Mutual Learning Research Articles

Equity and modeling in sustainability science: Examples and opportunities throughout the process

Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.

Multidirectional Heritage-Led Knowledge Exchange: Learning from Practice in 19 Rural Territories

Rural areas are regaining attention as key resource holders. This includes the attractiveness of intact and traditional cultural elements and heritage which helps to create new opportunities. However, renewal is needed for rural areas to be competitive beyond tourism. Knowledge exchange and transfer is seen as an enabling tool for regeneration and heritage valorization, although it has mostly been applied in an urban context. The aim of this paper is to explore the role of capacity building and knowledge exchange at different levels in promoting rural regeneration through heritage-led initiatives. The article describes a multi-directional knowledge transfer and exchange in 19 rural areas. The applied knowledge exchange methodology was designed to be a dynamic and vibrant exchange of capacity building and mutual learning. This exchange of knowledge enabled the local communities involved to explore new ideas and viable solutions for the regeneration of rural areas through the valorization of cultural and natural heritage. The research findings show that structuring a knowledge transfer and capacity building process that also involves key local stakeholders and the rural communities is an important milestone in the regeneration process. In addition, it can be a unique opportunity to start and build new professional long-term relationships.

Making mutual learning tangible: Mixed-method Delphi as a tool for measuring the convergence of participants’ reciprocal understanding in transdisciplinary processes

This paper proposes an approach to capture mutual learning within transdisciplinary research to develop future-oriented sustainability solutions to land use conflicts. While quality criteria for transdisciplinary research projects are increasingly discussed, there is still ample methodological potential to enable and better understand mutual learning as a key component of transdisciplinarity. Changes in the specific developments of perceptions of the participants are difficult to be tamed and tracked. To address this shortcoming we propose to apply the Delphi method for longitudinal tracking of mutual learning within transdisciplinary research. We present the application of the methodological approach as part of a transdisciplinary project on sustainable land use in the district of Lüneburg (Lower-Saxony, Germany). Evaluation of semi-structured interviews with seven participants translated into a three-round Delphi survey. A concluding round of semi-structured interviews was performed to validate and deepen the findings. The results showcase that the Delphi method can facilitate the operationalization of the convergence of understandings as a relevant outcome of mutual learning within transdisciplinary projects.

Semisupervised Medical Image Segmentation through Prototype-Based Mutual Consistency Learning

Medical image segmentation is a critical task in the healthcare field. While deep learning techniques have shown promise in this area, they often require a large number of accurately labeled images. To address this issue, semisupervised learning has emerged as a potential solution by reducing the reliance on precise annotations. Among these approaches, the student-teacher framework has garnered attention, but it is limited in its reliance solely on the teacher model for information. To overcome this limitation, we propose a prototype-based mutual consistency learning (PMCL) framework. This framework utilizes two branches that learn from each other, incorporating supervision loss and consistency loss to adapt to minor data perturbations and structural differences. By employing prototype consistency learning, we are able to achieve reliable consistency loss. Our experiments on three public medical image datasets demonstrate that PMCL outperforms other state-of-the-art methods, indicating its potential in semisupervised medical image segmentation. Our framework has the potential to assist medical professionals in enhancing their diagnoses and delivering improved patient care.

Artistic Mutual Learning under the Vision of "Belt and Road"

Artistic Mutual Learning under the Vision of "Belt and Road"

Transformative public procurement for innovation: ordinary, dynamic and functional capabilities

ABSTRACT Public Procurement for Innovation (PPI) requires multiple roles from the public administration according to the problem-solution space, delineated by the level of consensus around the definition of the needs of the contracting authority and the potential solutions to address them. Each role involves a distinct mix of capabilities, which we categorize as ordinary (i.e. doing things right), dynamic (i.e. doing the right things) and functional (i.e. addressing functional challenges). Following a Mutual Learning Exercise with procurement officials of 15 European countries, we identify 45 capabilities for contracting authorities to embrace the different facets of PPI as a transformative policy instrument.

