Wie vermeiden wir den Matthäuseffekt in Reallaboren? Selektivität in partizipativen Prozessen

In the quest for (more) effective adaptation, demands are rising in adaptation policy practitioners to address systemic injustices. In practice, however, adaptation incrementalism dominates, i.e. small-scale, reactive solutions, especially as it relates to addressing vulnerable populations. Germany is exemplary of these tensions. Little research investigates the larger context factors which impede the root causes of vulnerability from being addressed, how to transition away from incrementalism, and the role environmental agencies can play in this. Applying historical materialist policy analysis, the article follows a three-step approach which examines context, actors, and processes. The context analysis demonstrates how effective means for social redistribution were reduced since the mid-1980s in Germany’s capitalist welfare state. This corresponds with heightened social vulnerability to climate change. The actor landscape is diversifying. In the past, social policy actors (and tasks) were underrepresented but are becoming more important. The policy process indicates a greater focus on vulnerable populations. Yet, the understanding of the structural root causes of peoples’ vulnerability and financial resources of the policy field remain limited. This corresponds with informatory instruments of shallow depth. An improved root cause analytic coupled with new alliances and policy mixes are a good starting point towards greater social justice in adaptation.

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Speaking of success: Real-world experiments for sustainability transformations and causal inference

Korzhenevych

2024

GAIA - Ecological Perspectives for Science and Society

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Reports of successful sustainability-oriented real-world experiments can be categorized by the type of explanatory approaches employed, namely, the variance approach, which looks for correlations, and the process approach, which draws causal inferences in a narrative way. Their validity could benefit from a more critical reflection on the data and methods used.This paper examines a sample of 20 sustainability-oriented real-world experiment reports from 2006 to 2020, with the aim of uncovering the logic and methods used to demonstrate their success, that means, to show that they achieved their stated objectives. Following a distinction often made in the social sciences, I look for features of either the variance or the process approach to causal inference. I find that reports of transition experiments, socio-technical experiments, and community-based interventions display characteristic features of the process approach. Reports of trials, pilots, and field experiments, on the other hand, mostly use the variance approach to demonstrate success. An important observation is the limited recognition of possible biases related to the methods used or the data. I describe a number of possible biases that may be of importance in the context of sustainability-oriented real-world experiments. Important examples include measurement errors and biases in participant selection. Recognising the biases and correcting them where necessary can strengthen the validity of the findings obtained and help other researchers in designing their experiments.

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Wie vermeiden wir den Matthäuseffekt in Reallaboren? Selektivität in partizipativen Prozessen

Cited by 3 publications

References 33 publications

#mobildabei: Ein Reallabor zur Stärkung von Mobilität und sozialer Teilhabe armutsbedrohter Personen

#mobildabei: Ein Reallabor zur Stärkung von Mobilität und sozialer Teilhabe armutsbedrohter Personen

Opportunities and limitations for social justice in Germany’s climate adaptation policy

Speaking of success: Real-world experiments for sustainability transformations and causal inference

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