Article by Haley Fitzpatrick, Tobias Luthe, and Birger Sevaldson: “To leverage the fullest potential of systemic design research in real-world contexts, more diverse and reflexive approaches are necessary. Especially for addressing the place-based and unpredictable nature of sustainability transformations, scholars across disciplines caution that standard research strategies and methods often fall short. While systemic design promotes concepts such as holism, plurality, and emergence, more insight is necessary for translating these ideas into practices for engaging in complex, real-world applications. Reflexivity is crucial to understanding these implications, and systemic design practice will benefit from a deeper discourse on the relationships between researchers, contexts, and methods. In this study, we offer an illustrated example of applying a diverse and reflexive systems oriented design approach that engaged three mountain communities undergoing sustainability transformations. Based on a longitudinal, comparative research project, a combination of methods from systemic design, social science, education, and embodied practices was developed and prototyped across three mountain regions: Ostana, Italy; Hemsedal, Norway; and Mammoth Lakes, California. The selection of these regions was influenced by the researchers’ varying levels of previous engagement. Reflexivity was used to explore how place-based relationships influenced the researchers’ interactions with each community. Different modes of reflexivity were used to analyze the contextual, relational, and boundary-related factors that shaped how the framing, format, and communication of each method and practice adapted over time. We discuss these findings through visualizations and narrative examples to translate abstract concepts like emergence and plurality into actionable insights. This study contributes to systemic design research by showing how a reflexive approach of weaving across different places, methods, and worldviews supports the critical facilitation processes needed to apply and advance methodological plurality in practice…(More)”
Feminist democratic innovations in policy and politics
Article by Paloma Caravantes and Emanuela Lombardo: “This article examines the potential of feminist democratic innovations in policy and institutional politics. It examines how feminist democratic innovations can be conceptualised and articulated in local institutions. Combining theories on democratic governance, feminist democracy, social movements, municipalism, decentralisation, gender equality policies and state feminism, it conceptualises feminist democratic innovations in policy and politics as innovations oriented at (a) transforming knowledge, (b) transforming policymaking and public funding, (c) transforming institutions, and (d) transforming actors’ coalitions. Through analysis of municipal plans and interviews with key actors, the article examines feminist democratic innovations in the policy and politics of Barcelona’s local government from 2015 to 2023. Emerging from the mobilisation of progressive social movements after the 2008 economic crisis, the findings uncover a laboratory of feminist municipal politics, following the election of a new government and self-proclaimed feminist mayor. Critical actors and an enabling political context play a pivotal role in the adoption of this feminist institutional politics. The article concludes by arguing that feminist institutional politics at the local level contribute to democratising policy and politics in innovative ways, in particular encouraging inclusive intersectionality and participatory discourses and practices…(More)”.
Why data about people are so hard to govern
Paper by Wendy H. Wong, Jamie Duncan, and David A. Lake: “How data on individuals are gathered, analyzed, and stored remains largely ungoverned at both domestic and global levels. We address the unique governance problem posed by digital data to provide a framework for understanding why data governance remains elusive. Data are easily transferable and replicable, making them a useful tool. But this characteristic creates massive governance problems for all of us who want to have some agency and choice over how (or if) our data are collected and used. Moreover, data are co-created: individuals are the object from which data are culled by an interested party. Yet, any data point has a marginal value of close to zero and thus individuals have little bargaining power when it comes to negotiating with data collectors. Relatedly, data follow the rule of winner take all—the parties that have the most can leverage that data for greater accuracy and utility, leading to natural oligopolies. Finally, data’s value lies in combination with proprietary algorithms that analyze and predict the patterns. Given these characteristics, private governance solutions are ineffective. Public solutions will also likely be insufficient. The imbalance in market power between platforms that collect data and individuals will be reproduced in the political sphere. We conclude that some form of collective data governance is required. We examine the challenges to the data governance by looking a public effort, the EU’s General Data Protection Regulation, a private effort, Apple’s “privacy nutrition labels” in their App Store, and a collective effort, the First Nations Information Governance Centre in Canada…(More)”
Designing an instrument for scaling public sector innovations
Paper by Mirte A R van Hout, Rik B Braams, Paul Meijer, and Albert J Meijer: “Governments worldwide invest in developing and diffusing innovations to deal with wicked problems. While experiments and pilots flourish, governments struggle to successfully scale innovations. Public sector scaling remains understudied, and scholarly suggestions for scaling trajectories are lacking. Following a design approach, this research develops an academically grounded, practice-oriented scaling instrument for planning and reflecting on the scaling of public sector innovations. We design this instrument based on the academic literature, an empirical analysis of three scaling projects at the Dutch Ministry of Infrastructure and Water Management, and six focus groups with practitioners. This research proposes a context-specific and iterative understanding of scaling processes and contributes a typology of scaling barriers and an additional scaling strategy to the literature. The presented instrument increases our academic understanding of scaling and enables teams of policymakers, in cooperation with stakeholders, to plan and reflect on a context-specific scaling pathway for public sector innovations…(More)”.
