Leverage Points—Places to Intervene in a System

Reider, David; Partner, Principal

doi:10.4324/9781849773386-15

Cited by 55 publications

(3 citation statements)

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“…Thus, this article supports the conception of a digital intervention and information system in Québec. Although technical and communicational at first glance, the literature review showed that engagement is socially anchored ( Boudreau LeBlanc et al, 2022 ; Meadows, 2009a ; Milestad et al, 2012 ). Thus, program’s logic model on AMU monitoring needs both data originators and users’ proactive participation, and also several societal facilitators.…”

Section: Discussionmentioning

confidence: 99%

Building a Logic Model to Foster Engagement and Learning Using the Case of a Province-Wide Multispecies Antimicrobial Use Monitoring System

Boudreau LeBlanc,

Motulsky,

Moreault

et al. 2023

Eval Rev

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Successfully designing and implementing a program is complex; it requires a reflexive balance between the available resources and the priorities of various stakeholders, both of which change over time. Logic models are theory-based evaluation approaches used to identify and address key challenges of a program. This article describes the process of building a logic model on advanced theories in complexity studies. The models aim to support a province-wide multispecies monitoring system of antimicrobial use (AMU), designed in collaboration with the animal health sector in Quebec (Canada). Based on a rigorous theoretical foundation, the logic model is built in three steps: (1) mapping, a narrative review of literature on similar programs in other jurisdictions; (2) framing, iterative consultations with project members to elaborate the logic model; (3) shaping, hypotheses based on the logic model. The model emerges from the reflexive balancing of current scientific knowledge and empirical insights to gather relevant information about stakeholders from interdisciplinary experts that led a 3-year consensus-building process within the community. Recognizing the challenge of unpacking theories for practical use, we illustrate how the process of an “open” logic model building could enable governance coordination in complex processes. Logic models are useful for evaluating public, private, and academic partnerships in One Health programs that characterize an adaptive governance process.

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Section: Discussionmentioning

confidence: 99%

Building a Logic Model to Foster Engagement and Learning Using the Case of a Province-Wide Multispecies Antimicrobial Use Monitoring System

Boudreau LeBlanc,

Motulsky,

Moreault

et al. 2023

Eval Rev

View full text Add to dashboard Cite

show abstract

“…Non-linearity is the idea that a complex problem cannot be described in a sequential, linear fashion, and thus an intervention in one part of the system may not necessarily result in an equal change to another part of the system (Meadows, 2008;Willy et al, 2003;Wright & Meadows, 2009). Understanding the distinction between interventions into a system that is perceived as linear versus into a system that is perceived as complex (Fischer & Riechers, 2019) can provide new methods for evaluation and contribute additional insights into how planning problems may (or may not) unfold.…”

Section: Non-linearitymentioning

confidence: 99%

“…Perhaps one of the strongest benefits of systems mapping and systems thinking overall, is its potential to uncover leverage points that can be used as building blocks to introduce targeted interventions into the system to generate effective solutions. Beyond identifying errors or negative interactions in the system, levers highlight potential points of intervention (Abson et al, 2017)-specific interventions that are contingent on the context of the system and its intended outcome (Fischer & Riechers, 2019;Wright & Meadows, 2009). Fischer and Riechers (2019) argue, 'a leverage point's perspective explicitly recognises influential, "deep" leverage points-places at which interventions are difficult but likely to yield truly transformative change' and further 'can function as a methodological boundary object-that is, providing a common entry point for academics from different disciplines and other societal stakeholders to work together ' (p. 115).…”

Section: Systems Mapping: Operationalizing Feedback Loopsmentioning

confidence: 99%

Addressing the need for more nuanced approaches towards transit‐induced gentrification: A case for a complex systems thinking framework

2023

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The role of public transportation has shifted over the last 2 decades as planners and policymakers increasingly integrate new transportation infrastructure as an economic growth tool that promotes density and desirability. This shift has also positioned new infrastructure as a driver for neighbourhood change and gentrification, leading to the evolution of literature that explores transit‐induced gentrification. As this scholarship grows however, research has become fragmented, as the political economy work, which frames much of gentrification, is antipathetic to the neoclassical perspective that frames transportation research. The resulting inconsistencies have left researchers calling for the integration of new and holistic approaches that can address growing gaps. With transit‐induced gentrification becoming more prevalent across large and mid‐sized cities, and research lacking methodological consistency, this review considers: Can a complex systems thinking framework be used to better understand and address the process of transit‐induced gentrification?

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From Requirements Engineering to Green Requirements Engineering

Penzenstadler

2015

Green in Software Engineering

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Leverage Points—Places to Intervene in a System

Cited by 55 publications

References 0 publications

Building a Logic Model to Foster Engagement and Learning Using the Case of a Province-Wide Multispecies Antimicrobial Use Monitoring System

Building a Logic Model to Foster Engagement and Learning Using the Case of a Province-Wide Multispecies Antimicrobial Use Monitoring System

Addressing the need for more nuanced approaches towards transit‐induced gentrification: A case for a complex systems thinking framework

From Requirements Engineering to Green Requirements Engineering

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