Socio-spatial justice through public participation?

In this presentation at the AESOP (Assosiation of European Schools of Planning) annual Congress in 2022, Laura Mark, Katharina Huseljić and Tobias Escher introduced a framework of distributive socio-spatial justice and the way consultation procedures can contribute, before evaluating the case study Elbchaussee in Hamburg regarding socio-spatial justice, using qualitative and quantitative results. 

Abstract

Our current transport system exhibits significant socio-spatial injustices as it has both major negative environmental effects and structurally disadvantages certain socio-economic groups. Planning processes increasingly include elements of public participation, often linked to the hope of better understanding and integrating different mobility needs into the planning process. However, so far there is little knowledge on whether public participation results indeed in more socio-spatial justice.

To approach this question, we focus on socio-spatial justice as distributive justice and investigate how well consultative planning procedures do actually lead to measures that both contribute to sustainability (i.e. reduce or redistribute negative external effects) and cater for the needs of disadvantaged groups (e.g. those with low income or education, women and disabled people). To this end, we have investigated in detail the case study of the reconstruction of the Elbchaussee, a representative main road of citywide importance in the district of Altona in Hamburg, Germany. We are drawing on both qualitative and quantitative data including expert interviews and public surveys.  

We first show that the process did result in planning measures that contribute slightly to ecological sustainability. Second, in particular through improving the situation for pedestrians and cyclists as well as the quality of stay, the measures should contribute to more justice for some groups but this is recognized only by non-male groups. Beyond this there are no effects for people with low income, low education, those with mobility restrictions or with particular mobility needs often associated with these groups. Overall, we conclude that the consultative planning process provides only a small contribution to socio-spatial justice and we discuss potential explanations.

Key Findings

  • The consultative planning process as a whole resulted in measures that contribute slightly to socio-spatial justice, since they support the transition to more sustainable mobility and will benefit some disadvantages groups, though both to a limited degree.
  • We find that the consultation procedure had no significant influence on the policy. In terms of socio-spatial justice, no positive effects can be traced back to the consultation procedure. Notably, those that participated in the consultation did indeed report less satisfaction with the measures.
  • We trace those limited contributions back to some general features of consultation and the current planning system, but also find that in the case study the scope of possible influence was very limited due to external restrictions and power imbalances.

Publication

We are working on a publication for a peer-reviewed journal. The publication will be linked here as soon as it is published.

A Corpus of German Citizen Contributions in Mobility Planning: Supporting Evaluation Through Multidimensional Classification

In this publication in the Conference on Language Resources and Evaluation, Julia Romberg, Laura Mark and Tobias Escher introduce a collection of annotated datasets that promotes the development of machine learning approaches to support the evaluation of public participation contributions.

Abstract

Political authorities in democratic countries regularly consult the public in order to allow citizens to voice their ideas and concerns on specific issues. When trying to evaluate the (often large number of) contributions by the public in order to inform decision-making, authorities regularly face challenges due to restricted resources.

We identify several tasks whose automated support can help in the evaluation of public participation. These are i) the recognition of arguments, more precisely premises and their conclusions, ii) the assessment of the concreteness of arguments, iii) the detection of textual descriptions of locations in order to assign citizens’ ideas to a spatial location, and iv) the thematic categorization of contributions. To enable future research efforts to develop techniques addressing these four tasks, we introduce the CIMT PartEval Corpus, a new publicly-available German-language corpus that includes several thousand citizen contributions from six mobility-related planning processes in five German municipalities. The corpus provides annotations for each of these tasks which have not been available in German for the domain of public participation before either at all or in this scope and variety.

Key findings

  • The CIMT PartEval Argument Component Corpus comprises 17,852 sentences from German public participation processes annotated as non-argumentative, premise, or major position.
  • The CIMT PartEval Argument Concreteness Corpus consists of 1,127 argumentative text spans that are annotated according to three levels of concreteness: low, intermediate, and high.
  • Der CIMT PartEval Geographic Location Corpus consists of 4,830 locations and the GPS coordinates for 2,529 proposals from public consultations.
  • The CIMT PartEval Thematic Categorization Corpus relies on a new hierarchical categorization scheme for mobility that captures modes of transport (non-motorized transport: cycling, walking, scooters; motorized transport: local public transport, long-distance public transport, commercial transport) and a number of specifications, such as moving or stationary traffic, new services, and inter- and multimodality. In total, 697 documents have been annotated according to this scheme.

Publication

Romberg, Julia; Mark, Laura; Escher, Tobias (2022, June). A Corpus of German Citizen Contributions in Mobility Planning: Supporting Evaluation Through Multidimensional Classification. In Proceedings of the Language Resources and Evaluation Conference (pp. 2874–2883), Marseille, France. European Language Resources Association. https://aclanthology.org/2022.lrec-1.308

Corpus available under

https://github.com/juliaromberg/cimt-argument-mining-dataset

https://github.com/juliaromberg/cimt-argument-concreteness-dataset

https://github.com/juliaromberg/cimt-geographic-location-dataset

https://github.com/juliaromberg/cimt-thematic-categorization-dataset

Robust Methods for Classifying Argument Components in Public Participation Processes for Mobility Planning

In this publication in the Workshop on Argument Mining, Julia Romberg and Stefan Conrad address the robustness of classification algorithms for argument mining to build reliable models that generalize across datasets.