Harmonious Mutual Learning for Facial Emotion Recognition

Facial emotion recognition in the wild is an important task in computer vision, but it still remains challenging since the influence of backgrounds, occlusions and illumination variations in facial images, as well as the ambiguity of expressions. This paper proposes a harmonious mutual learning framework for emotion recognition, mainly through utilizing attention mechanisms and probability distributions without utilizing additional information. Specifically, this paper builds an architecture with two emotion recognition networks and makes progressive cooperation and interaction between them. We first integrate self-mutual attention module into the backbone to learn discriminative features against the influence from emotion-irrelevant facial information. In this process, we deploy spatial attention module and convolutional block attention module for the two networks respectively, guiding to enhanced and supplementary learning of attention. Further, in the classification head, we propose to learn the latent ground-truth emotion probability distributions using softmax function with temperature to characterize the expression ambiguity. On this basis, a probability distribution distillation learning module is constructed to perform class semantic interaction using bi-directional KL loss, allowing mutual calibration for the two networks. Experimental results on three public datasets show the superiority of the proposed method compared to state-of-the-art ones.

From distrust to trust: Balancing between forcing and fostering management control systems in a hostile cross-border post-acquisition integration

Extant research contends that in a context characterised by distrust, partners do not engage in developing trust in each other, and the use of management control systems creates tensions and increases distrust. This begs the questions of whether and how trust can be promoted and management control exercised in such a context. Thus, this paper examines the interplay between management control systems and (dis)trust in a hostile post-acquisition integration of two global companies. In doing so, this paper provides a detailed analysis of the role of management control systems as well as the underlying motives and the consequences of their use in various integration processes at different organisation levels. Applying the labour–management negotiation strategy theory, this study distinguishes between two modes of implementing management control. First, in the forcing mode, management control systems are used to coerce and monitor employees and instil top-down organisational values in them to promote controllability. Second, in the fostering mode, management control systems are exercised to promote mutual benefits, learning and shared values to support cooperation. The results show that the combined use of forcing and fostering management control systems supports the development of trust in the post-acquisition context characterised by distrust. Forcing control promotes trust by providing stability, creating accountability for cooperative achievements and supporting conflict resolution, whereas fostering control develops trust by facilitating goal sharing, mutual learning and value integration. This study advances the knowledge of management control systems and the relation between (dis)trust and control in the post-acquisition integration context by demonstrating why and how managers balance between forcing and fostering controls and how these control modes, separately and in combination, interact with (dis)trust.

Women, Peace and Security as deterrence? NATO and Russia's war against Ukraine

Abstract NATO's security turn following Russia's 2014 invasion of Ukraine opened new prospects for adopting the Women, Peace and Security (WPS) agenda from external operations to all tasks of the alliance. Drawing on feminist institutionalism and feminist pragmatist approach to security, this article interrogates NATO's WPS localization in deterrence and territorial defence. I demonstrate that NATO has in the past decade been unable to operationalize WPS in deterrence and defence. I identify following obstacles to NATO's post-2014 WPS considerations: first, implementing WPS pragmatically as an external, depoliticized and low-priority military agenda pushed primarily by femocrats; second, taking WPS to the strategic level while omitting practical localization in deterrence and defence; and third, approaching WPS partnership with Ukraine as a unidirectional transfer of NATO's WPS knowledge to Ukraine rather than a mutual learning. I argue that these institutional factors made NATO's WPS implementation only reactive and ultimately ill-prepared for such gendered security crisis as the one caused by Russia's full-out war against Ukraine in 2022. The article makes the case for rethinking feminist conceptualization of deterrence through the convergence of WPS and resilience agendas. This concerns going beyond military deterrence and centring social and political practices which are linked to societal resilience.

Inverting the deficit model in global mental health: An examination of strengths and assets of community mental health care in Ghana, India, Occupied Palestinian territories, and South Africa.

