Working with the tensions of transdisciplinary research: A review and agenda for the future of knowledge co-production in the Anthropocene

© 2024 The Author(s). Published by Cambridge University Press. This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives CC BY-NC-ND licence, https://creativecommons.org/licenses/by-nc-nd/4.0/Sustainability challenges in the age of the Anthropocene require researchers and practitioners to collaborate across multiple academic disciplines and multiple professions outside of universities. In this paper we draw on theories of institutional logics to explore how those involved in transdisciplinary environmental research and practice draw on particular sets of values and norms but encounter challenges to collaboration. These institutional logics include (among others) seeking societal/environmental impact, commercial objectives, and academic knowledge generation. In this paper we review the growing literature on the research experience of transdisciplinarity in sustainability; discuss the processes of managing such research; and present a framework that outlines the challenges and tensions at each stage of the innovation/research process. We set out an agenda for managing tension that calls for recognising the challenges, learning how to work with tensions, and building capabilities for future careers involving transdisciplinary research. The paper shows a key competence or skill for transdisciplinarians is the ability to develop complex collaborative relationships for sustainability drawing together different institutional logics, approaches, methods, goals, and values. Social media summary Transdisciplinary science: bridging disciplines, solving challenges. Soft skills and collaboration key to success.Peer reviewe

Effects of Higher-Order Cognitive Strategy Training on Gist-Reasoning and Fact-Learning in Adolescents

Improving the reasoning skills of adolescents across the United States has become a major concern for educators and scientists who are dedicated to identifying evidence-based protocols to improve student outcome. This small sample randomized, control pilot study sought to determine the efficacy of higher-order cognitive training on gist-reasoning and fact-learning in an inner-city public middle school. The study compared gist-reasoning and fact-learning performances after training in a smaller sample when tested in Spanish, many of the students’ native language, versus English. The 54 eighth grade students who participated in this pilot study were enroled in an urban middle school, predominantly from lower socio-economic status families, and were primarily of minority descent. The students were randomized into one of three groups, one that learned cognitive strategies promoting abstraction of meaning, a group that learned rote memory strategies, or a control group to ascertain the impact of each program on gist-reasoning and fact-learning from text-based information. We found that the students who had cognitive strategy instruction that entailed abstraction of meaning significantly improved their gist-reasoning and fact-learning ability. The students who learned rote memory strategies significantly improved their fact-learning scores from a text but not gist-reasoning ability. The control group showed no significant change in either gist-reasoning or fact-learning ability. A trend toward significant improvement in overall reading scores for the group that learned to abstract meaning as well as a significant correlation between gist-reasoning ability and the critical thinking on a state-mandated standardized reading test was also found. There were no significant differences between English and Spanish performance of gist-reasoning and fact-learning. Our findings suggest that teaching higher-order cognitive strategies facilitates gist-reasoning ability and student learning

Componential coding in the condition monitoring of electrical machines Part 2: application to a conventional machine and a novel machine

This paper (Part 2) presents the practical application of componential coding, the principles of which were described in the accompanying Part 1 paper. Four major issues are addressed, including optimization of the neural network, assessment of the anomaly detection results, development of diagnostic approaches (based on the reconstruction error) and also benchmarking of componential coding with other techniques (including waveform measures, Fourier-based signal reconstruction and principal component analysis). This is achieved by applying componential coding to the data monitored from both a conventional induction motor and from a novel transverse flux motor. The results reveal that machine condition monitoring using componential coding is not only capable of detecting and then diagnosing anomalies but it also outperforms other conventional techniques in that it is able to separate very small and localized anomalies

Structural Properties of Thermoresponsive Poly(N-isopropylacrylamide)-poly(ethyleneglycol) Microgels

