The Sustainable Development Goals, knowledge production and the global struggle over values

Chapter 1 in the book Knowledge for Justice: Critical Perspectives from Southern African-Nordic Research Partnerships

Democracy and the Discourse on Relevance Within the Academic Profession at Makerere University

Democracy and the Discourse of Relevance is set against the backdrop of the spread of neoliberal ideas and reforms since the 1980s, accepting also that these ideas are rooted in a longer history. It focuses on how neoliberalism has worked to transform the university sector and the academic profession. In particular, it examines how understandings of, and control over, what constitutes relevant knowledge have changed. Taken as a whole, these changes have sought to reorient universities and academics towards economic development in various ways. This includes the installation of strategies for how institutions and academics achieve recognition and status within the academy, the privatisation of educational services and the downgrading of the value of public higher education, as well as a steady shift away from the public funding for universities. Research universities are increasingly adopting a user- and market-oriented model, with an emphasis on meeting corporate demands, the privileging of short-term research, and a strong tendency to view utility, and the potential to sell intellectual property for profit, as primary criteria for determining the relevance of academic knowledge. The privatisation of education services and the reorienting of universities towards the needs of the ‘knowledge economy’ have largely succeeded in transforming the discourse around the role of the academic profession in society, including in many African countries. Makerere University in Uganda has often been lauded as an example of successful transformation along neoliberal lines. However, our research into the working lives of academics at Makerere revealed a very different picture. Far from epitomising the allegedly positive outcomes of neoliberal reform, academics and postgraduate students interviewed at Makerere provide worrying insights into the undermining of a vibrant and independent academic culture. The stories of the ordinary academics on the ground, the empirical focus of the book, are in contrast to the claimed successes of the university; and the official stories of the university leadership and administration paint a picture of an academic profession in crisis. With diminishing influence on deciding what is relevant knowledge and thus on processes of democratization of their own institution and society, academic freedom is also losing its value. This perspective from the ground-level exposes the many problems that neoliberal reforms have created for academics at Makerere, leaving them feeling disempowered, often reducing them to the status of consultants. We also show how a range of local initiatives ­are steadily increasing resistance to the neoliberal model. We consider how academics and others can further mobilise to regain control over what knowledge is considered relevant, and thereby deepen democracy. In so doing, we aim to highlight some responses and actions that have proven effective so far. Democracy and the Discourse of Relevance will hopefully help to change the systems that value knowledge in ways that are driving research institutions towards competitive and market-like behaviour. We also aim to contribute to contemporary debates about what knowledge is relevant

Fishing Trawler Event Detection: An Important Step Towards Digitization of Sustainable Fishing

Detection of anomalies within data streams is an important task that is useful for different important societal challenges such as in traffic control and fraud detection. To be able to perform anomaly detection, unsupervised analysis of data is an important key factor, especially in domains where obtaining labelled data is difficult or where the anomalies that should be detected are often changing or are not clearly definable at all. In this article, we present a complete machine learning based pipeline for real-time unsupervised anomaly detection that can handle different input data streams simultaneously. We evaluate the usefulness of the proposed method using three wellknown datasets (fall detection, crime detection, and sport event detection) and a completely new and unlabelled dataset within the domain of commercial fishing. For all datasets, our method outperforms the baselines significantly and is able to detect relevant anomalies while simultaneously having low numbers of false positives. In addition to the good detection performance, the presented system can operate in real-time and is also very flexible and easy to expand