Global mental health [GMH] scholarship and practice has typically focused on the unmet needs and barriers to mental health in communities, developing biomedical and psychosocial interventions for integration into formal health care platforms in response. In this article, we analyse four diverse settings to disrupt the emphasises on health system weaknesses, treatment gaps and barriers which can perpetuate harmful hierarchies and colonial and medical assumptions, or a 'deficit model'. We draw on the experiential knowledge of community mental health practitioners and researchers working in Ghana, India, the Occupied Palestinian Territory and South Africa to describe key assets existing in 'informal' community mental health care systems and how these are shaped by socio-political contexts. These qualitative case studies emerged from an online mutual learning process convened between 39 academic and community-based collaborators working in 24 countries who interrogated key tenets to inform a social paradigm for global mental health. Bringing together diverse expertise gained from professional practice and research, our sub-group explored the role of Community Mental Health Systems in GMH through comparative country case studies describing the features of community care beyond the health and social care system. We found that the socio-political health determinants of global economic structures in all four countries exert significant influence on local community health systems. We identified that key assets across sites included: family and community care, and support from non-profit organisations and religious and faith-based organisations. Strengthening community assets may promote reciprocal relationships between the formal and informal sectors, providing resources for support and training for communities while communities collaborate in the design and delivery of interventions rooted in localised expertise. This paper highlights the value of informal care, the unique social structures of each local context, and resources within local communities as key existing assets for mental health.

Mutual learning through participatory storytelling: Creative approaches to climate adaptation education in secondary schools

Unprecedented global temperatures have brought the question of how to teach sensitive issues of climate change to the fore. In this paper we suggest that a refocusing on adaptation productively shifts the debate to climate justice and practical solutions to building community resilience. The paper examines a practice-led project that sought to innovate and test the use of participatory storytelling with young people to explore climate adaptation. Our insights relate to two areas: first, the benefits of mutual learning through engaging in dialogue with frontline communities; second, how participatory storytelling supports emotionally intelligent sensemaking, agency and leadership by providing both ‘connections’ and ‘containers’ for engaging with climate.

Congenital heart disease and comorbidities in primary care: a cross-sectional study

Background/Aims Patients with congenital heart disease are living longer as a result of surgical and medical advances. General practice is key in identifying and supporting lifelong care, yet there is a lack of research into congenital heart disease in this area. This study aimed to explore the prevalence and comorbidities of patients with congenital heart disease compared to those without congenital heart disease in primary care settings in Cheshire, England. Methods This cross-sectional study used routinely collected health data from the NHS general practice population information disease database within primary care in Cheshire. Clinical read codes for congenital heart disease were added to the current data analytics risk stratification tool. Searches for patients of all ages with and without congenital heart disease were undertaken in July 2022. A total of 765 576 patients were included in the study. Results Of 765 576 patient records, 6419 patients were coded with congenital heart disease, a prevalence of 0.8%, with a comparatively younger age compared with the non-congenital heart disease cohort. Patients with congenital heart disease were three times more likely to have heart failure (odds ratio=3.36; 95% confidence interval=2.96−3.81) or stroke (odds ratio=3.58; 95% confidence interval=3.24–3.94). The most frequent comorbidities in both groups were hypertension, anxiety and depression, with no significant difference between the groups. Among those with congenital heart disease, the prevalence of a learning disability was more than eight times higher than those without congenital heart disease (odds ratio=9.23; 95% confidence interval=8.16–10.55) and autism was three times more likely (odds ratio=2.98; 95% confidence interval=2.32–3.84) in those with congenital heart disease. Conclusions There are high rates of comorbidities in the congenital heart disease population in primary care. Innovative use of digital instruments can enable identification and risk stratification of patients with congenital heart disease to support lifelong care. Congenital heart disease guidance should include primary care settings to create opportunities for mutual learning that can enhance collaborative practice.