The application of RNA interference to treat disease is an important yet challenging concept in modern medicine. In particular, small interfering RNA (siRNA) have shown tremendous promise in the treatment of cancer. However, siRNA show poor pharmacological properties, which presents a major hurdle for effective disease treatment especially through intravenous delivery routes. In response to these shortcomings, a variety of nanoparticle carriers have emerged, which are designed to encapsulate, protect, and transport siRNA into diseased cells. To be effective as carrier vehicles, nanoparticles must overcome a series of biological hurdles throughout the course of delivery. As a result, one promising approach to siRNA carriers is dynamic versatile nanoparticles that can perform several in vivo functions. Over the last several years, our research group has investigated hydrogel nanoparticles (nanogels) as candidate delivery vehicles for therapeutics, including siRNA. Throughout the course of our research, we have developed higher order architectures composed entirely of hydrogel components, where several different hydrogel chemistries may be isolated in unique compartments of a single construct. In this Account, we summarize a subset of our experiences in the design and application of nanogels in the context of drug delivery, summarizing the relevant characteristics for these materials as delivery vehicles for siRNA. Through the layering of multiple, orthogonal chemistries in a nanogel structure, we can impart multiple functions to the materials. We consider nanogels as a platform technology, where each functional element of the particle may be independently tuned to optimize the particle for the desired application. For instance, we can modify the shell compartment of a vehicle for cell-specific targeting or evasion of the innate immune system, whereas other compartments may incorporate fluorescent probes or regulate the encapsulation and release of macromolecular therapeutics. Proof-of-principle experiments have demonstrated the utility of multifunctional nanogels. For example, using a simple core/shell nanogel architecture, we have recently reported the delivery of siRNA to chemosensitize drug resistant ovarian cancer cells. Ongoing efforts have resulted in several advanced hydrogel structures, including biodegradable nanogels and multicompartment spheres. In parallel, our research group has studied other properties of the nanogels, including their behavior in confined environments and their ability to translocate through small pores

Central Province: Text summaries, maps, code lists and village identification

The major purpose of the Papua New Guinea Agricultural Systems Project is to produce information on small holder (subsistence) agriculture at provincial and national levels (Allen et al 1995). Information was collected by field observation, interviews with villagers and reference to published and unpublished documents. Methods are described by Bourke et al. (1993). This Working Paper contains a written summary of the information on the Agricultural Systems in this Province, maps of the location of agriculture systems, a complete listing of all information in the database in coded form, and lists of villages with National Population Census codes, indexed by agricultural systems. This information is available as a map-linked database (GIS) suitable for use on a personal computer in ESRI and MapInfo formats. An Agricultural System is identified when a set of similar agricultural crops and practices occur within a defined area. Six criteria are used to distinguish one system from another: 1. Fallow type (the vegetation which is cleared from a garden site before cultivation). 2. Fallow period (the length of time a garden site is left unused between cultivations). 3. Cultivation intensity (the number of consecutive crops planted before fallow). 4. The staple, or most important, crops. 5. Garden and crop segregation (the extent to which crops are planted in separate gardens; in separate areas within a garden; or are planted sequentially). 6. Soil fertility maintenance techniques (other than natural regrowth fallows). Where one or more of these factors differs significantly and the differences can be mapped, then a separate system is distinguished. Where variation occurs, but is not able to be mapped at 1:500 000 scale because the areas in which the variation occurs are too small or are widely dispersed within the larger system, a subsystem is identified. Subsystems within an Agricultural System are allocated a separate record in the database, identified by the Agricultural System number and a subsystem number. Sago is a widespread staple food in lowland Papua New Guinea. Sago is produced from palms which are not grown in gardens. Most of the criteria above cannot be applied. In this case, systems are differentiated on the basis of the staple crops only. The Papua New Guinea Resource Information System (PNGRIS) is a GIS which contains information on the natural resources of PNG (Bellamy 1986). PNGRIS contains no information on agricultural practices, other than an assessment of land use intensity based on air photograph interpretation by Saunders (1993. The Agricultural Systems Project is designed to provide detailed information on agricultural practices and cropping patterns as part of an upgraded PNGRIS geographical information system. For this reason the Agricultural Systems database contains almost no information on the environmental settings of the systems, except for altitude and slope. The layout of the text descriptions, the database code files and the village lists are similar to PNGRIS formats (Cuddy 1987). The mapping of Agricultural Systems has been carried out on the same map base and scale as PNGRIS (Tactical Pilotage Charts, 1:500 000). Agricultural Systems were mapped within the areas of agricultural land use established by Saunders (1993) from aerial photography. Except where specifically noted, Agricultural Systems boundaries have been mapped without reference to PNGRIS Resource Mapping Unit (RMU) boundaries. Agricultural Systems are defined at the level of the Province (following PNGRIS) but their wider distribution is recognised in the database by cross-referencing systems which cross provincial borders. A preliminary view of the relationships between PNGRIS RMUs and the Agricultural Systems in this Province can be obtained from the listing of villages by Agricultural System, where RMU numbers are appended. Allen, B. J., R. M. Bourke and R. L. Hide 1995. The sustainability of Papua New Guinea agricultural systems: the conceptual background. Global Environmental Change 5(4): 297-312. Bourke, R. M., R. L. Hide, B. J. Allen, R. Grau, G. S. Humphreys and H. C. Brookfield 1993. Mapping agricultural systems in Papua New Guinea. Population Family Health and Development. T. Taufa and C. Bass. University of Papua New Guinea Press, Port Moresby: 205-224. Bellamy, J. A. and J. R. McAlpine 1995. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use Handbook. Commonwealth Scientific and Industrial Research Organisation for the Australian Agency for International Development. PNGRIS Publication No. 6, Canberra. Cuddy, S. M. 1987. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use: Code Files Part 1 Natural Resources. Division of Water and Land Resources, Commonwealth Scientific and Industrial Research Organisation and Land Utilization Section, Department of Primary Industry, Papua New Guinea, Canberra

