Search results

Car dependency greatly contributes to the climate crisis and the corrosion of public space. In response, cities are introducing pedestrianisation, cycle lanes or tactical urban interventions aimed at repurposing streets for other road users. Framed as 'experiments', these reallocations of street space disrupt traditional transport planning procedures, often with promising results in promoting active travel. They are also associated with deep conflicts and criticism, especially by citizens defending the right to drive. Despite their ability to stop experiments, such conflicts have been little explored in the debates about experimentation and automobility. Similarly, street experiments have in most cases been uncritically embraced as a panacea for urban mobility problems, with little attention paid to experimentation as an expression of austerity urbanism. This paper aims to deepen our understanding of street experiments and their relationship to automobility by contextualising their conflictual unfolding as an expression of post-political planning in the age of austerity urbanism. Through a critical examination of the Torino Mobility Lab, a collaborative pedestrianisation experiment in Torino, we show how the governance-beyond-state setup of such projects masks a complex and contested coexistence of different meanings and processes for reimagining urban mobility and public space. We show how conflicts emerge embedded in the problematic and post-political governance of transport experiments. Nested within austerity urbanism, the experiment remains limited in its ability to create healthy spaces for participation. We conclude by highlighting the limitations and contradictions of attempts to overcome car dependency embedded in post-political frameworks and neoliberal-austerity planning practices.

Go alongs are a popular research method for studying everyday mobility practices, providing insight into embodied experiences of engaging with lived environments. Generally considered positive and productive, there is increasingly discussion of go-along interviews as emotionally, cognitively and physically demanding. We consider care an essential component of go-along interviews. However, this has been overlooked in scholarship; particularly the relationality of care, including care of the researcher. We provide four vignettes discussing our experiences of conducting 118 go-along interviews with residents living in or near London Low Traffic Neighbourhoods. Reflecting on care-full encounters, we highlight the role of reciprocity, solidarity, and mutual understanding, strengthened by the recognition of shared experiences. Reflecting on care-less encounters, we highlight how, by disrupting traditional research hierarchies, go-along interviews can expose marginalised and stigmatised researchers to abuse. Overall, our vignettes demonstrate that care is a relationally produced, shared accomplishment involving both the researcher and the participant.

Background: Conducting health impact assessments (HIAs) is a growing practice in various organizations and countries, yet scholarly interest in HIAs has primarily focused on the synergies between exposure and health outcomes. This limits our understanding of what factors influence HIAs and the uptake of their outcomes. This paper presents a framework for conducting participatory quantitative HIA (PQHIA) in low- and middle-income countries (LMICs), including integrating the outcomes back into society after an HIA is conducted. The study responds to the question: what are the different components of a participatory quantitative model that can influence HIA implementation in LMICs? Methods: To build the framework, we used a case study from a PQHIA fieldwork model developed in Port Louis (Mauritius). To explore thinking on the participatory components of the framework, we extract and analyze data from ethnographic material including fieldnotes, interviews, focus group discussions and feedback exercises with 14 stakeholders from the same case study. We confirm the validity of the ethnographic data using five quality criteria: credibility, transferability, dependability, confirmability, and authenticity. We build the PQHIA framework connecting the main HIA steps with factors influencing HIAs. Results: The final framework depicts the five standard HIA stages and summarizes participatory activities and outcomes. It also reflects key factors influencing PQHIA practice and uptake of HIA outcomes: costs for participation, HIA knowledge and interest of stakeholders, social responsibility of policymakers, existing policies, data availability, citizen participation, multi-level stakeholder engagement and multisectoral coordination. The framework suggests that factors necessary to complete a participatory HIA are the same needed to re-integrate HIA results back into the society. There are three different areas that can act as facilitators to PQHIAs: good governance, evidence-based policy making, and access to resources. Conclusions: The framework has several implications for research and practice. It underlines the importance of applying participatory approaches critically while providing a blueprint for methods to engage local stakeholders. Participatory approaches in quantitative HIAs are complex and demand a nuanced understanding of the context. Therefore, the political and cultural contexts in which HIA is conducted will define how the framework is applied. Finally, the framework underlines that participation in HIA does not need to be expensive or time consuming for the assessor or the participant. Yet, participatory quantitative models need to be contextually developed and integrated if they are to provide health benefits and be beneficial for the participants. This integration can be facilitated by investing in opportunities that fuel good governance and evidence-based policy making.

Background: Conducting health impact assessments (HIAs) is a growing practice in various organizations and countries, yet scholarly interest in HIAs has primarily focused on the synergies between exposure and health outcomes. This limits our understanding of what factors influence HIAs and the uptake of their outcomes. This paper presents a framework for conducting participatory quantitative HIA (PQHIA) in low- and middle-income countries (LMICs), including integrating the outcomes back into society after an HIA is conducted. The study responds to the question: what are the different components of a participatory quantitative model that can influence HIA implementation in LMICs?. Methods: To build the framework, we used a case study from a PQHIA fieldwork model developed in Port Louis (Mauritius). To explore thinking on the participatory components of the framework, we extract and analyze data from ethnographic material including fieldnotes, interviews, focus group discussions and feedback exercises with 14 stakeholders from the same case study. We confirm the validity of the ethnographic data using five quality criteria: credibility, transferability, dependability, confirmability, and authenticity. We build the PQHIA framework connecting the main HIA steps with factors influencing HIAs. Results: The final framework depicts the five standard HIA stages and summarizes participatory activities and outcomes. It also reflects key factors influencing PQHIA practice and uptake of HIA outcomes: costs for participation, HIA knowledge and interest of stakeholders, social responsibility of policymakers, existing policies, data availability, citizen participation, multi-level stakeholder engagement and multisectoral coordination. The framework suggests that factors necessary to complete a participatory HIA are the same needed to re-integrate HIA results back into the society. There are three different areas that can act as facilitators to PQHIAs: good governance, evidence-based policy making, and access to resources. Conclusions: The framework has several implications for research and practice. It underlines the importance of applying participatory approaches critically while providing a blueprint for methods to engage local stakeholders. Participatory approaches in quantitative HIAs are complex and demand a nuanced understanding of the context. Therefore, the political and cultural contexts in which HIA is conducted will define how the framework is applied. Finally, the framework underlines that participation in HIA does not need to be expensive or time consuming for the assessor or the participant. Yet, participatory quantitative models need to be contextually developed and integrated if they are to provide health benefits and be beneficial for the participants. This integration can be facilitated by investing in opportunities that fuel good governance and evidence-based policy making.