Mapping the service system that supports children and families in the context of place-based-disadvantage: Potential leverage points for intervention

Stuart, Jaimee; Krahe, Michelle; Branch, Sara; Gibson, Mandy

doi:10.1016/j.wss.2023.100165

Cited by 4 publications

(4 citation statements)

References 38 publications

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“…The choice to relocate is related to individual interests and subjective assessments of a region's attractiveness (Elshof et al, 2017). Availability of public services is among the crucial factors, particularly for families with children and regions with weaker socio-economic conditions (Stuart et al, 2023).…”

Section: Scientific Backgroundmentioning

confidence: 99%

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Human Capital at the Regional Level: Population Forecast Insights into Latvia from a Long-Term Perspective

Homutiņins,

Šipilova,

Aleksejeva

2024

Acad. J. Interdiscip. Stud.

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To remain prosperous and competitive, modern regions must meet the challenge of becoming smart and sustainable, and human capital has a key role in this context. Depopulation increases risks of human capital availability and emigration is a primary reason. Regions that are experiencing a decreased population must develop strategic sustainable regional development policies that consider scientifically based population forecasts. The youth population characterises regional potential for long-term human capital availability. First, children represent a region’s future employees and entrepreneurs. Second, children require availability of educational services at regional level, which promotes regional vitality. Third, the youth population indirectly demonstrates a region’s socio-economic attractiveness for living and working. This study employs the system dynamic method to forecast different population change scenarios at the regional level in Latvia. The results reveal a declining, long-term population tendency for working age and youth populations in Latvian regions. Overall, Latvian regions will remain extremely homogeneous in the long term, with minor differences in the short term. In conclusion, despite regional disparities in terms of quality of life with some leading examples, all regions will experience high emigration loss. Regional social, economic and environmental characteristics demonstrate a need to assess population change trends in a complex manner. This study provides data for understanding short- and long-term perspectives that must be addressed through sustainable regional development policies. Received: 27 October 2023 / Accepted: 24 March 2024 / Published: 5 May 2024

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Section: Scientific Backgroundmentioning

confidence: 99%

“…Overall, previous research indicates that social aspects in terms of health, education, public services and infrastructure (López-Penabad et al, 2022;Stuart et al, 2023) as well as job opportunities, unequal development and poverty (Suárez Roldan et al, 2023) are among the primary challenges for regional development.…”

Section: Socialmentioning

confidence: 99%

Human Capital at the Regional Level: Population Forecast Insights into Latvia from a Long-Term Perspective

Homutiņins,

Šipilova,

Aleksejeva

2024

Acad. J. Interdiscip. Stud.

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“…In seeking alternative methods, network analysis 35 has gained momentum as an accepted practice to quantitatively identify leverage points based on CLDs 8 , 23 – 30 , 36 – 55 —for example in public health 24 , 38 , 45 , 50 , 52 , 53 , 55 . Here, 22 of the 29 papers that we identified that adopt this practice were published in 2021 (4 papers 23 , 25 , 37 , 50 ), 2022 (8 papers 27 , 28 , 43 – 45 , 47 , 49 , 52 ), and 2023 (10 papers to date 26 , 30 , 36 , 38 , 39 , 41 , 42 , 46 , 53 , 55 ). Network analysis seemingly has the potential to mathematically analyse a CLD, which in this context can be considered a network of factors, to systematically find which factors represent leverage points.…”

Section: Introductionmentioning

confidence: 99%

“…The overarching approach taken in using network analysis to identify leverage points based on CLDs is to translate the CLD’s factors and arrows into an adjacency matrix, after which network analysis metrics can be employed. Metrics commonly applied in combination with CLDs are betweenness centrality 8 , 23 – 27 , 29 , 38 – 45 , 48 , 50 – 55 and closeness centrality 8 , 23 , 26 , 29 , 39 , 42 , 43 , 50 , 52 , 53 . The factor with the highest betweenness centrality lies on the highest number of shortest causal chains between pairs of other factors in the CLD 58 , hypothesised to indicate that it is an important mediator 8 , 24 , 26 , 29 , 38 , 42 .…”

Section: Introductionmentioning

confidence: 99%

Using network analysis to identify leverage points based on causal loop diagrams leads to false inference

Crielaard,

Quax,

Sawyer

et al. 2023

Sci Rep

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Network analysis is gaining momentum as an accepted practice to identify which factors in causal loop diagrams (CLDs)—mental models that graphically represent causal relationships between a system’s factors—are most likely to shift system-level behaviour, known as leverage points. This application of network analysis, employed to quantitatively identify leverage points without having to use computational modelling approaches that translate CLDs into sets of mathematical equations, has however not been duly reflected upon. We evaluate whether using commonly applied network analysis metrics to identify leverage points is justified, focusing on betweenness- and closeness centrality. First, we assess whether the metrics identify the same leverage points based on CLDs that represent the same system but differ in inferred causal structure—finding that they provide unreliable results. Second, we consider conflicts between assumptions underlying the metrics and CLDs. We recognise six conflicts suggesting that the metrics are not equipped to take key information captured in CLDs into account. In conclusion, using betweenness- and closeness centrality to identify leverage points based on CLDs is at best premature and at worst incorrect—possibly causing erroneous identification of leverage points. This is problematic as, in current practice, the results can inform policy recommendations. Other quantitative or qualitative approaches that better correspond with the system dynamics perspective must be explored.

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What does the Service System Know about the Community it Serves? A Grey Literature Review of Children, Young People, and Families Experiencing Place-based Disadvantage

Stuart,

Krahe,

Gibson

2023

Urban Policy and Research

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Mapping the service system that supports children and families in the context of place-based-disadvantage: Potential leverage points for intervention

Cited by 4 publications

References 38 publications

Human Capital at the Regional Level: Population Forecast Insights into Latvia from a Long-Term Perspective

Human Capital at the Regional Level: Population Forecast Insights into Latvia from a Long-Term Perspective

Using network analysis to identify leverage points based on causal loop diagrams leads to false inference

What does the Service System Know about the Community it Serves? A Grey Literature Review of Children, Young People, and Families Experiencing Place-based Disadvantage

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