Abstract

Public participation processes allow citizens to engage in municipal decision-making processes by expressing their opinions on specific issues. Municipalities often only have limited resources to analyze a possibly large amount of textual contributions that need to be evaluated in a timely and detailed manner. Automated support for the evaluation is therefore essential, e.g. to analyze arguments.

In this paper, we address (A) the identification of argumentative discourse units and (B) their classification as major position or premise in German public participation processes. The objective of our work is to make argument mining viable for use in municipalities. We compare different argument mining approaches and develop a generic model that can successfully detect argument structures in different datasets of mobility-related urban planning. We introduce a new data corpus comprising five public participation processes. In our evaluation, we achieve high macro F1 scores (0.76 – 0.80 for the identification of argumentative units; 0.86 – 0.93 for their classification) on all datasets. Additionally, we improve previous results for the classification of argumentative units on a similar German online participation dataset.

Key findings

  • We conducted a comprehensive evaluation of machine learning methods across five public participation process in German municipalities that differ in format (online participation platforms and questionnaires) and process subject.
  • BERT surpasses previously published argument mining approaches for public participation processes on German data for both tasks, reaching macro F1 scores of 0.76 – 0.80 for the identification of argumentative units and macro F1 scores of 0.86 – 0.93 for their classification.
  • In a cross-dataset evaluation, BERT models trained on one dataset can recognize argument structures in other public participation datasets (which were not part of the training) with comparable goodness of fit.
  • Such model robustness across datasets is an important step towards the practical application of argument mining in municipalities.

Publication

Romberg, Julia; Conrad, Stefan (2021, November). Citizen Involvement in Urban Planning – How Can Municipalities Be Supported in Evaluating Public Participation Processes for Mobility Transitions?. In Proceedings of the 8th Workshop on Argument Mining (pp. 89-99), Punta Cana, Dominican Republic. Association for Computational Linguistics. https://aclanthology.org/2021.argmining-1.9

Results of the first practical workshop of the junior research group CIMT

Our first practical workshop in summer 2020 focused on the question of how the evaluation of citizen contributions can be technically supported and what requirements practitioners have for a software solution designed to (partially) automate the evaluation.

More information can be found in the working paper (German version only!):

(Opportunities to) Mobilise for local political online participation

In this article in the Zeitschrift für Politikwissenschaft, Bastian Rottinghaus and Tobias Escher explore the question of who does (not) participate in digital participation formats for local mobility-related planning and to what extent personalised invitations can contribute to the mobilisation of a larger and more diverse group of participants.

Summary

Consistent findings of unequal political participation have been motivating different democratic innovations, including those that utilize the opportunities of information and communication technologies for political online participation. While previous research has established only a limited mobilizing potential of digital media, we still lack a good understanding of the mechanisms leading citizens to decide for or against engagement online. Therefore, we investigate who participates in opportunities for political online participation, what explains (non)-engagement and how effective personalized invitations are to increase and diversify participation. To address these questions, we conducted a comparative study of three almost identical instances of local online participation, relying on evidence from surveys of registered users and random samples of the local population.

Our results show that engagement in online participation is indeed significantly biased from the population towards resource-rich individuals who also differ in their assessment of the participation process and its results. This is despite the fact that knowledge of these participation opportunities is equally distributed among all social groups. While online aversion is a barrier for some, distrust in the participation process and lack of interest are more powerful reasons to refrain from engagement. Using a randomized-controlled field experiment we can confirm that personalized invitations are an effective instrument for mobilization that increased participation by a factor of four to seven and that can to a limited degree elicit participation from under-represented groups. These findings have a number of important implications for researchers and practitioners who aim to increase equality in political participation.

Key Findings

  • In 2017, largely identical online participation processes were carried out and analysed in three cities in North Rhine-Westphalia. In Bonn, Cologne-Ehrenfeld and Moers, the population was invited to submit suggestions for improvements to cycling on an online platform.
  • Initially, the usual participation patterns emerged, with above-average participation by highly educated and middle-aged men. One of the main reasons for participation was dissatisfaction with the cycling infrastructure.
  • A lack of knowledge about the participation process is the main reason for not participating. Our findings could show that all population groups were equally-well informed about the process, but in the end resource-rich groups were significantly more likely to decide to participate. Furthermore, there are some specific reservations about the online format, which represent an obstacle to online participation.
  • As part of a controlled field experiment, personalised letters were sent to a random selection of citizens with an invitation to the participation process. It was found that this increased participation by a factor of four to seven.
  • This invitation also mobilises additional groups that are otherwise under-represented in the consultation process. This applies, for example, to women and people with a lower level of formal education. They also have slightly different attitudes to ‘the usual suspects’ in that they are somewhat less critical of the existing transport infrastructure, but are also less positive about the results of the participation process.
  • Overall, this shows that personal invitations are an important means of mobilising a larger and more diverse group of citizens to participate in consultation processes, but they cannot eliminate the fundamental under-representation of people with fewer resources and political interests.

Publication

Rottinghaus, B., & Escher, T. (2020). Mechanisms for inclusion and exclusion through digital political participation: Evidence from a comparative study of online consultations in three German cities. Zeitschrift für Politikwissenschaft, 30(2), 261–298. https://doi.org/10.1007/s41358-020-00222-7