. When the government adopts a low subsidy policy, as the remanufacturing process misrepresentation factor increases, manufacturers’ profits are U shaped. When the government adopts a high subsidy policy, manufacturers’ profits are positively related to the remanufacturing process misrepresentation factor. (2) When government subsidies exceed a certain threshold, there is a negative impact on remanufacturers, who tend to reduce the level of misrepresentation in their remanufacturing processes. This study not only broadens the research on information misrepresentation through the lens of social exchange theory but also provides valuable insights for government policy decisions, particularly in regulating misrepresentation behaviors by remanufacturers under various scenarios. Full article

Background: Three aconitine poisoning events occurred in two Canadian provinces in 2022: one in British Columbia (BC) and two in Ontario (ON). Aconitine is a potent alkaloid found in several species of the plant Aconitum, containing cardiotoxins and neurotoxins. It is used in traditional Chinese medicine (TCM) for pain management, and in powdered form, Aconitum is similar in appearance to sand ginger (Kaempferia galanga), which can lead to poisonings from misidentification and mislabeling. Methods: Aconitine poisoning is rare in Canada; here, we compare communications, collaborations, laboratory testing options and actions during investigations. Results: Fourteen cases occurred from the consumption of sand ginger: in BC (n = 2), purchased at an Asian health food store; in ON (n = 11), Kaempferia galanga powder (KGP) spices were used to prepare meals at a restaurant, and in one ON case, KGP was purchased. Traceback found product imported from China contained aconitine levels ranging from 1304 to 5500 ppm. Later investigations revealed mislabeling of Aconitum as KGP from the same imported lot (January 2020). Plant DNA testing found no KGP in any spice packets, including lots not linked to illness, suggestive of adulteration. Conclusion: Method development for aconitine in BC led to an improved response time for testing in ON. BC and ON updated outbreak response protocols and communications. Full article

Vaccine hesitancy presents a significant challenge to public health, particularly in culturally diverse regions, such as South Tyrol, Italy. This article examines the interplay between political influences, conspiracy theories, and vaccine hesitancy in South Tyrol, an autonomous province characterised by its linguistic diversity and historical scepticism toward central authority. This study aimed to identify the important drivers of vaccine hesitancy and propose targeted strategies to enhance vaccine acceptance. Peer-reviewed and grey literature was examined to explore the sociocultural factors, political dynamics, and conspiracy narratives influencing vaccine hesitancy in South Tyrol. The analysis incorporated publicly available materials, including propaganda from anti-vaccine organisations, and regional public health data to contextualise the findings. Vaccine hesitancy in South Tyrol was influenced by historical tensions with the central government, cultural alignment with Austrian healthcare practices, and politically motivated opposition to vaccination. Conspiracy theories disseminated by local organisations and political entities exploit concerns regarding governmental overreach and personal autonomy. These dynamics are compounded by the selective misrepresentation of scientific discourse, which further polarises public opinion. Addressing vaccine hesitancy in South Tyrol requires culturally sensitive communication, community engagement through trusted local figures, transparency in health policies, and the proactive monitoring of misinformation. These strategies can mitigate mistrust and promote vaccine acceptance in regions with similar sociopolitical complexities. Full article

Multibeam echosounder (MBES) backscatter data are influenced by underwater sound absorption, which is dependent on environmental parameters such as temperature, salinity, and depth. This study leverages CTD datasets from the Korea Oceanographic Data Center (KODC) to analyze and visualize the spatiotemporal variations in absorption parameters in the East Sea of Korea, which are subject to pronounced variability over time and space. The legacy MBES backscatter data, originally processed using generalized absorption parameters that neglected spatiotemporal variations, were compared with the calibrated data. The calibration process included inverse calculation of water temperature with depth-specific average salinity values from the nearest KODC stations. This calibration revealed discrepancies of up to 2.1 dB in backscatter intensity across survey lines, highlighting the potential misrepresentation of legacy MBES backscatter data due to site-specific absorption variability having been overlooked. By addressing these discrepancies, this study underscores the importance of incorporating spatiotemporal absorption variability into MBES calibration workflows. This integrated approach not only enhances the reliability of legacy MBES data but also provides valuable insights for marine resource management, seafloor mapping, and environmental monitoring in highly dynamic marine environments such as the East Sea of Korea. Full article