Reviderte nasjonalregnskapstall 1970-2010

Næringsinndelingen i nasjonalregnskapet er nå tilpasset SSBs nye næringsstandard SN2007 som bygger på EU-standarden NACE Rev. 2. Alle EU- og EØS-land er forpliktet til å ta i bruk denne standarden fra høsten 2011. Statistisk sentralbyrå (2008) gir en detaljert beskrivelse av SN2007. Sammenliknet med den tidligere næringsstandarden, SN2002, som lå til grunn for nasjonalregnskapet, er det nå en mer detaljert inndeling av tjenesteytende næringer og en mer aggregert beskrivelse av industrien. Den nye inndelingen innebærer omfattende flytting av produksjonsaktiviteter mellom hovednæringer. informasjon og kommunikasjon, som omfatter forlagsvirksomhet (overført fra industri), telekommunikasjon (overført fra samferdsel), databehandling (overført fra forretningsmessig tjenesteyting), og dessuten film- og fjernsynsproduksjon (overført fra kulturell tjenesteyting). Bruttoproduktet i denne næringen utgjorde 83 milliarder kroner i 2010, og næringen sysselsatte 86 000 personer. Forlagsvirksomhet, telekommunikasjon og databehandling (tjenester tilknyttet informasjonsteknologi) er omtrent like store og utgjør hovedtyngden av virksomheten. Vannforsyning, avløp og renovasjon er også en ny hovednæring i næringsstandarden og i nasjonalregnskapet. Denne næringen inneholder blant annet gjenvinning av avfall som tidligere var en del av industrien. Den nye næringsstandarden er innarbeidet i nasjonalregnskapets tidsserier ved å omklassifisere produksjonsenheter i overensstemmelse med den nye næringsstandarden. Dette betyr at nasjonalregnskapet gir sammenliknbare tall over en 40-årsperiode for utviklingen i industri og andre næringer. I SSBs næringsstatistikk er den nye næringsstandarden lagt til grunn for tallene fra og med 2007

File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments

In this paper, we present initial results from our distributed edge systems research in the domain of sustainable harvesting of common good resources in the Arctic Ocean. Specifically, we are developing a digital platform for real-time privacy-preserving sustainability management in the domain of commercial fishery surveillance operations. This is in response to potentially privacy-infringing mandates from some governments to combat overfishing and other sustainability challenges. Our approach is to deploy sensory devices and distributed artificial intelligence algorithms on mobile, offshore fishing vessels and at mainland central control centers. To facilitate this, we need a novel data plane supporting efficient, available, secure, tamper-proof, and compliant data management in this weakly connected offshore environment. We have built our first prototype of Dorvu, a novel distributed file system in this context. Our devised architecture, the design trade-offs among conflicting properties, and our initial experiences are further detailed in this paper

The Democratic Developmental State: North-South Perspectives

The concept of a democratic developmental state is part of the current development discourse advocated by international aid agencies, deliberated on by academics, and embraced by policymakers in many emerging economies in the global South. What is noticeable in this discourse is how little attention has been paid to a discussion of the essence of a democratic developmental state, and much of what passes for theory is little more than policy-speak and political rhetoric.This volume fills a gap in the literature on the democratic developmental state. Analyzing the different approaches to the implementation of democratic developmental states in various countries, it evaluates the extent to which these are merely replicating the central tenets of the East Asian model of the developmental state or if they are succeeding in their attempts to establish a new and more inclusive conceptualization of the state. In particular, the authors scrutinize to what degree the attempts to build a democratic developmental state may be distorted by the imperatives of neoliberalism. The volume broadens the understanding of the Nordic model of a democratic developmental state and shows how it represents an additional, and perhaps contending understanding of the developmental state derived from the East Asian experience.Comparative Research Programme on Poverty (CROP) at the University of BergenpublishedVersio

Artificial intelligence in dry eye disease

Dry eye disease (DED) has a prevalence of between 5 and 50%, depending on the diagnostic criteria used and population under study. However, it remains one of the most underdiagnosed and undertreated conditions in ophthalmology. Many tests used in the diagnosis of DED rely on an experienced observer for image interpretation, which may be considered subjective and result in variation in diagnosis. Since artificial intelligence (AI) systems are capable of advanced problem solving, use of such techniques could lead to more objective diagnosis. Although the term ‘AI’ is commonly used, recent success in its applications to medicine is mainly due to advancements in the sub-field of machine learning, which has been used to automatically classify images and predict medical outcomes. Powerful machine learning techniques have been harnessed to understand nuances in patient data and medical images, aiming for consistent diagnosis and stratification of disease severity. This is the first literature review on the use of AI in DED. We provide a brief introduction to AI, report its current use in DED research and its potential for application in the clinic. Our review found that AI has been employed in a wide range of DED clinical tests and research applications, primarily for interpretation of interferometry, slit-lamp and meibography images. While initial results are promising, much work is still needed on model development, clinical testing and standardisation