Objectivity vs affect: how competing forms of legitimacy can polarize public debate in data-driven public consultation
Paper by Alison Powell: “How do data and objectivity become politicized? How do processes intended to include citizen voices instead push them into social media that intensify negative expression? This paper examines the possibility and limits of ‘agonistic data practices’ (Crooks & Currie, 2021) examining how data-driven consultation practices create competing forms of legitimacy for quantifiable knowledge and affective lived experience. Drawing on a two-year study of a private Facebook group self-presenting as a supportive space for working-class people critical of the development of ‘low-traffic neighbourhoods’ (LTNs), the paper reveals how the dynamics of ‘affective polarization’ associated the use of data with elite and exclusionary politics. Participants addressed this by framing their online contributions as ‘vernacular data’ and also by associating numerical data with exclusion and inequality. Over time the strong statements of feeling began to support content of a conspiratorial nature, reflected at the social level of discourse in the broader media environment where stories of strong feeling gain legitimacy in right-wing sources. The paper concludes that ideologies of dataism and practices of datafication may create conditions for political extremism to develop when the potential conditions of ‘agonistic data practices’ are not met, and that consultation processes must avoid overly valorizing data and calculable knowledge if they wish to retain democratic accountability…(More)”.
Designing Digital Voting Systems for Citizens
Paper by Joshua C. Yang et al: “Participatory Budgeting (PB) has evolved into a key democratic instrument for resource allocation in cities. Enabled by digital platforms, cities now have the opportunity to let citizens directly propose and vote on urban projects, using different voting input and aggregation rules. However, the choices cities make in terms of the rules of their PB have often not been informed by academic studies on voter behaviour and preferences. Therefore, this work presents the results of behavioural experiments where participants were asked to vote in a fictional PB setting. We identified approaches to designing PB voting that minimise cognitive load and enhance the perceived fairness and legitimacy of the digital process from the citizens’ perspective. In our study, participants preferred voting input formats that are more expressive (like rankings and distributing points) over simpler formats (like approval voting). Participants also indicated a desire for the budget to be fairly distributed across city districts and project categories. Participants found the Method of Equal Shares voting rule to be fairer than the conventional Greedy voting rule. These findings offer actionable insights for digital governance, contributing to the development of fairer and more transparent digital systems and collective decision-making processes for citizens…(More)”.
The Need for Climate Data Stewardship: 10 Tensions and Reflections regarding Climate Data Governance
Paper by Stefaan Verhulst: “Datafication — the increase in data generation and advancements in data analysis — offers new possibilities for governing and tackling worldwide challenges such as climate change. However, employing new data sources in policymaking carries various risks, such as exacerbating inequalities, introducing biases, and creating gaps in access. This paper articulates ten core tensions related to climate data and its implications for climate data governance, ranging from the diversity of data sources and stakeholders to issues of quality, access, and the balancing act between local needs and global imperatives. Through examining these tensions, the article advocates for a paradigm shift towards multi-stakeholder governance, data stewardship, and equitable data practices to harness the potential of climate data for public good. It underscores the critical role of data stewards in navigating these challenges, fostering a responsible data ecology, and ultimately contributing to a more sustainable and just approach to climate action and broader social issues…(More)”.
Market Power in Artificial Intelligence
Paper by Joshua S. Gans: “This paper surveys the relevant existing literature that can help researchers and policy makers understand the drivers of competition in markets that constitute the provision of artificial intelligence products. The focus is on three broad markets: training data, input data, and AI predictions. It is shown that a key factor in determining the emergence and persistence of market power will be the operation of markets for data that would allow for trading data across firm boundaries…(More)”.
Citizen silence: Missed opportunities in citizen science
Paper by Damon M Hall et al: “Citizen science is personal. Participation is contingent on the citizens’ connection to a topic or to interpersonal relationships meaningful to them. But from the peer-reviewed literature, scientists appear to have an acquisitive data-centered relationship with citizens. This has spurred ethical and pragmatic criticisms of extractive relationships with citizen scientists. We suggest five practical steps to shift citizen-science research from extractive to relational, reorienting the research process and providing reciprocal benefits to researchers and citizen scientists. By virtue of their interests and experience within their local environments, citizen scientists have expertise that, if engaged, can improve research methods and product design decisions. To boost the value of scientific outputs to society and participants, citizen-science research teams should rethink how they engage and value volunteers…(More)”.
Using online search activity for earlier detection of gynaecological malignancy
Paper by Jennifer F. Barcroft et al: Ovarian cancer is the most lethal and endometrial cancer the most common gynaecological cancer in the UK, yet neither have a screening program in place to facilitate early disease detection. The aim is to evaluate whether online search data can be used to differentiate between individuals with malignant and benign gynaecological diagnoses.
This is a prospective cohort study evaluating online search data in symptomatic individuals (Google user) referred from primary care (GP) with a suspected cancer to a London Hospital (UK) between December 2020 and June 2022. Informed written consent was obtained and online search data was extracted via Google takeout and anonymised. A health filter was applied to extract health-related terms for 24 months prior to GP referral. A predictive model (outcome: malignancy) was developed using (1) search queries (terms model) and (2) categorised search queries (categories model). Area under the ROC curve (AUC) was used to evaluate model performance. 844 women were approached, 652 were eligible to participate and 392 were recruited. Of those recruited, 108 did not complete enrollment, 12 withdrew and 37 were excluded as they did not track Google searches or had an empty search history, leaving a cohort of 235.s
The cohort had a median age of 53 years old (range 20–81) and a malignancy rate of 26.0%. There was a difference in online search data between those with a benign and malignant diagnosis, noted as early as 360 days in advance of GP referral, when search queries were used directly, but only 60 days in advance, when queries were divided into health categories. A model using online search data from patients (n = 153) who performed health-related search and corrected for sample size, achieved its highest sample-corrected AUC of 0.82, 60 days prior to GP referral.
Online search data appears to be different between individuals with malignant and benign gynaecological conditions, with a signal observed in advance of GP referral date. Online search data needs to be evaluated in a larger dataset to determine its value as an early disease detection tool and whether its use leads to improved clinical outcomes…(More)”.