Research on the innovative path of precise communication of Chinese Martial Arts under the background of the "One Belt and One Road"

Research on the innovative path of precise communication of Chinese Martial Arts under the background of the "One Belt and One Road"

Racism in the “colony”: Towards appreciating race fluidity and racialization in social psychology of racism

AbstractRace is a significant means through which individuals and groups relate to each other. A problematic instance of its significance is colonialism and all the destruction it brought with it. In this paper, I explore how knowledge about race and racism from settings that were erstwhile colonized can enrich current understandings and approaches to studying race and racism in social psychology. I advance the possibility of mutual learning and sharing of theoretical and methodological practices for researchers who examine race and racism in colonizing or settler‐colonial settings and those in erstwhile colonized settings. I do so by first, locating the centrality of Whiteness for the very development of race categories and the shaping of psychology as a discipline. Second, I discuss how race and racism are examined in (primarily) Euro‐American contexts, with a focus on engagement with Whiteness by Critical Race Psychologists and social constructionist researchers. Third, I outline alternative ways of engaging with race and race categories identified in erstwhile colonized places. I end with how this latter informs our understandings of race and racism, and possibilities for mutual learning.

Flood mitigation with the support of demographic bonuses in Indonesia

Floods during the rainy season are still a polemic for Indonesia because disaster create various losses and fatalities. Although, drainage development, green environment and outreach have been implemented. However, public awareness of waste that block the flow of water needs to be evaluated. Therefore, the bibliometric analysis then using Vos Viewer software to discuss relevant research topics. The aim is to provide the management of hydrometeorological disaster mitigation. Therefore, the literature review in this article then discusses various flood threats, efforts by several regions to overcome them, human resources and character of education. The results of the discussion show that flood control requires with collaboration. For this purpose, the demographic bonus in Indonesia needs to be used to optimize public participation. Moreover, recommendation from the research is that any schools to hold group teens go clean activities as mutual cooperation learning. Policy alternatives to build some intrinsic motivation and extrinsic motivation for each individual in creating a flood free area in their environment.

In-Hospital Arrangements for Preoperative Simulation

Neurosurgeons of the future must possess the ability to engage in preoperative simulation. However, given the changing medical practices and redistribution of tasks among physicians, the significance of radiological technologists is increasing. In this article, we describe the collaboration between radiological technologists and the hospital system to simplify preoperative simulation for young physicians. Preparation for preoperative simulation is a collaborative process with radiological technologists, aiming to facilitate mutual learning and risk management. It involves recognizing and utilizing the expertise of certified radiological technologists for imaging and additional surgical support, with due consideration given to the additional fees. The creation of an in-hospital arrangement system for preoperative simulation ensures more efficient and safer workflow.

Mutual Adaptation: Learning From Prototype for Time-Series Prediction

Time series prediction is a current research hotspot in deep learning. However, due to the complex nature of time series data, the modelling in this task is often highly non-convex, which can make the final convergence unstable. To address this challenge, recent works have proposed deep mutual learning frameworks that allow models to learn from both ground truth and knowledge of other models in order to locate a better convergence point. However, a key disadvantage of deep mutual learning is that models that converge to poor local optima may still share their knowledge, limiting overall performance. To overcome this limitation, we propose a new learning framework called mutual adaptation, which selects a prototype model that has the least error among all the models in the framework as the common teacher model. In addition, we incorporate a strategy of learning from each individual model's best local optimum in the history of training. Our experimental results show that, on average across multiple datasets, our method improves the performance of both Informer and LSTM models compared to deep mutual learning by 4.73% in MAE and 6.99% in MSE for Informer, and 11.54% in MAE and 18.15% in MSE for LSTM. We also demonstrate the importance of memory of individual best local optima and provide sensitivity analysis and visualization of error and the loss descending process. Our method represents a new state-of-the-art in group learning for time series prediction.