Research into the unio mystica has revealed what seems to be an area of “real discussion” between scholars of different traditions of mysticism, particularly those of Judaism, Christianity, and Islam. Although this research serves as a promising start to the dialogue among scholars, it has also raised many questions about a “shared moment” that is nevertheless expressed in “irreducibly diverse” and distinct ways in each tradition. What purpose, for instance, can generic cross-cultural categories serve when they mean little or nothing to scholars in each tradition? By contrast, tradition-specific vocabularies are profuse and often difficult to represent in interlinguistic contexts without significant explanation. The challenge of translating mystical texts, imagery, and ideas across cultures and linguistic traditions raises obvious concerns about the misrepresentation and distortion of traditions in an environment of post-colonial critique. Nevertheless, the continued promise of dialogue calls for specialists of these traditions—particularly non-western and non-Christian traditions—to approach, assess, re-formulate, and even challenge the categories of mysticism from within the conceptual and theoretical horizons of the traditions that they research. The present study models such an approach to scholarship in mysticism. It offers a (re)formulation of the unio mystica from within the theoretical frame of the 12th/13th-century Muslim/Sufi mystic, Ibn ʿArabī (d. 638/1240) and early members of his school of thought. By unpacking the primary terms involved in such an account—“God”, the “human being/self”, and “union”—from within the conceptual and theoretical horizons of that tradition, it problematizes the prevailing understanding of the unio mystica constructed from the writings of specialists in Christian mysticism. More importantly, it illustrates the payoff in terms of dialogue (incorporating the critique of existing theories) when each tradition operates confidently from its own milieu, developing its own theoretical resources for mysticism rather than prematurely embracing existing ideas or categories. Full article

This case study aims to problematise concepts of equine and human co-relational agency in the context of ‘mis-re-presentations’ in the Australian media of harms experienced by the Anglo Arab stallion, Cambridge, following his development of laminitis and his consequent confinement at a leading national Equestrian centre. Autoethnographic narrative is used to retrospectively and selectively narrate the evolving relationship between Cambridge and his owners, farrier, and treating veterinarians within the dominant housing and veterinary practices and welfare paradigms in equestrian culture of 1990’s Australia. Structured author/owner autoethnographic vignettes are framed by newspaper and internet reportage to highlight a productive tension between the public mediation of the case, and what it means to be fully embodied in relationship with an equine companion agent within a particular, racialised, gendered, and biopoliticised location. Adopting a phenomenologically informed intersectional feminist ethics of care perspective, a counternarrative to the gendered, racialised and essentialising rights-based judgements about Cambridge’s illness and eventual death that dominated the popular media is provided. Crucially, the autoethnographic vignettes are chosen to capture the corporeal reciprocity and rapport of forces that produced a co-created agentivity that characterised the horse’s birth, training, and treatment. The embodied interspecies knowledge that informs the training and care of equines (and all animal species) is always historically situated within permeable, dynamic worlds of self and other that are fluid, contextual, and always in relation. It is suggested that the case of Cambridge illustrates how competing stakeholder investments in animal welfare can play out in the public mediation of particular cases in ways that exclude their historical and interspecies situatedness and serve to reinforce dominant ideologies governing human and animal relationships. Full article

There are calls for the democratisation of higher education in line with the principles of social justice. Collaboration with students offers the potential for creating a more inclusive higher education environment, and open textbook development initiatives can be a vehicle for change. This paper focuses on the experiences of students as co-creators in open textbook initiatives at the University of Cape Town, South Africa. Drawing on interviews with 11 open textbook collaborators, this paper utilises Nancy Fraser’s social justice framework to explore students’ perspectives on injustices, challenges of collaboration and co-creation, and power dynamics in student–staff partnerships. The study shows that students experience and navigate various injustices in their classroom contexts related to economic maldistribution, cultural misrecognition and political misrepresentation. It reveals a complex interrelationship between student voice, power dynamics in the classroom, and the power of student–staff partnerships to build confidence and flatten hierarchies in open textbook co-creation. The student views presented here provide powerful evidence of a range of benefits they experience when the traditional hierarchies between student and lecturer are levelled through collaborative open textbook development processes. Results indicate that co-creation activities enabled them to have a voice through the power of publication and own their academic journeys. Full article