West New Britain Province: Text summaries, maps, code lists and village identification

The major purpose of the Papua New Guinea Agricultural Systems Project is to produce information on small holder (subsistence) agriculture at provincial and national levels (Allen et al 1995). Information was collected by field observation, interviews with villagers and reference to published and unpublished documents. Methods are described by Bourke et al. (1993). This Working Paper contains a written summary of the information on the Agricultural Systems in this Province, maps of the location of agriculture systems, a complete listing of all information in the database in coded form, and lists of villages with National Population Census codes, indexed by agricultural systems. This information is available as a map-linked database (GIS) suitable for use on a personal computer in ESRI and MapInfo formats. An Agricultural System is identified when a set of similar agricultural crops and practices occur within a defined area. Six criteria are used to distinguish one system from another: 1. Fallow type (the vegetation which is cleared from a garden site before cultivation). 2. Fallow period (the length of time a garden site is left unused between cultivations). 3. Cultivation intensity (the number of consecutive crops planted before fallow). 4. The staple, or most important, crops. 5. Garden and crop segregation (the extent to which crops are planted in separate gardens; in separate areas within a garden; or are planted sequentially). 6. Soil fertility maintenance techniques (other than natural regrowth fallows). Where one or more of these factors differs significantly and the differences can be mapped, then a separate system is distinguished. Where variation occurs, but is not able to be mapped at 1:500 000 scale because the areas in which the variation occurs are too small or are widely dispersed within the larger system, a subsystem is identified. Subsystems within an Agricultural System are allocated a separate record in the database, identified by the Agricultural System number and a subsystem number. Sago is a widespread staple food in lowland Papua New Guinea. Sago is produced from palms which are not grown in gardens. Most of the criteria above cannot be applied. In this case, systems are differentiated on the basis of the staple crops only. The Papua New Guinea Resource Information System (PNGRIS) is a GIS which contains information on the natural resources of PNG (Bellamy 1986). PNGRIS contains no information on agricultural practices, other than an assessment of land use intensity based on air photograph interpretation by Saunders (1993. The Agricultural Systems Project is designed to provide detailed information on agricultural practices and cropping patterns as part of an upgraded PNGRIS geographical information system. For this reason the Agricultural Systems database contains almost no information on the environmental settings of the systems, except for altitude and slope. The layout of the text descriptions, the database code files and the village lists are similar to PNGRIS formats (Cuddy 1987). The mapping of Agricultural Systems has been carried out on the same map base and scale as PNGRIS (Tactical Pilotage Charts, 1:500 000). Agricultural Systems were mapped within the areas of agricultural land use established by Saunders (1993) from aerial photography. Except where specifically noted, Agricultural Systems boundaries have been mapped without reference to PNGRIS Resource Mapping Unit (RMU) boundaries. Agricultural Systems are defined at the level of the Province (following PNGRIS) but their wider distribution is recognised in the database by cross-referencing systems which cross provincial borders. A preliminary view of the relationships between PNGRIS RMUs and the Agricultural Systems in this Province can be obtained from the listing of villages by Agricultural System, where RMU numbers are appended. Allen, B. J., R. M. Bourke and R. L. Hide 1995. The sustainability of Papua New Guinea agricultural systems: the conceptual background. Global Environmental Change 5(4): 297-312. Bourke, R. M., R. L. Hide, B. J. Allen, R. Grau, G. S. Humphreys and H. C. Brookfield 1993. Mapping agricultural systems in Papua New Guinea. Population Family Health and Development. T. Taufa and C. Bass. University of Papua New Guinea Press, Port Moresby: 205-224. Bellamy, J. A. and J. R. McAlpine 1995. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use Handbook. Commonwealth Scientific and Industrial Research Organisation for the Australian Agency for International Development. PNGRIS Publication No. 6, Canberra. Cuddy, S. M. 1987. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use: Code Files Part 1 Natural Resources. Division of Water and Land Resources, Commonwealth Scientific and Industrial Research Organisation and Land Utilization Section, Department of Primary Industry, Papua New Guinea, Canberra