학습자 입장에서 이해가 잘 되는 효과적인 수업운영 탐구–직소모형이 적용된 교직 수업 운영에 기반하여-

This study aims to reflect on classes that are easily understood from the learner's perspective and effective teaching methods, seeking improvements based on this reflection. The research participants are students participating in pedagogical subject classes applying the "Jigsaw(Direct –indirect) Model”. The reflective tasks include the following questions: "1. What characteristics should a class have for learners to understand it well from their perspective? 2. From the learner's perspective (applying the 'Jigsaw(Direct –indirect) Model'), what are effective methods for operating a class?” The research findings indicate that a class is well understood from the learner's perspective when the essential content is explained in an easily understandable manner. To operate such classes, it is crucial to comprehend and systematically organize the core content, preparing corresponding learning materials. During this process, it is essential to utilize learning activity sheets, consider the use of visual materials such as drawings, PowerPoint presentations, and images, and incorporate tools like blank worksheets, checking understanding during class, and post-class reflection opportunities are essential. Through these practices, learners are provided with opportunities for active participation. In classes applying the ‘Jigsaw(Direct –indirect) Model', learners exhibited awareness of the effectiveness of collaborative activities, while the reflection on class preparation and operation provided a sense of accomplishment and diverse educational experiences. Effectively managing classes using the ‘Jigsaw(Direct –indirect) Model' requires providing sufficient activity time, offering opportunities for rapport formation among group members, preventing free riding, exploring ways to improve the class environment, and guiding techniques for mutual learning. Additionally, meticulous planning, designing, and preparation by the instructor are necessary for successful class operations.

Cross-jurisdictional disaster preparedness: A Nigeria-USA data-analytical approach

Disasters pose significant challenges globally, demanding effective preparedness strategies to mitigate their impact. This study proposes a novel approach to disaster preparedness through cross-jurisdictional collaboration between Nigeria and the United States, leveraging data analytics for enhanced readiness. Nigeria, with its vulnerability to various disasters, and the United States, known for its advanced disaster management systems, offer a unique opportunity for mutual learning and collaboration. This research aims to bridge the gap in disaster preparedness between these two countries by employing a data-driven analytical framework. Through the collection, analysis, and comparison of disaster-related data from both nations, this approach seeks to identify commonalities, differences, and best practices in disaster preparedness strategies. By leveraging the strengths of both countries, such as Nigeria's community resilience and the USA's technological advancements, this approach aims to develop comprehensive disaster preparedness models tailored to the specific needs and contexts of each jurisdiction. Key components of this approach include data collection from various sources, including historical disaster records, socio-economic indicators, infrastructure data, and community resilience metrics. Advanced analytical techniques, such as machine learning algorithms and spatial analysis, will be employed to identify patterns, assess vulnerabilities, and predict potential disaster scenarios. The findings will inform the development of targeted preparedness strategies, including early warning systems, evacuation plans, resource allocation, and capacity building initiatives. Furthermore, this research emphasizes the importance of multi-stakeholder collaboration and knowledge exchange in disaster preparedness. By involving government agencies, non-governmental organizations, academic institutions, and local communities from both Nigeria and the USA, this approach aims to foster a holistic and inclusive preparedness framework. Ultimately, this study seeks to contribute to the global discourse on disaster risk reduction by demonstrating the effectiveness of cross-jurisdictional collaboration and data-driven approaches in enhancing disaster preparedness. By leveraging the strengths and experiences of Nigeria and the USA, this research aims to develop scalable and adaptable models that can be applied in diverse contexts to build resilience and mitigate the impact of disasters.

Educational approaches in African social work: Implications for U.S. social work training

This paper presents a comprehensive exploration of the methodologies in social work education, focusing on the potential integration and synergy between African and U.S. systems. Set against the backdrop of an increasingly globalized world, the study aims to bridge the gap between these two distinct educational paradigms, highlighting the rich diversity and potential for mutual learning. The scope of the paper encompasses a detailed examination of the historical evolution, pedagogical approaches, and the role of culture and tradition in social work practices within both regions. Adopting a comparative educational analysis as its methodological backbone, the study foregoes traditional fieldwork in favor of an extensive literature review and case study analysis. This approach facilitates a nuanced understanding of the differences and similarities in social work education across these diverse cultural contexts. The main findings reveal significant disparities in curriculum design, pedagogical methods, and the integration of community engagement and indigenous knowledge. African social work education, characterized by its community-centric approaches and cultural inclusivity, offers valuable insights that could enhance the U.S. framework. Conversely, the structured methodologies and technological advancements in U.S. programs present opportunities for African social work education. The study concludes with a call for a collaborative, reciprocal educational model. Recommendations include joint curriculum development, faculty exchanges, and shared research initiatives. Such collaborative efforts are essential for preparing future social workers to effectively address global challenges, fostering a more inclusive and culturally sensitive approach to social work education.