Njord: a fishing trawler dataset

Fish is one of the main sources of food worldwide. The commercial fishing industry has a lot of different aspects to consider, ranging from sustainability to reporting. The complexity of the domain also attracts a lot of research from different fields like marine biology, fishery sciences, cybernetics, and computer science. In computer science, detection of fishing vessels via for example remote sensing and classification of fish from images or videos using machine learning or other analysis methods attracts growing attention. Surprisingly, little work has been done that considers what is happening on board the fishing vessels. On the deck of the boats, a lot of data and important information are generated with potential applications, such as automatic detection of accidents or automatic reporting of fish caught. This paper presents Njord, a fishing trawler dataset consisting of surveillance videos from a modern off-shore fishing trawler at sea. The main goal of this dataset is to show the potential and possibilities that analysis of such data can provide. In addition to the data, we provide a baseline analysis and discuss several possible research questions this dataset could help answer

Monitoring Algal Blooms with Complementary Sensors on Multiple Spatial and Temporal Scales

Climate change, and other human-induced impacts, are severely increasing the intensity and occurrences of algal blooms in coastal regions (IPCC, 2022). Ocean warming, marine heatwaves, and eutrophication promote suitable conditions for rapid phytoplankton growth and biomass accumulation. An increase in such primary producers provides food for marine organisms, and phytoplankton play an important global role in fixing atmospheric carbon dioxide and producing much of the oxygen we breathe. But harmful algal blooms (HABs) can also form, and they may adversely affect the ecosystem by reducing oxygen availability in the water, releasing toxic substances, clogging fish gills, and diminishing biodiversity. Understanding, forecasting, and ultimately mitigating HAB events could reduce their impact on wild fish populations, help aquaculture producers avoid losses, and facilitate a healthy ocean. Phytoplankton respond rapidly to changes in the environment, and measuring the distribution of a bloom and its species composition and abundance is essential for determining its ecological impact and potential for harm. Satellite remote sensing of chlorophyll concentration has been used extensively to observe the development of algal blooms. Although this tool has wide spatial and temporal (nearly daily) coverage, it is limited to surface ocean waters and cloud-free days. Microscopic analyses of water and net samples allow much closer examination of the species present in a bloom and their abundance, but this is a time-consuming process that collects only discrete point samples, sparsely distributed in space and time. Neither of these methods alone captures the rapid evolution of algal blooms, the spatial and temporal patchiness of their distributions, or their high local variability. In situ optical devices and imaging sensors mounted on mobile platforms such as autonomous underwater vehicles (AUVs) and uncrewed surface vehicles (USVs) capture fine-scale temporal trends in plankton communities, while uncrewed aerial vehicles (UAVs) complement satellite remote sensing. Use of such autonomous platforms offers the flexibility to react to local conditions with adaptive sampling techniques in order to examine the marine environments in real time. Here we present an integrated approach to observing blooms—an “observational pyramid”—that includes both classical and newer, complementary observation methods (Figure 1). We aim to identify trends in phytoplankton blooms in a region with strong aquaculture activity on the Atlantic coast of mid-Norway. Field campaigns were carried out in consecutive springs (2021 and 2022) in Frohavet, an area of sea sheltered by the Froan archipelago (Figure 2). The region is a shallow, highly productive basin with abundant fishing and a growing aquaculture industry. Typically, there are one or more large algal blooms here during the spring months. We use multi-instrumentation from macro- to a microscale perspectives, combined with oceanographic modeling and ground truthing, to provide tools for early algal bloom detection

Single-centre, triple-blinded, randomised, 1-year, parallel-group, superiority study to compare the effects of Roux-en-Y gastric bypass and sleeve gastrectomy on remission of type 2 diabetes and β-cell function in subjects with morbid obesity: a protocol for the Obesity surgery in Tønsberg (Oseberg) study

publishedVersio