In this paper, we study the decision-making and coordination problem of a two-tier fresh food supply chain consisting of a supplier and a retailer. Considering the influencing factors of consumers’ information preference, freshness, and misrepresentation, we construct a centralized decision-making model and a decentralized decision-making Stackelberg game model. We also analyze the changes in the equilibrium solution of the supply chain before and after the input of blockchain technology, identify the conditions for the investment in blockchain technology, and design a “cost-sharing + benefit-sharing” combination contract for the coordination of the blockchain. The results are as follows: Firstly, under decentralized decision-making, if the fresh supplier misreports the freshness of the product, it will mislead the retailer to increase the order quantity, and its own profit will rise. Therefore, the fresh supplier has the motivation to misreport freshness. However, the backlog of fresh products will eventually damage the retailer’s profit, and the overall profit of the supply chain will also be damaged. Therefore, the increase in the profit of the fresh supplier is at the expense of the overall interests and stability of the supply chain. Second, when the investment cost of blockchain technology is within a certain threshold, it is feasible to invest in blockchain technology. Consumers’ preference for traceable fresh products will encourage the fresh supply chain to improve the level of information traceability and increase investment in blockchain technology. Finally, there are double marginal effects in the fresh supply chain under decentralized decision-making. The combined contract of “cost-sharing + revenue-sharing” can coordinate the overall revenue of the supply chain to the level of centralized decision-making. When the contract parameters meet certain conditions, Pareto improvement in revenue can be achieved for all parties involved in the fresh supply chain. The willingness of retailers to invest in blockchain technology will change with the change in contract parameters. When the proportion of retailers’ costs and the proportion of shared income are higher, the level of retailers’ investment in blockchain technology will decrease. Therefore, the interests of supply chain members need to be balanced in the process of contract coordination. Full article

Internalized racism is the internalization of beliefs about racism and colonization that contribute to the acceptance of negative messaging or stereotypical misrepresentations that inform perceptions about worth and ability. Internalized racism is associated with psychological distress in racially diverse people. Collective racial self-esteem is a potential protective factor that can serve as a moderator in reducing distress and facilitating psychological well-being. The sample for the present study consisted of 526 participants who self-identified as African American, Asian American/Pacific Islander, Latinx American, or American of Arab or Middle Eastern descent. The researchers used regression with the Process macro to investigate the potential moderating properties of collective racial self-esteem on the relationship between internalized racism and psychological distress in the sample. The findings indicated that specific domains of collective racial self-esteem moderated the internalized racism–psychological distress relationship. Full article

The exceptional performance of ImageNet competition winners in image classification has led AI researchers to repurpose these models for a whole range of tasks using transfer learning (TL). TL has been hailed for boosting performance, shortening learning time and reducing computational effort. Despite these benefits, issues such as data sparsity and the misrepresentation of classes can diminish these gains, occasionally leading to misleading TL accuracy scores. This research explores the innovative concept of endowing ImageNet models with a self-awareness that enables them to recognize their own accumulated knowledge and experience. Such self-awareness is expected to improve their adaptability in various domains. We conduct a case study using two different datasets, PBC and BCCD, which focus on blood cell classification. The PBC dataset provides high-resolution images with abundant data, while the BCCD dataset is hindered by limited data and inferior image quality. To compensate for these discrepancies, we use data augmentation for BCCD and undersampling for both datasets to achieve balance. Subsequent pre-processing generates datasets of different size and quality, all geared towards blood cell classification. We extend conventional evaluation tools with novel metrics—“accuracy difference” and “loss difference”—to detect overfitting or underfitting and evaluate their utility as potential indicators for learning behavior and promoting the self-confidence of ImageNet models. Our results show that these metrics effectively track learning progress and improve the reliability and overall performance of ImageNet models in new applications. This study highlights the transformative potential of turning ImageNet models into self-aware entities that significantly improve their robustness and efficiency in various AI tasks. This groundbreaking approach opens new perspectives for increasing the effectiveness of transfer learning in real-world AI implementations. Full article